overpopulation and deforestation essay

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Population Growth and Deforestation: A Critical and Complex Relationship

June 1, 2004

Frederick A.B. Meyerson

Former Visiting Scholar

Social and Environmental Dimensions of Health

During the last two decades, agricultural expansion, logging, development, and other human activities caused the deforestation of more than 120,000 square kilometers each year. In contrast, an area only one-tenth that size was regained due to reforestation efforts and natural re-growth. 1 This is the continuation of an historical process that has left the world with less than half of its original forests. While population growth and density are unquestionably related to forest cover trends, there is no simple way to describe or predict that association. Not surprisingly, the relationship is as complex as the regional and cultural variations in human societies and the changes in those societies over time.

Nonetheless, important patterns are beginning to develop from the many studies that have been undertaken and the evolving debate around them. An overview of studies conducted in the 1980s and 1990s reveals a strong relationship between population growth and deforestation in Central America, East and West Africa, and South Asia, but a much less clear association in Amazonia (South America) and Central Africa. 2 In a number of more developed countries, such as the United States, China and Russia, forest cover has been recovering for some time after extensive earlier deforestation. 3

Emerging Trends

From the deforestation studies to date, a few generalizations can be made. At extremely low population densities (less than one to two persons per square kilometer), it is possible to maintain large amounts of forest intact in areas where the population can be sustained primarily through the harvesting of non-timber forest products rather than by agriculture. 4 However, even in sparsely inhabited areas, external forces such as demand for timber or cattle in other parts of the country or world can lead to deforestation that is not closely related to local population growth. This has been the case in parts of the Brazilian Amazon. 5

As agriculturally based population density increases in and near forested areas, the strongest relationship between population growth and deforestation occurs, as local people and young migrant families arrive at the forest frontier and clear land to provide more area for subsistence farming. 6 The poorer the soil quality, the lower the agricultural production per hectare, and the more land per capita is likely to be cleared. In Central America, population density and loss of forest cover are closely related at many scales: at the regional and national level, and in local areas inside and near forest reserves, such as the Maya Biosphere Reserve in Guatemala. 7 This relationship may overpower efforts to manage forests in protected areas, particularly where the local population is primarily dependent on subsistence agriculture (see figure).

Figure Population Density and Forest Cover: Central American Countries (1990 and 2000 Data)

Source: Updated (with data from Food and Agriculture Organization, The Global Forest Assessment 2000) from Frederick A.B. Meyerson, “Population, Biodiversity and Changing Climate,” Advances in Applied Biodiversity Science 4 (2003).

Reforestation in Key Developed and Developing Nations

In the case of more-developed countries, the relationship becomes much more complex. The population begins to shift away from dependence on agriculture as a livelihood and agriculture uses more capital and technology and less labor. In addition, food, fuel, and timber needs may be met through imports from other areas of the country and world. Thus, the northeastern part of the United States, almost entirely deforested by the middle of the 19th century, is now largely reforested because people abandoned agricultural uses of the land and now import most of their food and fuel and some of their timber. Both population and per capita consumption may continue to increase but are no longer associated with local forests and land use. This pattern is also occurring in parts of Europe and some countries in the former Soviet Union.

In a few large Asian countries, aggressive forest policy in the recent past has more than offset losses of forest cover from agricultural expansion and development. In spite of significant human population increases during the 1990s, India added 381,000 hectares (net) through tree plantation programs. 8 One recent study has suggested that this increase in forests is a function of India’s relatively closed economy and the resultant need to ensure domestic production of forest products, and therefore might not have occurred had India’s external markets been more open. 9 Similar plantation efforts in China have produced an even larger net increase in forests. The general principle from the experience of countries as different as the United States, China, and India may be that after going through an initial deforestation phase, the combination of the scarcity of forest products and rising economic fortunes can lead societies to value, replant, and manage forests.

Ecosystem and Biodiversity Challenges

It is important to note that planted forests are very different from original forest cover in terms of species composition (planted forests are often monocultures), ecosystem functions, and their ability to support a wide range of plant and animal species and withstand stress such as drought and disease. Natural tropical forests contain a large percentage of the world’s remaining biodiversity. More than half of remaining forested land is found in less-developed countries, and many tropical forests are in areas with high population growth rates, high poverty, low access to reproductive health services, and rapid migration.

One conservation challenge is that average population density and growth rates are significantly greater in areas with high biodiversity than in the other habitable parts of Earth’s surface. For instance, in sub-Saharan Africa, human population density is greatest in area with the highest number of species of birds, mammals, snakes, and amphibians. Some of these species are threatened with extinction. Nearly 20 percent of the world’s population (1.2 billion people) lives in these “biodiversity hotspots.” This makes conflicts between biodiversity and forest conservation, population, and development almost impossible to avoid.

Climate Change Uncertainty

A critical wild card in the population-forests equation is global, regional, and local climate change, which can alter temperature and precipitation patterns sufficiently so that the existing forest cover type can no longer be supported. This is particularly true in areas with significant dry seasons, where even a slight decrease in rainfall can produce more frequent and more destructive forest fires, preventing the regrowth of certain species and favoring others, or even changing the ecosystem permanently from forest to grasslands. The demographic characteristics of an area may facilitate this change by producing a more flammable mixture of fields and forests or by providing fire sources. In the long run, climate change is also likely to change the nature of human demands on forests, particularly in agricultural communities.

For More Information

Roger-Mark De Souza, John Williams, and Frederick A.B. Meyerson, “Critical Links: Population, Health, and the Environment,” Population Bulletin 58 , no. 3 (2003)

Jonathan G. Nash, Healthy People Need Healthy Forests — Population and Deforestation (Population Reference Bureau, 2001).

• Food and Agriculture Organization (FAO), The Global Forest Assessment 2000 (Rome: Food and Agriculture Organization, Committee on Forestry, 2000).
• Thomas K. Rudel, Kevin Flesher, Diana Bates, Sandra Baptista, and Peter Holmgren, “Tropical Deforestation Literature: Geographical and Historical Patterns,” Unasylva 203, Vol. 51 (2000): 11-18; Alexander S. Pfaff, “What drives deforestation in the Brazilian Amazon?” Journal of Economics and Management 37 (1999): 26-43.
• FAO, The Global Forest Assessment 2000.
• Phillip M. Fearnside, “Human Carrying Capacity Estimation in Brazilian Amazonia as the Basis for Sustainable Development,” Environmental Conservation 24 (1997): 271-82; and Frederick A.B. Meyerson, “Human Population Density, Deforestation and Protected Areas Management: A Multi-scale Analysis of Central America, Guatemala, and the Maya Biosphere Reserve, Proceedings of the International Union for the Scientific Study of Population, XXIV General Population Conference (Salvador, Brazil, 2001).
• C.H. Wood and David L. Skole, “Linking satellite, census, and survey data to study deforestation in the Brazilian Amazon,” in People and Pixels, ed. D. Liverman et al. (Washington, DC: National Academies Press, 1998).
• Suzi Kerr, Alexander S. Pfaff, and Arturo Sanchez, “Development and Deforestation: Evidence From Costa Rica (unpublished paper, 2003).
• Frederick A.B. Meyerson, “Population, Biodiversity and Changing Climate,” Advances in Applied Biodiversity Science 4 (2003), Chapter 11 (2003): 83-90.
• Andrew D. Foster and Mark R. Rosenzweig, “Economic Growth and the Rise of Forests,” The Quarterly Journal of Economics (May 2003): 601-637.
• A. Balmford et al., “Conservation Conflicts Across Africa,” Science 291 (2001): 2616-19.
• Richard P. Cincotta, Jennifer Wisnewski, and Robert Engelman, “Human Population in the Biodiversity Hotspots,” Nature 404 (2000): 990-92.

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• Published: 06 May 2020

Deforestation and world population sustainability: a quantitative analysis

• Mauro Bologna 1   na1 &
• Gerardo Aquino 2 , 3 , 4   na1  

Scientific Reports volume  10 , Article number:  7631 ( 2020 ) Cite this article

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• Applied mathematics
• Environmental impact
• Population dynamics
• Statistical physics, thermodynamics and nonlinear dynamics

In this paper we afford a quantitative analysis of the sustainability of current world population growth in relation to the parallel deforestation process adopting a statistical point of view. We consider a simplified model based on a stochastic growth process driven by a continuous time random walk, which depicts the technological evolution of human kind, in conjunction with a deterministic generalised logistic model for humans-forest interaction and we evaluate the probability of avoiding the self-destruction of our civilisation. Based on the current resource consumption rates and best estimate of technological rate growth our study shows that we have very low probability, less than 10% in most optimistic estimate, to survive without facing a catastrophic collapse.

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Introduction

In the last few decades, the debate on climate change has assumed global importance with consequences on national and global policies. Many factors due to human activity are considered as possible responsible of the observed changes: among these water and air contamination (mostly greenhouse effect) and deforestation are the mostly cited. While the extent of human contribution to the greenhouse effect and temperature changes is still a matter of discussion, the deforestation is an undeniable fact. Indeed before the development of human civilisations, our planet was covered by 60 million square kilometres of forest 1 . As a result of deforestation, less than 40 million square kilometres currently remain 2 . In this paper, we focus on the consequence of indiscriminate deforestation.

Trees’ services to our planet range from carbon storage, oxygen production to soil conservation and water cycle regulation. They support natural and human food systems and provide homes for countless species, including us, through building materials. Trees and forests are our best atmosphere cleaners and, due to the key role they play in the terrestrial ecosystem, it is highly unlikely to imagine the survival of many species, including ours, on Earth without them. In this sense, the debate on climate change will be almost obsolete in case of a global deforestation of the planet. Starting from this almost obvious observation, we investigate the problem of the survival of humanity from a statistical point of view. We model the interaction between forests and humans based on a deterministic logistic-like dynamics, while we assume a stochastic model for the technological development of the human civilisation. The former model has already been applied in similar contexts 3 , 4 while the latter is based on data and model of global energy consumption 5 , 6 used as a proxy for the technological development of a society. This gives solidity to our discussion and we show that, keeping the current rate of deforestation, statistically the probability to survive without facing a catastrophic collapse, is very low. We connect such probability to survive to the capability of humankind to spread and exploit the resources of the full solar system. According to Kardashev scale 7 , 8 , which measures a civilisation’s level of technological advancement based on the amount of energy they are able to use, in order to spread through the solar system we need to be able to harness the energy radiated by the Sun at a rate of ≈4 × 10 26 Watt. Our current energy consumption rate is estimated in ≈10 13 Watt 9 . As showed in the subsections “Statistical Model of technological development” and “Numerical results” of the following section, a successful outcome has a well defined threshold and we conclude that the probability of avoiding a catastrophic collapse is very low, less than 10% in the most optimistic estimate.

Model and Results

Deforestation.

The deforestation of the planet is a fact 2 . Between 2000 and 2012, 2.3 million Km 2 of forests around the world were cut down 10 which amounts to 2 × 10 5 Km 2 per year. At this rate all the forests would disappear approximatively in 100–200 years. Clearly it is unrealistic to imagine that the human society would start to be affected by the deforestation only when the last tree would be cut down. The progressive degradation of the environment due to deforestation would heavily affect human society and consequently the human collapse would start much earlier.

Curiously enough, the current situation of our planet has a lot in common with the deforestation of Easter Island as described in 3 . We therefore use the model introduced in that reference to roughly describe the humans-forest interaction. Admittedly, we are not aiming here for an exact exhaustive model. It is probably impossible to build such a model. What we propose and illustrate in the following sections, is a simplified model which nonetheless allows us to extrapolate the time scales of the processes involved: i.e. the deterministic process describing human population and resource (forest) consumption and the stochastic process defining the economic and technological growth of societies. Adopting the model in 3 (see also 11 ) we have for the humans-forest dynamics

where N represent the world population and R the Earth surface covered by forest. β is a positive constant related to the carrying capacity of the planet for human population, r is the growth rate for humans (estimated as r  ~ 0.01 years −1 ) 12 , a 0 may be identified as the technological parameter measuring the rate at which humans can extract the resources from the environment, as a consequence of their reached technological level. r ’ is the renewability parameter representing the capability of the resources to regenerate, (estimated as r ’ ~ 0.001 years −1 ) 13 , R c the resources carrying capacity that in our case may be identified with the initial 60 million square kilometres of forest. A closer look at this simplified model and at the analogy with Easter Island on which is based, shows nonetheless, strong similarities with our current situation. Like the old inhabitants of Easter Island we too, at least for few more decades, cannot leave the planet. The consumption of the natural resources, in particular the forests, is in competition with our technological level. Higher technological level leads to growing population and higher forest consumption (larger a 0 ) but also to a more effective use of resources. With higher technological level we can in principle develop technical solutions to avoid/prevent the ecological collapse of our planet or, as last chance, to rebuild a civilisation in the extraterrestrial space (see section on the Fermi paradox). The dynamics of our model for humans-forest interaction in Eqs. ( 1 , 2 ), is typically characterised by a growing human population until a maximum is reached after which a rapid disastrous collapse in population occurs before eventually reaching a low population steady state or total extinction. We will use this maximum as a reference for reaching a disastrous condition. We call this point in time the “no-return point” because if the deforestation rate is not changed before this time the human population will not be able to sustain itself and a disastrous collapse or even extinction will occur. As a first approximation 3 , since the capability of the resources to regenerate, r ′, is an order of magnitude smaller than the growing rate for humans, r , we may neglect the first term in the right hand-side of Eq. ( 2 ). Therefore, working in a regime of the exploitation of the resources governed essentially by the deforestation, from Eq. ( 2 ) we can derive the rate of tree extinction as

The actual population of the Earth is N  ~ 7.5 × 10 9 inhabitants with a maximum carrying capacity estimated 14 of N c  ~ 10 10 inhabitants. The forest carrying capacity may be taken as 1 R c  ~ 6 × 10 7 Km 2 while the actual surface of forest is \(R\lesssim 4\times {10}^{7}\) Km 2 . Assuming that β is constant, we may estimate this parameter evaluating the equality N c ( t ) =  βR ( t ) at the time when the forests were intact. Here N c ( t ) is the instantaneous human carrying capacity given by Eq. ( 1 ). We obtain β  ~  N c / R c  ~ 170.

In alternative we may evaluate β using actual data of the population growth 15 and inserting it in Eq. ( 1 ). In this case we obtain a range \(700\lesssim \beta \lesssim 900\) that gives a slightly favourable scenario for the human kind (see below and Fig.  4 ). We stress anyway that this second scenario depends on many factors not least the fact that the period examined in 15 is relatively short. On the contrary β  ~ 170 is based on the accepted value for the maximum human carrying capacity. With respect to the value of parameter a 0 , adopting the data relative to years 2000–2012 of ref. 10 ,we have

The time evolution of system ( 1 ) and ( 2 ) is plotted in Figs.  1 and 2 . We note that in Fig.  1 the numerical value of the maximum of the function N ( t ) is N M  ~ 10 10 estimated as the carrying capacity for the Earth population 14 . Again we have to stress that it is unrealistic to think that the decline of the population in a situation of strong environmental degradation would be a non-chaotic and well-ordered decline, that is also way we take the maximum in population and the time at which occurs as the point of reference for the occurrence of an irreversible catastrophic collapse, namely a ‘no-return’ point.

On the left: plot of the solution of Eq. ( 1 ) with the initial condition N 0  = 6 × 10 9 at initial time t  = 2000 A.C. On the right: plot of the solution of Eq. ( 2 ) with the initial condition R 0  = 4 × 10 7 . Here β  = 700 and a 0  = 10 −12 .

On the left: plot of the solution of Eq. ( 1 ) with the initial condition N 0  = 6 × 10 9 at initial time t  = 2000 A.C. On the right: plot of the solution of Eq. ( 2 ) with the initial condition R 0  = 4 × 10 7 . Here β  = 170 and a 0  = 10 −12 .

Statistical model of technological development

According to Kardashev scale 7 , 8 , in order to be able to spread through the solar system, a civilisation must be capable to build a Dyson sphere 16 , i.e. a maximal technological exploitation of most the energy from its local star, which in the case of the Earth with the Sun would correspond to an energy consumption of E D  ≈ 4 × 10 26 Watts, we call this value Dyson limit. Our actual energy consumption is estimated in E c  ≈ 10 13 Watts (Statistical Review of World Energy source) 9 . To describe our technological evolution, we may roughly schematise the development as a dichotomous random process

where T is the level of technological development of human civilisation that we can also identify with the energy consumption. α is a constant parameter describing the technological growth rate (i.e. of T ) and ξ ( t ) a random variable with values 0, 1. We consider therefore, based on data of global energy consumption 5 , 6 an exponential growth with fluctuations mainly reflecting changes in global economy. We therefore consider a modulated exponential growth process where the fluctuations in the growth rate are captured by the variable ξ ( t ). This variable switches between values 0, 1 with waiting times between switches distributed with density ψ ( t ). When ξ ( t ) = 0 the growth stops and resumes when ξ switches to ξ ( t ) = 1. If we consider T more strictly as describing the technological development, ξ ( t ) reflects the fact that investments in research can have interruptions as a consequence of alternation of periods of economic growth and crisis. With the following transformation,

differentiating both sides respect to t and using Eq. ( 5 ), we obtain for the transformed variable W

where \(\bar{\xi }(t)=2[\xi (t)-\langle \xi \rangle ]\) and 〈ξ 〉 is the average of ξ ( t ) so that \(\bar{\xi }(t)\) takes the values ±1.

The above equation has been intensively studied, and a general solution for the probability distribution P ( W , t ) generated by a generic waiting time distribution can be found in literature 17 . Knowing the distribution we may evaluate the first passage time distribution in reaching the necessary level of technology to e.g. live in the extraterrestrial space or develop any other way to sustain population of the planet. This characteristic time has to be compared with the time that it will take to reach the no-return point. Knowing the first passage time distribution 18 we will be able to evaluate the probability to survive for our civilisation.

If the dichotomous process is a Poissonian process with rate γ then the correlation function is an exponential, i.e.

and Eq. ( 7 ) generates for the probability density the well known telegrapher’s equation

We note that the approach that we are following is based on the assumption that at random times, exponentially distributed with rate γ , the dichotomous variable \(\bar{\xi }\) changes its value. With this assumption the solution to Eq. ( 9 ) is

where I n ( z ) are the modified Bessel function of the first kind. Transforming back to the variable T we have

where for sake of compactness we set

In Laplace transform we have

The first passage time distribution, in laplace transform, is evaluated as 19

Inverting the Laplace transform we obtain

which is confirmed (see Fig.  3 ) by numerical simulations. The time average to get the point x for the first time is given by

which interestingly is double the time it would take if a pure exponential growth occurred, depends on the ratio between final and initial value of T and is independent of γ . We also stress that this result depends on parameters directly related to the stage of development of the considered civilisation, namely the starting value T 1 , that we assume to be the energy consumption E c of the fully industrialised stage of the civilisation evolution and the final value T , that we assume to be the Dyson limit E D , and the technological growth rate α . For the latter we may, rather optimistically, choose the value α  = 0.345, following the Moore Law 20 (see next section). Using the data above, relative to our planet’s scenario, we obtain the estimate of 〈 t 〉 ≈ 180 years. From Figs.  1 and 2 we see that the estimate for the no-return time are 130 and 22 years for β  = 700 and β  = 170 respectively, with the latter being the most realistic value. In either case, these estimates based on average values, being less than 180 years, already portend not a favourable outcome for avoiding a catastrophic collapse. Nonetheless, in order to estimate the actual probability for avoiding collapse we cannot rely on average values, but we need to evaluate the single trajectories, and count the ones that manage to reach the Dyson limit before the ‘no-return point’. We implement this numerically as explained in the following.

(Left) Comparison between theoretical prediction of Eq. ( 15 ) (black curve) and numerical simulation of Eq. ( 3 ) (cyan curve) for γ  = 4 (arbitrary units). (Right) Comparison between theoretical prediction of Eq. ( 15 ) (red curve) and numerical simulation of Eq. ( 3 ) (black curve) for γ  = 1/4 (arbitrary units).

(Left panel) Probability p suc of reaching Dyson value before reaching “no-return” point as function of α and a for β  = 170. Parameter a is expressed in Km 2 ys −1 . (Right panel) 2D plot of p suc for a  = 1.5 × 10 −4 Km 2 ys −1 as a function of α . Red line is p suc for β  = 170. Black continuous lines (indistinguishable) are p suc for β  = 300 and 700 respectively (see also Fig.  6 ). Green dashed line indicates the value of α corresponding to Moore’s law.

Numerical results

We run simulations of Eqs. ( 1 ), ( 2 ) and ( 5 ) simultaneously for different values of of parameters a 0 and α for fixed β and we count the number of trajectories that reach Dyson limit before the population level reaches the “no-return point” after which rapid collapse occurs. More precisely, the evolution of T is stochastic due to the dichotomous random process ξ ( t ), so we generate the T ( t ) trajectories and at the same time we follow the evolution of the population and forest density dictated by the dynamics of Eqs. ( 1 ), ( 2 ) 3 until the latter dynamics reaches the no-return point (maximum in population followed by collapse). When this happens, if the trajectory in T ( t ) has reached the Dyson limit we count it as a success, otherwise as failure. This way we determine the probabilities and relative mean times in Figs.  5 , 6 and 7 . Adopting a weak sustainability point of view our model does not specify the technological mechanism by which the successful trajectories are able to find an alternative to forests and avoid collapse, we leave this undefined and link it exclusively and probabilistically to the attainment of the Dyson limit. It is important to notice that we link the technological growth process described by Eq. ( 5 ) to the economic growth and therefore we consider, for both economic and technological growth, a random sequence of growth and stagnation cycles, with mean periods of about 1 and 4 years in accordance with estimates for the driving world economy, i.e. the United States according to the National Bureau of Economic Research 21 .

Average time τ (in years) to reach Dyson value before hitting “no-return” point (success, left) and without meeting Dyson value (failure, right) as function of α and a for β  = 170. Plateau region (left panel) where τ  ≥ 50 corresponds to diverging τ , i.e. Dyson value not being reached before hitting “no-return” point and therefore failure. Plateau region at τ  = 0 (right panel), corresponds to failure not occurring, i.e. success. Parameter a is expressed in Km 2 ys −1 .

Probability p suc of reaching Dyson value before hitting “no-return” point as function of α and a for β  = 300 (left) and 700 (right). Parameter a is expressed in Km 2 ys −1 .

Probability of reaching Dyson value p suc before reaching “no-return” point as function of β and α for a  = 1.5 × 10 −4 Km 2 ys −1 .

In Eq. ( 1 , 2 ) we redefine the variables as N ′ =  N / R W and R ′ =  R / R W with \({R}_{W}\simeq 150\times {10}^{6}\,K{m}^{2}\) the total continental area, and replace parameter a 0 accordingly with a  =  a 0  ×  R W  = 1.5 × 10 −4 Km 2 ys −1 . We run simulations accordingly starting from values \({R{\prime} }_{0}\) and \({N{\prime} }_{0}\) , based respectively on the current forest surface and human population. We take values of a from 10 −5 to 3 × 10 −4 Km 2 ys −1 and for α from 0.01 ys −1 to 4.4 ys −1 . Results are shown in Figs.  4 and 6 . Figure  4 shows a threshold value for the parameter α , the technological growth rate, above which there is a non-zero probability of success. This threshold value increases with the value of the other parameter a . As shown in Fig.  7 this values depends as well on the value of β and higher values of β correspond to a more favourable scenario where the transition to a non-zero probability of success occurs for smaller α , i.e. for smaller, more accessible values, of technological growth rate. More specifically, left panel of Fig.  4 shows that, for the more realistic value β  = 170, a region of parameter values with non-zero probability of avoiding collapse corresponds to values of α larger than 0.5. Even assuming that the technological growth rate be comparable to the value α  = log(2)/2 = 0.345 ys −1 , given by the Moore Law (corresponding to a doubling in size every two years), therefore, it is unlikely in this regime to avoid reaching the the catastrophic ‘no-return point’. When the realistic value of a  = 1.5 × 10 4 Km 2 ys −1 estimated from Eq. ( 4 ), is adopted, in fact, a probability less than 10% is obtained for avoiding collapse with a Moore growth rate, even when adopting the more optimistic scenario corresponding to β  = 700 (black curve in right panel of Fig.  4 ). While an α larger than 1.5 is needed to have a non-zero probability of avoiding collapse when β  = 170 (red curve, same panel). As far as time scales are concerned, right panel of Fig.  5 shows for β  = 170 that even in the range α  > 0.5, corresponding to a non-zero probability of avoiding collapse, collapse is still possible, and when this occurs, the average time to the ‘no-return point’ ranges from 20 to 40 years. Left panel in same figure, shows for the same parameters, that in order to avoid catastrophe, our society has to reach the Dyson’s limit in the same average amount of time of 20–40 years.

In Fig.  7 we show the dependence of the model on the parameter β for a  = 1.5 × 10 −4 .

We run simulations of Eqs. ( 1 ), ( 2 ) and ( 5 ) simultaneously for different values of of parameters a 0 and α depending on β as explained in Methods and Results to generate Figs.  5 , 6 and 7 . Equations ( 1 ), ( 2 ) are integrated via standard Euler method. Eq. ( 5 ) is integrated as well via standard Euler method between the random changes of the variable ξ . The stochastic dichotomous process ξ is generated numerically in the following way: using the random number generator from gsl library we generate the times intervals between the changes of the dichotomous variable ξ  = 0, 1, with an exponential distribution(with mean values of 1 and 4 years respectively), we therefore obtain a time series of 0 and 1 for each trajectory. We then integrate Eq. ( 5 ) in time using this time series and we average over N  = 10000 trajectories. The latter procedure is used to carry out simulations in Figs.  3 and 4 as well in order to evaluate the first passage time probabilities. All simulations are implemented in C++.

Fermi paradox

In this section we briefly discuss a few considerations about the so called Fermi paradox that can be drawn from our model. We may in fact relate the Fermi paradox to the problem of resource consumption and self destruction of a civilisation. The origin of Fermi paradox dates back to a casual conversation about extraterrestrial life that Enrico Fermi had with E. Konopinski, E. Teller and H. York in 1950, during which Fermi asked the famous question: “where is everybody?”, since then become eponymous for the paradox. Starting from the closely related Drake equation 22 , 23 , used to estimate the number of extraterrestrial civilisations in the Milky Way, the debate around this topic has been particularly intense in the past (for a more comprehensive covering we refer to Hart 24 , Freitas 25 and reference therein). Hart’s conclusion is that there are no other advanced or ‘technological’ civilisations in our galaxy as also supported recently by 26 based on a careful reexamination of Drake’s equation. In other words the terrestrial civilisation should be the only one living in the Milk Way. Such conclusions are still debated, but many of Hart’s arguments are undoubtedly still valid while some of them need to be rediscussed or updated. For example, there is also the possibility that avoiding communication might actually be an ‘intelligent’ choice and a possible explanation of the paradox. On several public occasions, in fact, Professor Stephen Hawking suggested human kind should be very cautious about making contact with extraterrestrial life. More precisely when questioned about planet Gliese 832c’s potential for alien life he once said: “One day, we might receive a signal from a planet like this, but we should be wary of answering back”. Human history has in fact been punctuated by clashes between different civilisations and cultures which should serve as caveat. From the relatively soft replacement between Neanderthals and Homo Sapiens (Kolodny 27 ) up to the violent confrontation between native Americans and Europeans, the historical examples of clashes and extinctions of cultures and civilisations have been quite numerous. Looking at human history Hawking’s suggestion appears as a wise warning and we cannot role out the possibility that extraterrestrial societies are following similar advice coming from their best minds.

With the help of new technologies capable of observing extrasolar planetary systems, searching and contacting alien life is becoming a concrete possibility (see for example Grimaldi 28 for a study on the chance of detecting extraterrestrial intelligence), therefore a discussion on the probability of this occurring is an important opportunity to assess also our current situation as a civilisation. Among Hart’s arguments, the self-destruction hypothesis especially needs to be rediscussed at a deeper level. Self-destruction following environmental degradation is becoming more and more an alarming possibility. While violent events, such as global war or natural catastrophic events, are of immediate concern to everyone, a relatively slow consumption of the planetary resources may be not perceived as strongly as a mortal danger for the human civilisation. Modern societies are in fact driven by Economy, and, without giving here a well detailed definition of “economical society”, we may agree that such a kind of society privileges the interest of its components with less or no concern for the whole ecosystem that hosts them (for more details see 29 for a review on Ecological Economics and its criticisms to mainstream Economics). Clear examples of the consequences of this type of societies are the international agreements about Climate Change. The Paris climate agreement 30 , 31 is in fact, just the last example of a weak agreement due to its strong subordination to the economic interests of the single individual countries. In contraposition to this type of society we may have to redefine a different model of society, a “cultural society”, that in some way privileges the interest of the ecosystem above the individual interest of its components, but eventually in accordance with the overall communal interest. This consideration suggests a statistical explanation of Fermi paradox: even if intelligent life forms were very common (in agreement with the mediocrity principle in one of its version 32 : “there is nothing special about the solar system and the planet Earth”) only very few civilisations would be able to reach a sufficient technological level so as to spread in their own solar system before collapsing due to resource consumption.

We are aware that several objections can be raised against this argument and we discuss below the one that we believe to be the most important. The main objection is that we do not know anything about extraterrestrial life. Consequently, we do not know the role that a hypothetical intelligence plays in the ecosystem of the planet. For example not necessarily the planet needs trees (or the equivalent of trees) for its ecosystem. Furthermore the intelligent form of life could be itself the analogous of our trees, so avoiding the problem of the “deforestation” (or its analogous). But if we assume that we are not an exception (mediocrity principle) then independently of the structure of the alien ecosystem, the intelligent life form would exploit every kind of resources, from rocks to organic resources (animal/vegetal/etc), evolving towards a critical situation. Even if we are at the beginning of the extrasolar planetology, we have strong indications that Earth-like planets have the volume magnitude of the order of our planet. In other words, the resources that alien civilisations have at their disposal are, as order of magnitude, the same for all of them, including ourselves. Furthermore the mean time to reach the Dyson limit as derived in Eq.  6 depends only on the ratio between final and initial value of T and therefore would be independent of the size of the planet, if we assume as a proxy for T energy consumption (which scales with the size of the planet), producing a rather general result which can be extended to other civilisations. Along this line of thinking, if we are an exception in the Universe we have a high probability to collapse or become extinct, while if we assume the mediocrity principle we are led to conclude that very few civilisations are able to reach a sufficient technological level so as to spread in their own solar system before the consumption of their planet’s resources triggers a catastrophic population collapse. The mediocrity principle has been questioned (see for example Kukla 33 for a critical discussion about it) but on the other hand the idea that the humankind is in some way “special” in the universe has historically been challenged several times. Starting with the idea of the Earth at the centre of the universe (geocentrism), then of the solar system as centre of the universe (Heliocentrism) and finally our galaxy as centre of the universe. All these beliefs have been denied by the facts. Our discussion, being focused on the resource consumption, shows that whether we assume the mediocrity principle or our “uniqueness” as an intelligent species in the universe, the conclusion does not change. Giving a very broad meaning to the concept of cultural civilisation as a civilisation not strongly ruled by economy, we suggest for avoiding collapse 34 that only civilisations capable of such a switch from an economical society to a sort of “cultural” society in a timely manner, may survive. This discussion leads us to the conclusion that, even assuming the mediocrity principle, the answer to “Where is everybody?” could be a lugubrious “(almost) everyone is dead”.

Conclusions

In conclusion our model shows that a catastrophic collapse in human population, due to resource consumption, is the most likely scenario of the dynamical evolution based on current parameters. Adopting a combined deterministic and stochastic model we conclude from a statistical point of view that the probability that our civilisation survives itself is less than 10% in the most optimistic scenario. Calculations show that, maintaining the actual rate of population growth and resource consumption, in particular forest consumption, we have a few decades left before an irreversible collapse of our civilisation (see Fig.  5 ). Making the situation even worse, we stress once again that it is unrealistic to think that the decline of the population in a situation of strong environmental degradation would be a non-chaotic and well-ordered decline. This consideration leads to an even shorter remaining time. Admittedly, in our analysis, we assume parameters such as population growth and deforestation rate in our model as constant. This is a rough approximation which allows us to predict future scenarios based on current conditions. Nonetheless the resulting mean-times for a catastrophic outcome to occur, which are of the order of 2–4 decades (see Fig.  5 ), make this approximation acceptable, as it is hard to imagine, in absence of very strong collective efforts, big changes of these parameters to occur in such time scale. This interval of time seems to be out of our reach and incompatible with the actual rate of the resource consumption on Earth, although some fluctuations around this trend are possible 35 not only due to unforeseen effects of climate change but also to desirable human-driven reforestation. This scenario offers as well a plausible additional explanation to the fact that no signals from other civilisations are detected. In fact according to Eq. ( 16 ) the mean time to reach Dyson sphere depends on the ratio of the technological level T and therefore, assuming energy consumption (which scales with the size of the planet) as a proxy for T , such ratio is approximately independent of the size of the planet. Based on this observation and on the mediocrity principle, one could extend the results shown in this paper, and conclude that a generic civilisation has approximatively two centuries starting from its fully developed industrial age to reach the capability to spread through its own solar system. In fact, giving a very broad meaning to the concept of cultural civilisation as a civilisation not strongly ruled by economy, we suggest that only civilisations capable of a switch from an economical society to a sort of “cultural” society in a timely manner, may survive.

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Acknowledgements

M.B. and G.A. acknowledge Phy. C.A. for logistical support.

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Departamento de Ingeniería Eléctrica-Electrónica, Universidad de Tarapacá, Arica, Chile

Mauro Bologna

The Alan Turing Institute, London, UK

Gerardo Aquino

University of Surrey, Guildford, UK

Goldsmiths, University of London, London, UK

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M.B. and G.A. equally contributed and reviewed the manuscript.

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How is Deforestation Related to Population Growth?

Even though it is quite obvious, very few people out there know that deforestation and population growth are directly related to each other in such a manner that the rise in population invariably results in a rise in the rate at which deforestation occurs. Continue reading to see how deforestation is related to population growth...

Even though it is quite obvious, very few people out there know that deforestation and population growth are directly related to each other in such a manner that the rise in population invariably results in a rise in the rate at which deforestation occurs. Continue reading to see how deforestation is related to population growth…

We often get to hear that deforestation, which can be attributed to a wide range of human activities including agriculture and logging, is to be blamed for several environmental issues that planet Earth is facing today. While destruction of forest cover can be attributed to natural processes such as volcanoes and landslides as well, their role in this destruction is easily overshadowed by the role played by humans. Does that mean deforestation and population rise are directly related to each other?

There is absolutely no doubt about the fact that rising population tends to put a great deal of pressure on natural resources; and when we say natural resources we don’t just refer to fossil fuels and water, which we directly come in contact with, but also refer to the forests, marine resources, etc., which, though indirectly, play a crucial role in our lives. Nevertheless, here we will stress on the relationship between deforestation and population growth, in a bid to see how the rise in population can contribute to the destruction of forest cover.

Deforestation and Population Growth

According to a report compiled by the United Nations Framework Convention on Climate Change (UNFCCC), approximately 80 percent of the deforestation in the world today is attributed to agriculture (i.e. 48 percent to subsistence agriculture and 32 percent to commercial agriculture). Of the remaining 20 percent, roughly around 14 percent is attributed to logging, 5 percent to the use of firewood and remaining is utilized for other purposes.

All these human activities which are considered to be the causes of deforestation invariably rise with the rise in population. For instance, population growth is directly related to increase in the demand for food. In order to meet this demand for food, we have to produce more crop. In order to produce more crop, we require more land; and to get more land for cultivation we have started encroaching upon the forestland, cutting down trees and turning vast tracts of lush green forests into large fields.

Deforestation in forested areas starts with human settlements mushrooming in near-forest areas. As time elapses, these settlers begin producing their own food by resorting to subsistence agriculture for which they begin clearing forest land. If the fertility of soil is less, the crop produce is low which prompts humans to cultivate more area and leads to further encroachment on forestland.

While this practice is indeed helpful for us humans, species which inhabit these forested areas have to bear the brunt of this practice. Even in the age of metals, we are highly dependent on timber when it comes to construction; and this timber comes from felling of trees in various parts of the world. Large tracts of forestland are also cleared to fulfill the vested interests of the bigwigs in mining lobby with strong political influences.

The rapid rate at which forests are converted to agricultural lands can be attributed to the belief that forest conversion is more beneficial for humans than forest conservation. Since 1970, somewhere around 232,000 square miles of Amazon forest has been cleared to make way for agriculture and to obtain timber for construction activity.

Even today, these forests are cleared at the rate of 1.5 acres per second; which in turn has left several species in these forests endangered. This destruction of tropical rainforests, like the Amazon, is bound to affect the planet as a whole as these forests are home to half the species of plants and animals on the planet. (Not to forget, these forests are referred to as the lungs of our planet as they produce a significant amount of atmospheric oxygen that we require to survive.)

Population Density and Deforestation

Studies have revealed that the forest cover of a particular region can only be retained when the density of population for that region is low. When population density is as low as two people per sq km, it is possible to keep forest cover intact as the population can be sustained on non-timber forest products rather than resorting to agriculture.

However, this low population density has become more of a mythical concept of late; with the population density of the world (total land area excluding the continent of Antarctica) reaching 51 people per sq km of late. Similarly, sparsely populated regions of the world are also subjected to a considerable amount of deforestation with external factors such as timber requirement in the field of construction or cattle rearing coming into play.

While population growth continues to fuel deforestation, the effects of deforestation on population are also becoming pretty obvious in the form of climate change and related environmental issues which has put us on toes of late. That explains why developed nations like the United States and Russia have gone into a damage control mode, and are trying their best to recover forest cover which they lost to extensive deforestation during the initial phase of economic development.

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How to tackle the global deforestation crisis

Imagine if France, Germany, and Spain were completely blanketed in forests — and then all those trees were quickly chopped down. That’s nearly the amount of deforestation that occurred globally between 2001 and 2020, with profound consequences.

Deforestation is a major contributor to climate change, producing between 6 and 17 percent of global greenhouse gas emissions, according to a 2009 study. Meanwhile, because trees also absorb carbon dioxide, removing it from the atmosphere, they help keep the Earth cooler. And climate change aside, forests protect biodiversity.

“Climate change and biodiversity make this a global problem, not a local problem,” says MIT economist Ben Olken. “Deciding to cut down trees or not has huge implications for the world.”

But deforestation is often financially profitable, so it continues at a rapid rate. Researchers can now measure this trend closely: In the last quarter-century, satellite-based technology has led to a paradigm change in charting deforestation. New deforestation datasets, based on the Landsat satellites, for instance, track forest change since 2000 with resolution at 30 meters, while many other products now offer frequent imaging at close resolution.

“Part of this revolution in measurement is accuracy, and the other part is coverage,” says Clare Balboni, an assistant professor of economics at the London School of Economics (LSE). “On-site observation is very expensive and logistically challenging, and you’re talking about case studies. These satellite-based data sets just open up opportunities to see deforestation at scale, systematically, across the globe.”

Balboni and Olken have now helped write a new paper providing a road map for thinking about this crisis. The open-access article, “ The Economics of Tropical Deforestation ,” appears this month in the Annual Review of Economics . The co-authors are Balboni, a former MIT faculty member; Aaron Berman, a PhD candidate in MIT’s Department of Economics; Robin Burgess, an LSE professor; and Olken, MIT’s Jane Berkowitz Carlton and Dennis William Carlton Professor of Microeconomics. Balboni and Olken have also conducted primary research in this area, along with Burgess.

So, how can the world tackle deforestation? It starts with understanding the problem.

Replacing forests with farms

Several decades ago, some thinkers, including the famous MIT economist Paul Samuelson in the 1970s, built models to study forests as a renewable resource; Samuelson calculated the “maximum sustained yield” at which a forest could be cleared while being regrown. These frameworks were designed to think about tree farms or the U.S. national forest system, where a fraction of trees would be cut each year, and then new trees would be grown over time to take their place.

But deforestation today, particularly in tropical areas, often looks very different, and forest regeneration is not common.

Indeed, as Balboni and Olken emphasize, deforestation is now rampant partly because the profits from chopping down trees come not just from timber, but from replacing forests with agriculture. In Brazil, deforestation has increased along with agricultural prices; in Indonesia, clearing trees accelerated as the global price of palm oil went up, leading companies to replace forests with palm tree orchards.

All this tree-clearing creates a familiar situation: The globally shared costs of climate change from deforestation are “externalities,” as economists say, imposed on everyone else by the people removing forest land. It is akin to a company that pollutes into a river, affecting the water quality of residents.

“Economics has changed the way it thinks about this over the last 50 years, and two things are central,” Olken says. “The relevance of global externalities is very important, and the conceptualization of alternate land uses is very important.” This also means traditional forest-management guidance about regrowth is not enough. With the economic dynamics in mind, which policies might work, and why?

The search for solutions

As Balboni and Olken note, economists often recommend “Pigouvian” taxes (named after the British economist Arthur Pigou) in these cases, levied against people imposing externalities on others. And yet, it can be hard to identify who is doing the deforesting.

Instead of taxing people for clearing forests, governments can pay people to keep forests intact. The UN uses Payments for Environmental Services (PES) as part of its REDD+ (Reducing Emissions from Deforestation and forest Degradation) program. However, it is similarly tough to identify the optimal landowners to subsidize, and these payments may not match the quick cash-in of deforestation. A 2017 study in Uganda showed PES reduced deforestation somewhat; a 2022 study in Indonesia found no reduction; another 2022 study, in Brazil, showed again that some forest protection resulted.

“There’s mixed evidence from many of these [studies],” Balboni says. These policies, she notes, must reach people who would otherwise clear forests, and a key question is, “How can we assess their success compared to what would have happened anyway?”

Some places have tried cash transfer programs for larger populations. In Indonesia, a 2020 study found such subsidies reduced deforestation near villages by 30 percent. But in Mexico, a similar program meant more people could afford milk and meat, again creating demand for more agriculture and thus leading to more forest-clearing.

At this point, it might seem that laws simply banning deforestation in key areas would work best — indeed, about 16 percent of the world’s land overall is protected in some way. Yet the dynamics of protection are tricky. Even with protected areas in place, there is still “leakage” of deforestation into other regions. 

Still more approaches exist, including “nonstate agreements,” such as the Amazon Soy Moratorium in Brazil, in which grain traders pledged not to buy soy from deforested lands, and reduced deforestation without “leakage.”

Also, intriguingly, a 2008 policy change in the Brazilian Amazon made agricultural credit harder to obtain by requiring recipients to comply with environmental and land registration rules. The result? Deforestation dropped by up to 60 percent over nearly a decade. 

Politics and pulp

Overall, Balboni and Olken observe, beyond “externalities,” two major challenges exist. One, it is often unclear who holds property rights in forests. In these circumstances, deforestation seems to increase. Two, deforestation is subject to political battles.

For instance, as economist Bard Harstad of Stanford University has observed, environmental lobbying is asymmetric. Balboni and Olken write: “The conservationist lobby must pay the government in perpetuity … while the deforestation-oriented lobby need pay only once to deforest in the present.” And political instability leads to more deforestation because “the current administration places lower value on future conservation payments.”

Even so, national political measures can work. In the Amazon from 2001 to 2005, Brazilian deforestation rates were three to four times higher than on similar land across the border, but that imbalance vanished once the country passed conservation measures in 2006. However, deforestation ramped up again after a 2014 change in government. Looking at particular monitoring approaches, a study of Brazil’s satellite-based Real-Time System for Detection of Deforestation (DETER), launched in 2004, suggests that a 50 percent annual increase in its use in municipalities created a 25 percent reduction in deforestation from 2006 to 2016.

How precisely politics matters may depend on the context. In a 2021 paper, Balboni and Olken (with three colleagues) found that deforestation actually decreased around elections in Indonesia. Conversely, in Brazil, one study found that deforestation rates were 8 to 10 percent higher where mayors were running for re-election between 2002 and 2012, suggesting incumbents had deforestation industry support.

“The research there is aiming to understand what the political economy drivers are,” Olken says, “with the idea that if you understand those things, reform in those countries is more likely.”

Looking ahead, Balboni and Olken also suggest that new research estimating the value of intact forest land intact could influence public debates. And while many scholars have studied deforestation in Brazil and Indonesia, fewer have examined the Democratic Republic of Congo, another deforestation leader, and sub-Saharan Africa.

Deforestation is an ongoing crisis. But thanks to satellites and many recent studies, experts know vastly more about the problem than they did a decade or two ago, and with an economics toolkit, can evaluate the incentives and dynamics at play.

“To the extent that there’s ambuiguity across different contexts with different findings, part of the point of our review piece is to draw out common themes — the important considerations in determining which policy levers can [work] in different circumstances,” Balboni says. “That’s a fast-evolving area. We don’t have all the answers, but part of the process is bringing together growing evidence about [everything] that affects how successful those choices can be.”

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The Effect of Population Growth on the Environment: Evidence from European Regions

Hannes weber.

1 Department of Sociology, University of Mannheim, A5, 6, 68159 Mannheim, Germany

Jennifer Dabbs Sciubba

2 Department of International Studies, Rhodes College, 2000 North Parkway, Memphis, TN 38112 USA

There is a long-standing dispute on the extent to which population growth causes environmental degradation. Most studies on this link have so far analyzed cross-country data, finding contradictory results. However, these country-level analyses suffer from the high level of dissimilarity between world regions and strong collinearity of population growth, income, and other factors. We argue that regional-level analyses can provide more robust evidence, isolating the population effect from national particularities such as policies or culture. We compile a dataset of 1062 regions within 22 European countries and analyze the effect from population growth on carbon dioxide (CO 2 ) emissions and urban land use change between 1990 and 2006. Data are analyzed using panel regressions, spatial econometric models, and propensity score matching where regions with high population growth are matched to otherwise highly similar regions exhibiting significantly less growth. We find a considerable effect from regional population growth on carbon dioxide (CO 2 ) emissions and urban land use increase in Western Europe. By contrast, in the new member states in the East, other factors appear more important.

Introduction

Somewhere around 1990, the mood in Europe turned against limiting population growth. By the turn of the millennium, the dominant narrative had shifted from worries over “too many people” to worries over “too few people,” highlighting the global divergence between negative European population trends and those of less developed states still experiencing significant growth. In 1983, a majority of 52% of Italians considered the recent dramatic drop in the total fertility rate to 1.4 children per women in their country to be “a good thing” (Palomba et al. 1998 ). Only 15% thought the Italian population should increase, while a large majority preferred either a decreasing (29%) or a stationary population (52%) (see ibid.). By 1995, this picture had changed considerably. According to Eurobarometer survey data, 40% of Italians now wanted their nation to grow, with less than 20% supporting a population decline (European Commission 1995 ). In the year 2000, according to the second wave of the “Population Policy Acceptance Study,” only 8% of the respondents in 12 European countries preferred their respective populations to decrease, compared to 49% who favored an increase (Höhn et al. 2008 ). Rapid and intense population aging—and in many cases, shrinking—is partly responsible for this shift in European viewpoints on optimal population trends. Viewed in the context of Europe’s environmental plans, however, desires for population increase might contradict those states’ ambitious climate goals.

Primarily because of concerns over economic strains, the EU is scrambling to institute policies that soften the economic effects of population aging and decline on the size of the workforce (European Commission 2015 ). Yet, by 2020 the EU aims to reduce CO 2 emissions by 20% and achieve no new net urban land by 2050 (European Commission 2011 ). Can these population and environmental goals exist side by side? Has fear of “overpopulation” damaging the environment rightly been dismissed in Europe? To answer these questions we estimate the effect of population growth on two dimensions of environmental degradation in Europe, greenhouse gas (CO 2 ) emissions and urban land use, for 1062 European NUTS-3 regions. 1 We analyze CO 2 emissions and urban growth as outcomes in this paper since these factors are recognized as drivers of adverse climate change by both environmental research and EU policies. CO 2 emissions directly affect world climate, while urban growth can have (among other consequences) an additional effect on air pollution and carbon stock in soil and vegetation by soil sealing and increased vehicular traffic (see, e.g., De Ridder et al. 2008 ; Schulp et al. 2008 ).

Our results demonstrate that net population growth in Europe will undermine ambitious climate goals. While some cities and regions have been able to experience high or medium population growth and still reduce emissions, particularly in Western Europe, many regions have not. Reducing emissions of a growing population requires significant planning and investment. Contemporary population policies within EU member states are usually concerned with stimulating growth. Possible benefits for the environment accompanying low or negative population growth are rarely discussed in official documents (see, e.g., European Commission 2014 ).

In the European Union, fertility rates have been at or below replacement level for two or more decades in most countries and projections by the United Nations and others routinely expect Europe to shrink—the UN ( 2015 ) estimates Europe to lose 32,000 people by 2050. By contrast, Bijak et al. ( 2007 ) project the EU-27’s population to remain constant by 2052 in their “base” scenario, while higher immigration rates could lead to an increase to 563 million people by mid-century, up from 504 million in 2015 and 482 million in 2000. Migration is incredibly difficult to predict, but we do know that migrants will conform to the general consumption behavior of where they move to, rather than retaining consumption patterns from where they came. And if we consider density instead of just total population, “depopulation” is not imminent for the EU. After all, with around 116 people per km 2 , the EU’s population density is more than twice the world’s average and by far greater than the USA’s (35/km 2 ), Africa’s (36/km 2 ) and also Asia’s (87/km 2 ). Despite a lower per capita consumption of natural resources than the USA, Canada, or Australia, densely populated European countries such as the Netherlands, Belgium, the UK, or Germany have a high ecological footprint, i.e., they consume a multitude of renewable resources compared to what their lands produce (Wackernagel and Rees 1996 ).

Theoretical Accounts on the Population–Environment Link

The relation between population and environmental degradation is often considered straightforward: More people should have a greater impact on the environment, if all other factors (such as per capita consumption) remain unchanged. As Laurie Mazur ( 2012 , p. 2) writes, “if we increase by 30% by 2050, we must swiftly reduce our collective impact by a third just to maintain the disastrous status quo.” The formal expression of this idea is the famous IPAT decomposition (Holdren and Ehrlich 1974 ), where humans’ environmental impact ( I ) is conceived to be a product of population size ( P ), per capita affluence ( A ), and technology ( T ) per unit of affluence. IPAT is still frequently referred to in the scientific debate, in particular by critics of population–environment (P–E) studies (e.g., Angus and Butler 2011 ). However, researchers in this field have long acknowledged the limits of IPAT for empirical research. In many applications, T is simply a ratio of I and A , and thus, the relative impact of population growth cannot be empirically assessed (see, e.g., York et al. 2003 ). In addition, in its simplest form, IPAT neglects possible interactions between the right-hand side variables.

Problems with IPAT are less acute in its stochastic version known as STIRPAT (Dietz and Rosa 1997 ) which allows for over- or underproportional weights of the factors in the equation determined by empirical data. Unobserved variables or interactions lead to a large error term which informs the researcher that the model only partly captures what is going on in the real world. There are many mechanisms of environmental degradation that do not involve population size or growth (see, e.g., de Sherbinin et al. 2007 for an overview). In the following, we review theoretical arguments on the link between population and the two outcomes of interest in this paper: urban land use change and CO 2 emissions.

With regard to urban growth, Lambin et al. ( 2003 , p. 224) list five “high-level causes” of land use change, only one of which specifically involves population growth. The other causal pathways focus on, among other factors, changing economic opportunities, policy interventions, and cultural change. In recent decades, cities such as Liverpool (the UK) or Leipzig (Germany) have experienced urban sprawl during periods of population decline (Couch et al. 2005 ). Many mechanisms driving urbanization of previously undeveloped land exist in the absence of population growth: Investors seek to build out-of-center retail facilities on cheaper building sites, and many families prefer detached houses in the “green” periphery (ibid.). This is particularly the case if income levels rise and households can afford larger homes (Patacchini et al. 2009 ). Commuting costs and public transport infrastructure in and around cities are also obvious determinants of how and where urban growth occurs (ibid.). Historical trajectories, local policies, and cultural preferences affect how compact or dispersed residential areas are built. For instance, European cities such as Barcelona are often contrasted against North American cities with a comparable population size, but a much larger urban area (e.g., Catalán et al. 2008 ). As an example of a more complex mechanism, urban growth into formerly suburban or rural areas can depend on whether socially deprived areas with high crime rates are more prominent in city centers (as is typical for North America) or in suburbs (as in many European cities, see Patacchini et al. 2009 ). Nevertheless, urban growth should ceteris paribus be stronger in the case of rapid population growth as compared with a stagnant population scenario. More people lead to a greater demand for accommodations and traffic—the question is whether this direct effect is empirically suppressed by other mechanisms as outlined above. Research mostly finds that population growth fosters urban land cover change, but there are geographical differences. In their meta-analysis, Seto et al. ( 2011 ) find that urban land expansion in India and Africa is mainly driven by population growth, while in China, North America, and Europe the main factor is GDP growth.

With regard to CO 2 emissions, there are also conflicting expectations in the literature. In general, few seem to doubt that a causal effect from human activity on the level of CO 2 emissions exists, mostly as a result of fossil energy combustion for purposes such as residential heating or transportation (e.g., de Sherbinin et al. 2007 ). Even though there are considerable differences in per capita consumption of energy, more humans ceteris paribus emit more CO 2 . As O’Neill et al. ( 2012 , p. 159) emphasize, if all other determinants of emissions and all relevant causal pathways are accounted for in a statistical model, “population can only act as a scale factor and its elasticity should therefore be 1.” However, the indirect effect of population growth via interactions and feedbacks with other variables remains often unclear. For instance, Simon ( 1993 , 1994 ) famously assumed that while population growth might create shortages of resources, rising prices for goods made with those resources will motivate technological innovations (which are more likely to occur in large populations) and therefore, in the long run, “more people equals (…) a healthier environment” (Simon 1994 , p. 22). Similar to the view put forward by Boserup ( 1965 ), technology is seen as endogenous to population growth (and positively affected by it). On the other hand, recent research suggests that more efficient technologies are paradoxically accompanied by an increase in energy consumption and thus emissions rise despite technological progress (York and McGee 2016 ). Empirically, most research finds that population growth is positively associated with CO 2 emissions increase (Bongaarts 1992 ; MacKellar et al. 1995 ; Dietz and Rosa 1997 ; Shi 2003 ; York et al. 2003 ; O’Neill et al. 2012 ; Liddle 2013 ). Against this body of research, critics point out that the bivariate correlation between population growth and emissions growth on the level of countries is zero or even negative (Satterthwaite 2009 ): Many countries marked by rapid population growth have low levels and low growth rates in emissions, and vice versa. This perspective suggests that differences in consumption levels caused by economic inequality, rather than population size or growth, are responsible for CO 2 emissions increase.

The biggest theoretical challenges to P–E research arguably lie in the insufficient knowledge about interactions and feedbacks between population, environment, and other factors. Most notably, population growth can interact with affluence. It is well established that fertility rates vary with factors such as socioeconomic modernity (e.g., Lutz and Qiang 2002 ), especially education (Schultz 1993 ), and human capital (Becker et al. 1990 ). According to the theory of demographic transition (Caldwell 1976 ; Dyson 2010 ), lower infant and child mortality rates (offset by higher affluence levels) are the primary cause of fertility decline (because humans have fewer children if they can expect more of them to survive). Due to a delay between the onsets of mortality and fertility decline, a population grows rapidly for a certain period and then stabilizes at a higher level. After fertility levels have dropped, a country can enjoy the “demographic dividend” (Bloom et al. 2003 ), as many young adults enter the workforce, but have fewer children to take care of. This change in age structure can also be accompanied by changing aspirations and preferences for accommodation (e.g., larger living space) and consumption, as has happened, for instance, in China in recent decades (Zhu and Peng 2012 ). Thus, in terms of IPAT, a decrease in P (or delta P) can cause an increase in A (and vice versa) and therefore halting population growth could possibly result in more environmental degradation rather than less.

In sum, most scholars agree that population size and growth have a direct effect on urban land cover and CO 2 emissions if all other factors are held constant. However, some authors argue that indirect effects—e.g., interactions and feedback processes with income or technology—typically compensate or even reverse the direct effect from population over time. We cannot solve this controversy in this paper. Instead, our research objective is to assess the total effect (i.e., direct and indirect effects) from population growth on the environment in Europe. The goal is to come to reasonable assumptions about what would happen if Europe’s population grew more or less rapidly. As described above, we use two operationalizations for environmental degradation: urban land use growth and CO 2 emissions.

Methodological Issues and Research Design

Contemporary P–E studies typically follow one of three types of approaches. The first approach focuses on an in-depth understanding of the causal pathway from P to E, including interactions and feedback with other factors. This approach often involves qualitative research, e.g., in the form of case studies of a particular country or region (e.g., Lutz et al. 2002 ; Gorrenflo et al. 2011 ). These studies can provide valuable insight for quantitative research with regard to how to model these direct and indirect effects. Yet, it is often difficult to generalize these qualitative findings on how population, policies, culture, and the economy interact in a specific setting to other countries or regions. The second approach quantitatively analyzes large (mostly cross-country) datasets with various statistical methods (for recent reviews see Hummel et al. 2013 ; Liddle 2014 ). These include linear regressions (Shi 2003 ; York et al. 2003 ) or more advanced econometric techniques for the analysis of panel data (Liddle 2013 ). They seek to attain generalizable knowledge of how P and E are usually correlated. Yet, different model specifications (with regard to how to deal with endogeneity or interaction effects) have produced different results in the past. Finally, a third approach uses simulations to arrive at different scenarios and predictions for future trends under varying assumptions. Simulations can either be done with macro-level models (e.g., Bongaarts 1992 ; O’Neill et al. 2010 ) or with bottom-up agent-based simulations, where household decisions, policy reactions, and feedback processes are modeled to study the emergent macro-level outcome (e.g., An et al. 2005 ). The validity of these predictions depends on how well the set of assumptions calibrating the simulations reflects reality, and they are commonly critiqued for excluding relevant variables and oversimplifying with regard to indirect effects and interactions. For instance, O’Neill et al. ( 2010 ) do not explicitly model any feedback effects from affluence or environment on population growth, which is why Angus and Butler ( 2011 ) refer to their models as “Malthus in, Malthus out.”

One of the biggest methodological problems in global cross-country research is the high level of collinearity usually found for many socioeconomic, political, and other variables (Schrodt 2014 ). Many comparative studies in P–E research suffer from the dissimilarity of the observed cases with regard to nearly anything that might affect population, environment, or both. For instance, emission levels have increased considerably in developed countries such as France over the past century, whereas this increase has been only modest in developing countries such as Ethiopia. The opposite is true for population growth. Thus, the observed correlation between population growth and emissions change is negative, as pointed out by Satterthwaite ( 2009 ) and others. However, this can hardly lead to the conclusion that France’s low population growth was causally responsible for the increase in emissions and a much higher population growth rate would have benefitted the environment. This is because France and Ethiopia also differ with regard to previous levels of population density and state of the environment as well as many other economic, technological, and other factors. A better approach could be to match France to a similar country that has experienced notably higher (or lower) rates of population growth and compare emission levels between the two countries. This could certainly provide a better foundation for a counterfactual scenario to determine what would happen if France’s population grew more or less rapidly. There might just not be many countries that meet the requirements for such a design to provide us with a sample sufficiently large to conduct quantitative analyses.

We argue that a good way to find appropriate cases is to examine the sub-national level (as in, e.g., Cramer 2002 ). Regions within one country are affected by the same national policies and are usually highly similar with regard to many potentially relevant factors such as climate, culture, or technological standards. For instance, Siedentop and Fina ( 2012 ) find that country-specific drivers of urban land use are important beyond demographic and economic variables; this distinction cannot be made in global country-level analyses. We avoid a large number of potential fallacies if we compare population growth and environmental trends in two French regions as opposed to comparing France to Ethiopia.

It might seem counterintuitive to select contemporary Europe as the location to examine the effects of population growth. As is well known, Europe is the world region with by far the lowest growth rate. Empirical studies usually find a much stronger detrimental population effect on the environment on other continents (e.g., Seto et al. 2011 ; Liddle 2013 ). However, net population growth—whether through natural increase or migration—in higher-income European areas potentially has greater detrimental effects on the environment than does growth in a lower-income area because the average European inhabitant has such high consumption. Additionally, from a methodological perspective, European regions provide a good sample to study the effect of population change on greenhouse gas emissions and urban land use because population is growing in some European regions, while in others is stationary or declining. Europe also includes considerable variation with regard to changes in emissions and land use. At the same time, the broader demographic, socioeconomic, and political context is held constant to some extent—our sample includes only upper-middle-income countries so we can move beyond emphasis on consumption patterns that dominate discussions of population and environment at the global level, and can isolate population growth to see if it is still a relevant issue for environmental discussions in developed states. By contrast, previous studies have often compared countries at various stages of the demographic transition that are embedded in different socioeconomic and political contexts. This wide sample poses some serious methodological issues as well as a risk of misinterpreting the data. By analyzing sub-national regions, we can also achieve greater statistical power through a larger sample size.

All European countries have already completed the demographic transition, and fertility rates are at or below replacement level. Variation in population growth is therefore not rooted in different levels of human development or broad cultural values, factors that could also affect the environment. Even differences in fertility rates between urban and rural regions, which were prominent until the mid-twentieth century, have almost disappeared. For instance, in 1960, the total fertility rate (TFR) in Switzerland was below 2 in urban areas such as Geneva compared with 3.5 or more children per woman in several rural cantons; today in all cantons the TFR falls somewhere between 1.2 and 1.7 (Basten et al. 2012 ). Population growth in Europe today mainly depends on internal and external migration. Net migration into a region partly varies with economic factors, such as employment opportunities, as in, say, south–north movements within Italy. On the other hand, international migration, especially, is path dependent and networks often lead to spatial variation in inflows long after the original cause of the first migration wave is gone (see, e.g., Mayda 2010 ). Consider, for instance, that many immigrants in Europe came as workers in the 1960s and 1970s and clustered into industrial areas. Later, new immigrants continued to prefer these cities over other destinations because family members or other co-ethnics already live there, despite the decline in the heavy industry in cities such as Lille (France), Duisburg (Germany), or Malmö (Sweden), where employment or income levels are similar or even worse compared with other regions hosting fewer immigrants. It also seems reasonable to assume that migrants do not target specific cities or regions primarily due to their environmental quality. Thus, we can argue that population growth in European regions is at least partly exogenous to the other variables in the equation and therefore issues of endogeneity or unobserved interactions should be much smaller compared with global cross-country analyses.

Data and Statistical Models

Our dataset encompasses 1062 NUTS-3 regions within 22 countries where data were available for our main variables of interest. 2 All countries are EU member states. We analyze changes between two time points with regard to urban growth and CO 2 emissions. Data for urban growth come from the CORINE Land Cover (CLC) project, a satellite-based classification of land surface by the European Environmental Agency ( 2007 ), distributed by the European Spatial Planning Observation Network (ESPON 2012 ). We use the first and the third releases of CLC with reference years 1990 and 2006, respectively, and calculate the change in the proportion of land in a NUTS-3 region that is classified as “artificial surfaces” (CLC-1), i.e., urban fabric, industrial areas, transport, etc., between these years. For greenhouse gas emissions we use data from the Emission Database for Global Atmospheric Research (EDGAR), aggregated for European NUTS regions as part of the “Greener Economy” project by ESPON ( 2014 ). The dataset contains estimates for total CO 2 emissions from fossil fuel combustion (excluding emissions from organic carbon, large-scale biomass burning, aviation, and shipping, as these cannot be directly attributed to human activity within the region) for the years 2000 and 2008. Average annual population growth within the same time period is calculated using data from Eurostat ( 2015a ). 3 We include regional data for per capita GDP and GDP growth (from Eurostat 2015b ) in our models. A list of all variables with descriptive statistics is given in “ Appendix .”

How are trends in population growth, emissions, and urban land use connected to one another? In a first step, we use the total sample of regions. We specify a dynamic model where changes in environmental impact Δ y i (representing either urban land use or CO 2 emissions) in region i = 1, …, N are regressed on their level at the time of the previous observation ( y i , t - 1 ). 4 Using changes rather than levels in the dependent variable reduces the problem of non-stationarity that likely exists when analyzing time-series data of autoregressive phenomena such as land use cover. This is relevant because non-stationary processes imply the risk of finding spurious correlations (Granger and Newbold 1974 ). In addition, the lagged dependent variable (LDV) y i , t - 1 captures the unobserved time-constant causes that led to differences between regions in the first place and also controls for a “Matthew effect.” (Urban land cover change occurs more often in areas that are already highly urbanized.) Note that observations are not yearly, but refer to first and last years of the observed period (thus T = 2) due to data availability. For both population ( p ) and per capita GDP ( a ), we include lagged level as well as change over the observed time period. Total population and per capita GDP are log-transformed to account for skewed distributions. A squared term of GDP to test for an environmental Kuznets curve (see, e.g., Carson 2010 ) was tested, but dropped from the final models since there was no evidence for such a pattern in Europe. As an additional control, we include a dummy for coastal location ( c ) of a region. The regression parameters are denoted by β 0 to β 6 , while ε i is the regional-level error term. Model 1 reports an ordinary least squares (OLS) estimation based on the following equation:

In a second model, we consider spatial autocorrelation: Regions are likely influenced by neighboring areas because of, e.g., commuter networks between regions, leading to a correlation in error terms among nearby regions. For instance, we can expect a rural region close to a city to develop differently in terms of urban land change and CO 2 emissions compared to an otherwise similar but remote rural region. These expectations are in line with previous research showing that, e.g., urban expansion is affected by surrounding land use (Huang et al. 2009 ). In our data, a test for spatial autocorrelation reveals significant amounts of spatial interdependence: Moran’s I is .31 for urban land use change and .46 for CO 2 emissions change in our sample. Neighboring regions are defined by contiguity here, and a binary weight matrix is applied, where the value is 1 if regions are contiguous and 0 otherwise. We estimate a spatial lag model (see Ward and Gleditsch 2008 ; LeSage and Pace 2009 ), where a spatially lagged dependent variable is added to the model. In Eq. ( 2 ), the term W y denotes the spatially lagged dependent variable together with weight matrix W .

As a robustness test, we also use a distance-based concept of neighborhood since this might better capture some drivers of spatial dependence in our dependent variables (such as commuting flows). In addition to the spatial lag model, we also estimate a spatial error model and a spatial lag model where the independent variables are lagged as well. These models can be found in “ Appendix .”

Next, we add a country-specific error term α j which is allowed to correlate with the other predictors (equivalent to a set of M-1 dummy variables for country j = 1, …, M ). 5 These country fixed effects control for unobserved country-specific influences such as national environmental policies. The equation for Model 3 can accordingly be written as:

Since regions in formerly communist Central-Eastern European countries may be more similar to each other than to Western European regions, we run the same analysis as in Model 3 separately in subsamples of only Western (Model 4) and only Eastern (Model 5) regions. We used base R for OLS regressions (R Core Team 2013 ) and the spdep package (Bivand and Piras 2015 ) for spatial models.

Finally, we preprocess the data using different matching algorithms (see, e.g., Ho et al. 2007 ). The idea is that for every region with high population growth, we find a region with a considerably lower growth rate, but otherwise highly similar characteristics. This type of “most similar case” design results in a more balanced sample and arguably gets us as close to identifying the population growth effect as it can get with this quasi-experimental study design. Around 10% of all regions ( N = 96) in the sample have experienced population growth rates of 1% or more per year on average during the study period. These regions represent the “treatment” group. As reported below, this “treatment” is only weakly correlated with other predictor variables in the data and therefore issues of endogeneity appear to be of low salience. The control group consists of regions with less than 0.5% growth per year ( N = 815). This cutoff value is chosen arbitrarily, though the results do not change significantly if we use a somewhat different threshold. We perform one-to-one nearest neighbor matching with a propensity score matching algorithm (Ho et al. 2007 ). 6

The result leaves us with a sample of 96 high-growth and 96 most similar low-growth regions. We then compare the distributions of urban growth and change in CO 2 emissions between “treatment” and control cases. To deal with missing values we used multiple imputation, creating ten multiply imputed datasets with Amelia II software (Honaker et al. 2011 ). Matching and model estimation are performed in each of the datasets, and the results are averaged with Rubin’s ( 1987 ) rules. (Note that 1029 out of 1062 cases have complete information, so missingness is not a major issue in our data.) An acceptable balance between the distributions of the variables in the two groups can be achieved with the algorithm. In the matched dataset for urban growth, both the high and the low population growth groups consist of predominantly Western European regions (93 vs. 91%), around half of them with a coastline (compared with 22% in the total sample). Per capita GDP averages at 27,500 Euros in the treatment group and 27,300 Euros in the control group (compared with 23,000 Euros in the total sample). Mean GDP growth rates are 4.0% over the observed period of time in both groups; only in terms of initial population size (652,000 vs. 548,000) the average values differ somewhat. For CO 2 emissions, balance is equally acceptable. Initial level of emissions (4400 tons vs. 4200 tons), per capita GDP (27,500 Euros vs. 27,600 Euros), GDP growth (4.0 vs. 4.1%), coastal location (49 vs. 52%), and location in Western Europe (93 vs. 91%) are very similar among the high and the low population growth groups. Again, initial population size (652,000 vs. 571,000) slightly differs. Some examples from the match tables: Madrid, Spain (high population growth), was matched with Rome, Italy (low population growth). The Irish South-East (high growth) was paired with South Jylland, Denmark (low growth). Dutch city of Utrecht (high growth) was matched with Salzburg, Austria (low growth), while the fast-growing Algarve in southern Portugal was paired with French department of Yvelines, where population growth was low.

Figures  1 , ​ ,2, 2 , and ​ and3 3 show the regional variation in population growth, CO 2 emissions, and urban land use between the regions in our dataset. Population growth was highest in Spain and Ireland in the 2000s, as these two countries witnessed the largest increase in their immigrant populations (in percentage points), followed by Italy (see Fig.  1 ). For Germany and France, the 2000s was a decade of low net immigration, but France’s major urban agglomerations still increased. Many Central-Eastern European countries had a net population loss, although not all regions; several populations in metro areas around cities such as Budapest, Prague, or Poznan increased. Urban growth, as Fig.  2 shows, is clearly related to the level of urbanization that was already present in a region. Artificial land use increased strongest in the already highly densely populated regions in the Netherlands and West Germany, along the Spanish, Portuguese, and French coastlines and in their respective capital regions, around the Irish and Danish capitals, in the tourist hotspots of Tyrol and in the industrial centers of northern Italy and Polish Silesia and capital region. The amount of soil sealing (destruction of soil due to urbanization construction, such as buildings) of farmland, pasture, or forests was rather low in many rural regions, in the Baltics and Balkans, or in inland France and Spain, apart from their capitals. There are observable differences in CO 2 emissions between countries and regions, too (see Fig.  3 ). Emissions grew strongly in the Baltic countries and in many parts of Ireland, Spain, and Bulgaria. By contrast, Denmark, Germany, and the Czech Republic largely reduced the emission of CO 2 .

Population growth in 20 European countries, 2000–2008, average annual rate

Urban land use change in 20 European countries, 1990–2006

CO2 emissions change in 19 European countries, 2000–2008

Tables  1 and ​ and2 2 show the regression results using the full dataset with urban land change (Table  1 ) and CO 2 emissions change (Table  2 ) as the respective dependent variables. Table  1 confirms that population growth is positively correlated with urban growth. This effect holds when spatial autocorrelation (Model 2) and country-level fixed effects (Model 3) are taken into account, while the effect of GDP vanishes. When East and West are differentiated, a fairly strong positive effect for population growth is shown to exist in the West, while this effect is insignificant in the East. By contrast, urban growth is strongly determined by regional per capita GDP in the formerly communist countries, while affluence has no impact in the West.

Table 1

Predictors of urban growth as a percentage of total land use (logit-transformed) in 1062 European NUTS-3 regions between 1990 and 2006, all regions and by location in Eastern or Western Europe

Cells show unstandardized coefficients with standard errors in parentheses. * p  < .05 ** p  < .01 *** p  < .001

Table 2

Predictors of change in CO 2 emissions (in kilotons) in 1033 European NUTS-3 regions between 2000 and 2008, all regions and by location in Eastern or Western Europe

The pattern is similar for CO 2 emissions (see Table  2 ). One additional percentage point of annual population growth is associated with 2.5 additional kilotons CO 2 emitted between 2000 and 2008 in Western Europe. In the East, however, there is no significant correlation between population and emissions change. Rather, the interesting finding here is that the lagged value of CO 2 emissions is negatively related to its increase. This finding means emissions grow stronger in Eastern regions where the level has previously been low, indicating that these regions seem to “catch up” in terms of CO 2 emissions. These emissions are not related to economic activity, however, since the coefficient for GDP growth is negative in all models where country-specific differences are controlled for.

Our data lend some support for the argument that population growth in European regions is partly exogenous to other variables in question, where on the level of Western European regions, population growth between 2000 and 2008 is only weakly correlated with per capita GDP in 2000 ( r = .10) and even negatively with GDP growth ( r = − .19) for the observed period. Note, however, that in Eastern Europe, the correlation between regional per capita GDP in 2000 and population growth between 2000 and 2008 is considerably stronger ( r = .41) than in the West (while for GDP growth, the coefficient is also weak and negative (− .18)). This might indicate that in Eastern Europe, population growth is endogenous to wealth to some extent, probably as a result of intra-national (e.g., rural–urban) migration, as international migration only played a minor role in most Eastern countries during the period under study.

It is also instructive to compare the effect of per capita GDP between models with (Model 3) and without (Models 1 and 2) country-specific errors in Table  2 . Judging from Model 1, we would assume a strong negative relationship between GDP and CO 2 emissions in Europe. This could be interpreted as showing that European regions are beyond the turning point on an environmental Kuznets curve, and the higher the affluence, the cleaner the regions with regard to emissions. These differences can entirely be attributed to the country level, however, and disappear once the country level is included. Thus, it seems as if the more affluent countries have made greater efforts to reduce emissions, but within countries there is no such relationship. These differences point to a possible interaction between socioeconomic prosperity and country-level policies, while dismissing a direct negative effect from affluence on emissions. A research design restricted to cross-country comparison likely fails to differentiate the effects of this sort.

Finally, results from the preprocessed sample using propensity score matching are shown in Figs.  4 and ​ and5. 5 . Figure  4 displays differences in urban land take between regions with high population growth compared with a control group of otherwise most similar regions but where population growth was small or zero. Again, high population growth regions show a significantly larger increase in urban fabric compared with regions of similar size, affluence, and income growth, but with lower population growth. Urban land use increased at a mean rate which was more than twice as high in the high population growth regions compared with the control group. With regard to CO 2 emissions, the differences are similarly large (see Fig.  5 ). While regions with low to medium population growth have on average kept their level between 2000 and 2008, similar regions with higher population growth increased emissions by more than 10%. The significant population effect remains if we run multivariate models on this reduced sample where the other covariates are taken into account.

Urban land use change in European regions with high population growth and matched control group with low growth (red mark = mean).

Note Thick black lines denote the median, box limits are 25th and 75th percentile, respectively, red marks are mean values, and jitter points are regions ( N = 96 in high population growth group and N = 96 in control group). (Color figure online)

CO2 emissions change in European regions with high population growth and matched control group with low growth (red mark = mean).

So how are some European regions with high population growth able to achieve low CO 2 emissions? The city of Brussels, which put ambitious climate policies in place in 2004, provides one such example. The city set a specific target to reduce CO 2 emissions by 40% per capita by 2025, partly through high energy and air quality standards. Although population is growing, the city aims to improve air quality by encouraging public transportation and reducing car traffic by 20% from 2001 to 2018 (European Union 2016 ).

East Jylland provides another example. East Jylland forms the eastern portion of the continental portion of Denmark, north of Germany. The largest city in East Jylland is Arhus, which is considered the economic, trading, and cultural hub of both Jylland and Denmark (outside of Copenhagen). In 2008 and 2009, Arhus was named one of the six “Eco Cities” by the Danish Ministry of Climate and Energy—a scheme “developed in order to acknowledge cutting-edge cities and to inspire other local authorities to make increased efforts in the field of climate and energy” (Rasmussen and Christensen 2010 , p. 217). As a “cutting-edge” city in developing clean energy alternatives and fighting global warming, local officials in Arhus in 2007 committed the city to being CO 2 neutral by 2030 (ibid.). Arhus was also the first city to monitor and map its CO 2 emissions and to develop a “CO 2 calculator,” which is now used across Europe. The city’s current eco plan “consists of several generations of climate plans reaching towards 2030” (City of Aarhus 2016 ). The primary legs of these plans consist of: developing an extensive and efficient light rail, committing public funds to increasing the size of local forests and wetlands, improving biking accessibility and safety, improving the municipality’s heating system (which is derived from the local incineration plant), planning and implementing flood prevention plans, increasing public knowledge of and funding for housing energy efficiency, and finally, increasing public knowledge and public–private partnerships. In direct public spending on these goals, local authorities have committed over 72 million Euros. However, the actual sum is much larger when you take into account government subsidies for energy efficiency improvements, investments in current energy infrastructure, and public–private partnerships. These investments are paying off. For example, improvements to the city’s incinerator/zero-carbon energy producer have decreased CO 2 output by 60,000 tons per year, while investments into reforestation will begin absorbing nearly 14 tons of CO 2 annually (City of Aarhus 2016 ).

Hamburg, in northern Germany, is a case of low population growth and low emissions. With around 1.7 million inhabitants, Hamburg is one of the European Union’s largest cities and its population grew at a modest 0.48% per annum during the study period. The city won the European Union’s award for “Europe’s Green Capital” in 2011. Rather than expanding outwards, Hamburg is focusing on redeveloping formerly industrial areas (brownfields), such as HafenCity, Hamburg, which sits on 388 acres and is slated to add 5500 homes, commercial areas, green space, offices, schools—including a university—and daycare, all following the city’s green building standards. Hamburg’s “urban densification” efforts, as opposed to urban sprawl, prevent the city’s ecological footprint from spreading outward, potentially converting rural lands into suburban areas (Benfield 2011 ). Hamburg’s city leaders have made raising awareness about air quality among its residents a priority and have “ambitious climate protection goals” that aim to reduce Hamburg’s CO 2 emissions by 40% by 2020 and by 80% by 2050. Investments in energy-saving measures in public buildings are partly responsible for reducing the per capita emissions by 15% against 1990 (European Commission 2009 ).

Finally, Dublin, which has similar characteristics to Hamburg in terms of per capita income and other variables in our dataset, illustrates the environmental consequences possible with high population growth (1.51% during the period of study). With a growing population and growing emissions, Dublin, Ireland, does not represent the typical trend in European environmental standards. Between 1990 and 2006, Dublin’s annual emissions increased by almost 15,000 kilotons (CO 2 ). The majority of that increase in emissions came from the rapidly increasing transport and residential sectors as a result of the transportation and housing demands of Dublin’s burgeoning population. In fact, the transport sector has shown an increase of 165% from 1990 to 2006 (Environmental Protection Agency 2006 ). In addition, the Environmental Protection Agency projects Ireland will fail to meet its obligations under the EU emissions reduction agreement by 2020 (ibid). As a solution to Dublin’s growing population and rising emissions, the Dublin City Council’s 2016 –2022 Development Plan proposes redeveloping “vacant, derelict, and under-used lands with a focus on areas close to public transport corridors as well as areas of under-utilized physical and social infrastructure.” The city council also recognizes the importance of green infrastructure and has identified it as significantly contributing “in the areas of development management, climate change and environmental risk management” (Dublin City Council 2016 ).

Conclusion and Discussion

Bookchin ( 1996 , p. 30) suggests that “[t]he ‘population problem’ has a Phoenix-like existence: it rises from the ashes at least every generation and sometimes every decade or so.” But this is also true about the “depopulation problem,” which has recurred periodically over the last centuries (see Teitelbaum and Winter 1985 ). Both Malthusian (abundance of population is bad) and “cornucopian” (abundance of population is good) ideas are found in writings throughout recorded history (see, e.g., Schumpeter 1954 , pp. 250–251; Spengler 1998 , pp .4–5). Today, worries about “too few” instead of “too many people” seem to dominate the European discourse (Coole 2013 ). Trends in public discourse may or may not reflect empirical evidence on the topic. The question of whether population growth is harmful for the environment cannot be solved by solely looking at the discourse. The fact alone that people (perhaps unfoundedly) warned of “overpopulation” at times when world population was 0.2 billion (Plato), 1.0 billion (Malthus) or 3.5 billion (Ehrlich 1968 ) does not prove that any further increases from today’s 7 billion will necessarily come without further adverse consequences.

Population growth affects the environment in Europe: This is what our regional-level analysis of changes in urban land growth and CO 2 emissions indicates. However, we find significant differences between Western and Eastern Europe. In the West, regions with population growth are clearly experiencing both more urban growth as well as a greater increase in CO 2 emissions compared with stationary or shrinking regions. This suggests that population acts as a scale factor for environmental degradation in the West, as proponents of IPAT have argued. In the East, however, where population is mostly decreasing, there is no such correlation. Instead, urban growth in Eastern Europe seems to have more to do with affluence, and emissions have grown strongest in those regions where they have previously been low.

Many Western European regions are expected to experience population growth in the coming decades, mostly due to internal population shifts and international immigration. Immigration from non-European countries has clearly been one of the most salient political topics in recent years and will likely continue to be in the near future. However, it is also a strongly polarizing topic that has triggered schisms among many environmentalists (Huang 2012 ). Some have pointed out that, on a global level, migration is a zero-sum game and therefore world population growth matters, not changes in its spatial distribution (e.g., Mazur 2012 ). Others have shown that an individual’s environmental footprint grows after moving to a developed country (e.g., Conca et al. 2002 ). This argument obviously only holds if the unequal distribution of wealth and pollutants is assumed to persist. In any case, there are no reasons to believe that for a specific ecosystem under pressure from human population growth, it matters whether the additional people were born within some specific borders or somewhere else. And global environmental problems can certainly not be solved by limiting immigration to Europe. However, the empirical evidence suggests that future population growth as a result of immigration will make it harder for the European Union to achieve its climate goals.

See Tables  3 , ​ ,4, 4 , and ​ and5 5 .

Table 3

Descriptive statistics

Table 4

Determinants of urban land growth in European NUTS-3 regions (additional spatial model specifications)

Table 5

Determinants of CO 2 emission change in European NUTS-3 regions (additional spatial model specifications)

Compliance with Ethical Standards

Conflict of interest.

The authors declare that they have no conflict of interest.

1 The EU classifies its territory into four layers according to the Nomenclature des Unités Territoriales Statistiques (NUTS). The lowest level consists of NUTS-3 regions, designed to usually host between 150,000 and 800,000 people. France, for instance, consists of 100 NUTS-3 regions (départements), 20 NUTS-2 regions (régions), 8 NUTS-1 regions (groups of régions), and one NUTS-0 region (metropolitan France).

2 These countries are Austria, Belgium, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, France, Germany, Hungary, Italy, Ireland, Latvia, Lithuania, Luxembourg, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, and Spain. For CO 2 emissions, no data were available for Croatia. As a result of a reform of regional boundaries in the German state of Saxony, most regions in Saxony are missing from the analysis (note the white area on the maps).

3 For the models explaining urban growth which is measured between 1990 and 2006, population growth is averaged for this period. However, population data are not available for all regions since 1990 in the source dataset; for these regions the values refer to average population growth between the earliest available year since 1990 and 2008. Figure  1 displays average annual population growth rates between 2000 and 2008 for all regions.

4 Since urban land use is measured as a percentage of total land use and therefore 0–1 bounded, we use the logit transformation on this variable.

5 A random effects model was initially considered (providing similar results to the fixed effects model), but a Hausman test suggested superiority of the fixed effects estimator. Since we are not interested in estimating country-level predictors, we went without random effects (or multilevel) models.

6 Optimal matching and genetic matching were used as alternative algorithms. Since the results do not differ substantially, we only report the findings from propensity score matching here.

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Population growth, environmental degradation and climate change

More than a third of 50 recently surveyed Nobel laureates cited “population rise / environmental degradation” as the biggest threat to humankind. Second on the list was “nuclear war”, cited by 23 percent of the laureates, while no other issue was selected by more than 10 percent of respondents.

Are the survey responses of the Nobelists an accurate assessment of the relative importance of the threats facing humanity? And why were population increase and environmental damage bundled together in the survey, rather than being treated as separate issues?

A new report on population growth and sustainable development from the Population Division of UN DESA revisits the complex relationships linking population increase to social and economic development and environmental change.

On 23 February, the new report will be launched at the Future of the World Global Policy Dialogues: The Future of Population Growth kicking off at 8:30 a.m. EST. This event will be discussing the findings of the report and the linkages between population growth, socioeconomic development and environmental change.

The human population has experienced a period of unprecedented growth, more than tripling in size since 1950. It reached almost 7.8 billion in 2020 and is projected to grow to over 8.5 billion in 2030, the target date for achievement of the Sustainable Development Goals (SDGs).

This growth is the result of two trends: on the one hand, the gradual increase in average human longevity due to widespread improvements in public health, nutrition, personal hygiene and medicine, and on the other hand, the persistence of high levels of fertility in many countries. But is growth of the human population responsible for the environmental catastrophe our planet is facing?

The data tell a different story. For example, although high-income and upper-middle-income countries contain around 50 per cent of the global population, they contribute around 85 per cent of global emissions of carbon dioxide. Such emissions from upper-middle-income countries have more than doubled since 2000, even though the population growth rate was falling throughout this period. Most high-income countries are growing slowly if at all, and for some the population has been decreasing.

Could measures to limit future population growth make a substantial contribution to mitigating climate change? A fundamental challenge is the slow pace at which population trends change. The Intergovernmental Panel on Climate Change (IPCC) underlines that limiting global warming to 1.5°C would require rapid, far-reaching and unprecedented changes in all aspects of society to reach net-zero emissions by 2050.

Globally, population growth is slowing down and may come to a halt by around 2100, thanks to the smaller family sizes associated with social and economic development. However, given the intrinsic momentum of population growth, the range of plausible trajectories of global population over the next few decades is quite narrow. For this reason, further actions by Governments to limit the growth of populations would do little to mitigate the forces of climate change between now and 2050.

Instead of looking for solutions in demographic trends, achieving sustainability will depend critically on humanity’s capacity and willingness to increase resource efficiency in consumption and production and to decouple economic growth from damage to the environment. High-income and upper-middle-income countries should acknowledge their disproportionate contributions to global environmental damage and take the lead in building a more sustainable economic system for the benefit of future generations.

At the same time, in many low-income and lower-middle-income countries today, rapid population growth remains a matter of concern, because it adds to the challenges of achieving social and economic development and of ensuring that no one is left behind. The continuing high levels of fertility that drive such growth are both a symptom and a cause of slow progress in development, often linked to a lack of choice and empowerment among women and girls.

Rapid population growth makes it more difficult for low-income and lower-middle-income countries to commit sufficient resources to improving the health and education of their populations. Rapid growth and the associated slow progress in development also diminish their capacity to respond and adapt to emerging environmental threats, including those caused by climate change.

Achieving the SDG targets related to reproductive health, education and gender equality will require empowering individuals, particularly women, to make choices about the number and timing of their children. The experience of countries from all regions suggests that such changes will facilitate, and could potentially accelerate, the anticipated slowdown in global population growth over the coming decades.

Learn more about the Future of the World Global Policy Dialogues: The Future of Population Growth event on 23 February. Register here by 22 February. Learn more and access the report on the website of UN DESA’s Population Division .

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Essay on Deforestation

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Introduction:

Deforestation is the process of clearing trees and forest for other uses. Deforestation usually occurs due to city expansion. As habitats increase in cities, there is a need to create more space the for homes, organizations, and factories. This, however, has a damning effect on our environment.

Effect of Deforestation on the Environment:

Deforestation means fewer trees and more land. This has a serious adverse effect on our environment. On one hand, deforestation makes some animals homeless. Animals that survive in the forest might go extinct with less forest. On the other hand, deforestation is also the biggest cause of climate change around the world.

Preventing Deforestation:

Reducing or preventing deforestation is easier said than done. This is because trees are cut down because there is a pressing need to do so. Thus, to prevent deforestation we must try to reduce that need by making smarter choices in paper usage, city planning, migration, etc.

Conclusion:

The essence of plant life in the forest is unquestionable. To ensure a greener environment we must all join the efforts in reducing deforestation.

Deforestation is definitely one of the most troubling of all problems which has plagued our environment. It is important more than ever to take care of the green cover or else it can jeopardize the existence of life on Earth. It is owing to the presence of green trees that we get the oxygen needed to breathe in.

However, because of excessive exploitation by humans, it has been seen that the trees are being cut down mercilessly. This act of cleaning the green cover is known as deforestation.

Educate people:

The best way to handle the problem of deforestation is by making sure that we educate the masses regarding the importance of green cover. When people understand as to how deforestation is leading to grave consequences, they will get the incentive to plant trees rather than uproot them.

Protect the Environment:

As we have continued to exploit the environment in a way that it is hard to get things back to normal, it is now important to immediately start protecting the environment. A lot of natural calamities are occurring these days because the ecosystem balance has been disturbed. Deforestation alone is responsible for a major amount of problems.

So, you need to understand as to how you can come up with ways to excite people about planting more trees and doing their bit for the sake of the environment. Think of your children and grand children. If we continue with our aggressive deforestation campaigns, they are not likely to have a healthy environment for survival. Is that what we really want?

Deforestation can be defined as the removal of trees and clearing of forests for the personal and commercial benefits of human beings. Deforestation has emerged as one of the biggest man-made disasters recently. Every year, more and more trees and vegetation are being erased just to fulfill the various needs of the human race.

Deforestation happens for many reasons. The growing population is one of them. Rising human population needs more area for residential purpose. For this, forests are either burned down or cut to make space for constructing homes and apartments.

Deforestation is also done for commercial purposes. This includes setting up of factories, industries, and towers, etc. The enormous requirements of feeding the human race also create a burden on the land. As a result, clearing land for agricultural purposes leads to deforestation.

Deforestation impacts our earth in several ways. Trees are natural air purifiers. They absorb the carbon dioxide from the air and release oxygen into the atmosphere. Deforestation results in uncontrolled air pollution. When there are fewer trees, there is lesser absorption of carbon dioxide and other pollutants.

Deforestation also disturbs the water cycle. Forests absorb the groundwater and release the water vapors to form clouds, which in turn cause rains. Roots of trees hold the soil intact and prevent floods. But when there are no trees, different kinds of natural calamities are bound to happen.

With deforestation, chances of floods, drought, global warming, and disturbed weather cycle all come into the play. Not only that, the disappearance of forests means the extinction of wild animals and plants, which are highly important parts of our ecosystem.

In order to curb these disasters, we must plant more trees. Restoration of existing vegetation is equally essential. Population control is another indirect method to save trees and forest areas.

Deforestation is the process of cutting down of trees and forests completely or partially for different reasons like manufacturing different products with various parts of the tree as raw material, to build structures and other buildings, etc. Deforestation in recent days has become the curse of our world that resulted in the destruction of nature and the environment.

Cause and Drawbacks:

Deforestation is mainly done for making better living assets for humans and this one side thought is the biggest drawback of this issue. Instead of doing only the cutting part humans should practice forestation along with deforestation. Whenever a tree or a forest is cut, another one should be planted at the same place or on other lands to promote the forestation.

Deforestation is the main cause for many natural deficiencies and the destruction of many animal, plant and bird species. If the practice of cutting down trees continues, then eventually even the world may get destructed along with the extinction of the human race.

It’s not like trees shouldn’t be used for any kind of production and urbanization or industrialization shouldn’t be done for the development, but the main factor is to compensate for every minus done. Through this, there will be a balancing between the reduction and plantation which will help, to an extent, in the rectification of problems faced by the world due to deforestation.

Deforestation has also affected the atmospheric air combination. The carbon content in the atmosphere has considerably increased over years due to many human activities like uncontrolled fuel combustion.

Forest has played a massive function of inhaling the carbon dioxide from the atmosphere and exhaling oxygen during the daytime while they prepare food for themselves. This process is the reason for maintaining a balanced oxygen and carbon level in the atmosphere and that makes the life of us humans to breathe free.

Population growth is undeniably the major factor behind the increased deforestation level. The increased demand for more assets for better living has increased the need for deforestation as well. In such cases forestation should also be made as a follow-up process.

Controlling the overuse of assets can also help in reducing the deforestation rate. If humans start to use products that use a tree as raw material reasonably then it will help in avoiding deforestation as well. Deforestation not only is a life-threatening scenario for many animals and birds, but also the whole human species.

Deforestation refers to the elimination of plants and trees from a region. Deforestation also includes the clearing of jungles and plants from the region due to the numerous commercial motives.

Different Causes of Deforestation:

The below are the different causes of deforestation:

1. Overgrazing:

Overgrazing in jungles finishes recently renewed development. It makes the soil additional compact and invulnerable. The fertility of the soil also reduces owing to the devastation of organic substance. Overgrazing also results in the desertification and the soil erosion. Deforestation results in decreasing the overall soil’s productivity.

2. Shifting Cultivation:

Numerous agriculturalists destroy the jungle for farming and commercial motives and once productiveness of soil is shattered owing to recurrent harvesting, a fresh forest region is devastated. Hence, farmers must be recommended to utilize a similar area for agriculture and use some upgraded farming techniques and stop the deforestation.

3. Fuel Wood:

The maximum amount of forest is destroyed for the fuel wood. Around 86% of the fuel wood is utilized in rural regions in comparison to the 14% in urban parts and hence lead to more deforestation.

4. Forest Fires:

Recurrent fires in the forest regions are one of the major reasons of deforestation. Few incidents of fires are minor whereas the maximum of them are huge.

The industries related to the plywood and timber is mostly accountable for the deforestation. In fact, the huge demand for wooden things has resulted in the quick reduction of the forest.

6. Industry Establishment:

At times the industrial unit is constructed after deforestation. It means for a small achievement of few people, all other people have to bear a permanent loss. In this procedure, wild animals, valuable plant, and unusual birds get devastated. In fact, it adversely affects the quality of the environment.

7. Violation of Forest:

One more reason of deforestation is a violation by tribal on the land of forest for cultivation and other motives. Even though such type of land has a virtuous support for agriculture creation but still it creates environmental threats.

8. Forest Diseases:

Numerous diseases are instigated by rusts, parasitic fungi, nematodes and viruses that result in demise and deterioration of jungle. Fresh saplings are devastated owing to the occurrence of nematodes. Numerous diseases like blister rust, heart rot, and phloem necrosis, oak will, and Dutch elm, etc. destroy the jungle in large quantities.

9. Landslide:

The landslide lead to the deforestation in the mountains is a question of worry. It happened largely in the regions where growing actions are proceeding for the previous few years. The building of highways and railways mainly in hilly lands as well as the structure of large irrigation plans have resulted in enough deforestation and speeded the natural procedure of denudation.

Worldwide Solution for the Deforestation:

The jungle is an essential natural reserve for any nation and deforestation slow down a nation’s growth. To encounter the necessities of the growing population, simple resources might be attained only with the help of afforestation. It is actually the arrangement of implanting plants for food and food growth. Moreover, the nurseries have a significant part in increasing the coverage of the forest area.

Deforestation is the cutting down of trees. It is basically changing the use of land to a different purpose other than the planting of trees.

There are many reasons which have led to large levels of deforestation all over the world. One of the major causes is ever growing population of the world. With the growth in population, the need for more land to live has been rising. This has further led to cutting down of trees. Also, with modernisation, there has been a substantial increase in the requirement of land for setting up of industries. This has again contributed to deforestation.

Mining is another activity of humans which has led to large-scale deforestation in many areas. The need to build road and rail network in order to increase connectivity to the mines has led to cutting down of trees. This has altered the climatic conditions in these areas.

Deforestation has had a huge impact on the environment. Lack of trees has led to less release of water vapour in the air. This has, in turn, led to the alteration of rainfall patterns in different regions. India is a country which is dependent on monsoon rains for agriculture. Frequent droughts and floods caused due to deforestation have affected the lives of many in different parts of the country.

Moreover, trees absorb the carbon-dioxide from the air and help to purify it. Without trees around us, the presence of harmful gases in the air has been rising. This has also led to global warming which is again a major environmental concern. Also, the ever-rising pollution level, especially in many cities in India is due to vast deforestation only.

Additionally, trees bind the soil around them and prevent soil erosion. Deforestation has led to the soil being washed away with winds and rain, making the land unfit for agriculture. Also, trees and forests are the homes to different species of wildlife. With shrinking forests, several of the wildlife has become extinct as they were not able to cope with the changing conditions. Also, there have been increased man and wildlife conflicts in recent times as the animals are forced to venture in the cities in search of food. All these are severe effects of deforestation and need urgent attention by all.

The Perfect Example:

New Delhi is the capital of India. There was once a time when Delhi was a beautiful city. But with modernisation, increase in population, deforestation and mining in the nearby Aravalli hills, Delhi has been reduced to a gas chamber. Such is the impact the Delhi has become one of the most polluted cities in the world. What better example can be there to understand what deforestation has led us to?

There are many ways in which we can reduce deforestation. We must protect our forests. Moreover, we must mark adequate land for our farming needs. There are some laws already in place which prohibit people from unnecessary felling of trees. What needs to be done is the proper execution of the rules so that everyone abides by it. Also, stricter punishments need to be in place for violators so as to deter other people from disobeying the laws. Alternatively, people need to ensure that for every tree felled, equal numbers of trees are planted so that the balance of nature can be maintained. Summarily, it has to be a collective duty of all and just the governments alone, if we really need to reduce deforestation.

It is true that we all need space to live. With the ever-growing population and urbanisation, there has been more than ever need to cut trees and make space. However, we must realise that it is not possible for us to live without having trees around us. Trees bring so many benefits such as giving us oxygen, utilising the harmful carbon dioxide and so many products we need in our daily lives. Without trees around us, there would be no life on the earth. We should all do the needful to protect trees and reduce deforestation.

Deforestation is also known as clearing or clearance of trees. It can be said to mean removal of strands of trees or forests and the conversion of such area of land to a use that is totally non-forest in nature. Some deforestation examples are the converting of areas of forest to urban, ranches or farms use. The area of land that undergoes the most deforestation is the tropical rainforests. It is important to note that forests cover more than 31 percent in total land area of the surface of the earth.

There are a lot of different reasons why deforestation occurs: some tree are being cut down for building or as fuel (timber or coal), while areas of land are to be used as plantation and also as pasture to feed livestock. When trees are removed with properly replacing them, there can as a result be aridity, loss of biodiversity and even habitat damage. We have also had cases of deforestation used in times of war to starve the enemy.

Causes of Deforestation:

It has been discovered that the major and primary deforestation cause is agriculture. Studies have shown that about 48 percent of all deforestation is as a result of subsistence farming and 32 percent of deforestation is as a result of commercial agriculture. Also, it was discovered that logging accounts for about 14% of the total deforestation and 5% is from the removal for fuel wood.

There has been no form of agreement from experts on if industrial form of logging is a very important contributing factor to deforestation globally. Some experts have argued that the clearing of forests is something poor people do more as a result of them not having other alternatives. Other experts are of the belief that the poor seldom clear forests because they do not have the resources needed to do that. A study has also revealed that increase in population as a result of fertility rates that are very high are not a major driver of deforestation and they only influenced less than 8% of the cases of deforestation.

The Environmental Effects of Deforestation:

Deforestation has a lot of negative effects on our planet and environment.

A few of the areas where it negatively affects our environment are discussed below:

i. Atmospheric Effect:

Global warming has deforestation as one of its major contributing factors and deforestation is also a key cause of greenhouse effect. About 20% of all the emission of greenhouse gases is as a result of tropical deforestation. The land in an area that is deforested heats up quicker and it gets to a temperature that is higher than normal, causing a change in solar energy absorption, flow of water vapours and even wind flows and all of these affects the local climate of the area and also the global climate.

Also, the burning of plants in the forest in order to carry out clearing of land, incineration cause a huge amount of carbon dioxide release which is a major and important contributor to the global warming.

ii. Hydrological Effect:

Various researches have shown that deforestation greatly affects water cycle. Groundwater is extracted by trees through the help of their roots; the water extracted is then released into the surrounding atmosphere. If we remove a part of the forest, there will not be transpiration of water like it should be and this result in the climate being a lot drier. The water content of the soil is heavily reduced by deforestation and also atmospheric moisture as well as groundwater. There is a reduced level of water intake that the trees can extract as a result of the dry soil. Soil cohesion is also reduced by deforestation and this can result in landslides, flooding and erosion.

iii. Effect on Soil:

As a direct result of the plant litter on the surface, there is a minimal and reduced erosion rate in forests largely undisturbed. Deforestation increases the erosion rate as a result of the subsequent decrease in the quantity of cover of litter available. The litter cover actually serves as a protection for the soil from all varieties of surface runoff. When mechanized equipments and machineries are used in forestry operations, there can be a resulting erosion increase as a result of the development of roads in the forests.

iv. Effect on Biodiversity:

There is a biodiversity decline due to deforestation. Deforestation can lead to the death and extinction of a lot of species of animals and plants. The habitat of various animals are taken away as a result of deforestation.

The total coverage of forests on the earth’s landmass is 30 percent and the fact the people are destroying them is worrying. Research reveals that majority of the tropical forests on earth are being destroyed. We are almost at half the forest landmass in destruction. How would earth look life without forests? It will be a total disaster if deforestation is encouraged. Deforestation is a human act in which forests are permanently destroyed in order to create settlement area and use the trees for industries like paper manufacture, wood and construction. A lot of forests have been destroyed and the impact has been felt through climate change and extinction of animals due to destruction of the ecosystem. The impacts of deforestation are adverse and there is need to prevent and control it before it can get any worse.

Deforestation is mainly a human activity affected by many factors. Overpopulation contributed to deforestation because there is need to create a settlement area for the increasing number of people on earth and the need for urbanization for economic reasons. Recently, population has greatly risen in the world and people require shelter as a basic need. Forests are destroyed in order for people to find land to build a shelter and then trees are further cut to build those houses. Overpopulation is a major threat to the forest landmass and if not controlled, people will continue to occupy the forests until there is no more forest coverage on earth.

Another factor influencing deforestation is industrialization. Industries that use trees to manufacture their product e.g. paper and wood industries have caused major destruction of forests. The problem with industries is the large-scale need for trees which causes extensive deforestation. The use of timber in industries is a treat to forests all over the world. In as much as we need furniture, paper and homes, it is not worth the massive destruction of our forests.

Fires are also a cause of deforestation. During episodes of drought, fire spreads widely and burns down trees. The fire incidences could result from human activities like smoking or charcoal burning in the forests. Drought due to adverse weather changes in global warming is a natural disaster that claim the lives of people and living things.

Agricultural activities such as farming and livestock keeping also cause deforestation because of the land demand in those activities. Deforestation for farming purpose involves clearing all the vegetation on the required land and using it for and then burring the vegetation hence the name ‘slash and burn agriculture’. The ranches required for cattle keeping among other livestock require a large area that is clear from trees.

Impacts of Deforestation:

Deforestation has a great impact on the ecosystem in different ways. Climate change is influenced by deforestation because trees influence weather directly. Trees usually act to protect against strong winds and erosion but in its absence, natural disasters like floods and storms could be experienced. Also, tree are important in replenishing the air in the atmosphere. Trees have the ability to absorb carbon dioxide from the atmosphere and release oxygen. Without trees, the concentration of carbon dioxide in the atmosphere will be increased. Because carbon dioxide is a greenhouse gas, it causes global warming.

Global warming is a serious environmental issue that causes adverse climatic changes and affects life on earth. Extreme weather conditions like storms, drought and floods. These weather conditions are not conducive for humans and other living things on earth. Natural disasters as a result of global warming are very destructive both to animate and inanimate objects in the environment.

Loss of species due to deforestation has negatively affected biodiversity. Biodiversity is a highly valued aspect of life on earth and its interruption is a loss. There is a loss of habitat for species to exist in as a result of deforestation and therefore species face extinction. Extinction of some rare species is a threat we are currently facing. Animals that live and depend on forest vegetation for food will also suffer and eventually die of hunger. Survival has been forced on animals of the jungle due to deforestation and that is why human wildlife conflict is being experienced.

The water cycle on earth is negatively affected by deforestation. The existence of water vapor in the atmosphere is maintained by trees. Absence of trees cause a reduced vapor retention in the atmosphere which result in adverse climate changes. Trees and other forest vegetation are important in preventing water pollution because they prevent the contaminated runoff into water sources like rivers, lakes and oceans. Without trees, pollution of water is more frequent and therefore the water will be unsafe for consumption by human and animals.

Solutions to Deforestation:

Based on the serious impact of deforestation, it is only safe if solutions are sought to end this problem. The ultimate solution is definitely restoration of the forest landmass on earth. The restoration can be done by encouraging the planting of trees, a process called reforestation. Although reforestation will not completely solve the impacts of deforestation, it will restore a habitat for the wild animals and slowly restore the ecosystem. Major impacts like concentration of carbon dioxide in the atmosphere require another approach. Human activities that contribute to carbon dioxide gas emission to the atmosphere have to be reduced through strict policies for industries and finding alternative energy sources that do not produce greenhouse gases.

Another solution is public awareness. People have to be made aware that deforestation has negative effects so that they can reduce the act. Through awareness, people can also be taught on ways of reducing the population e.g., family planning. On World Environment Day, people are encouraged to participate in activities like tree planting in order to conserve environment and that is how the awareness takes place.

In conclusion, deforestation is a human activity that is destructive and should be discouraged. Environmental conservation is our responsibility because we have only one earth to live in.

Deforestation , Environment , Forests

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Overpopulation: Cause and Effect

Conversations about overpopulation can quickly become controversial because they beg the question: Who exactly is the cause of the problem and what, if anything, should be done about it? Many population experts worry discussions around overpopulation will be abused by small-minded people to suggest some are the “right people” to be on the planet (like themselves), and some people are “the wrong people” (usually people in poverty, people of color, foreigners, and so on—you get the drift). But there are no “right” or “wrong” people on the planet, and discussing the problems of global overpopulation can never be an excuse, or in any way provide a platform, for having that type of conversation.

Each human being has a legitimate claim on a sufficient and fair amount of Earth’s resources. But with a population approaching 8 billion, even if everyone adopted a relatively low material standard of living like the one currently found in Papua New Guinea , it would still push Earth to its ecological breaking point. Unfortunately, the “average person” on Earth consumes at a rate over 50% above a sustainable level. Incredibly, the average person in the United States uses almost five times more than the sustainable yield of the planet.

When we use the term “overpopulation,” we specifically mean a situation in which the Earth cannot regenerate the resources used by the world’s population each year. Experts say this has been the case every year since 1970, with each successive year becoming more and more damaging. To help temper this wildly unsustainable situation, we need to understand what’s contributing to overpopulation and overconsumption and how these trends are affecting everything from climate change to sociopolitical unrest.

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The causes of overpopulation.

Today the Earth is home to more than 7.8 billion people . By 2100 the population is on track to hit 10.8 billion , according to the United Nations — and that’s assuming steady fertility declines in many countries. Interestingly, if extra progress is made in women’s reproductive self-determination, and fertility falls more than the United Nations assumes is likely, the population in 2100 might be a relatively smaller 7.3 billion.

For now, the world’s population is still increasing in huge annual increments (about 80 million per year), and our supply of vital non-renewable resources are being exhausted. Many factors contribute to these unsustainable trends , including falling mortality rates, underutilized contraception, and a lack of education for girls.

Falling Mortality Rate

The primary (and perhaps most obvious) cause of population growth is an imbalance between births and deaths. The infant mortality rate has decreased globally, with 4.1 million infant deaths in 2017 compared to 8.8 million in 1990, according to the World Health Organization (WHO). This is welcome public health news, of course.

At the same time, lifespans are increasing around the world. Those of us who are alive today will likely live much longer than most of our ancestors. Global average life expectancy has more than doubled since 1900 , thanks to advancements in medicine, technology, and general hygiene. Falling mortality rates are certainly nothing to complain about either, but widespread longevity does contribute to the mathematics of increasing population numbers.

Underutilized Contraception 

The global fertility rate has fallen steadily over the years, down from an average of 5 children per woman in 1950 to 2.4 children per woman today, according to the UN Population Division . Along with that promising trend, contraceptive use has slowly but steadily increased globally, rising from 54% in 1990 to 57.4% in 2015. Yet, on the whole, contraceptive use is still underutilized. For example, according to the WHO, an estimated 214 million women in developing countries who want to avoid pregnancy are not using modern contraceptives.

These women aren’t using contraceptives for a variety of reasons, including social norms or religious beliefs that discourage birth control, misconceptions about adverse side effects, and a lack of agency for women to make decisions around sex and family planning. An estimated 44% of pregnancies were unintended worldwide between 2010-2014. Getting more women the access and agency to utilize family planning methods could go a long way in flattening the population curve.

Lack of Female Education    

Although female access to education has increased over the years, the gender gap remains. Roughly 130 million girls worldwide are out of school currently, and an estimated 15 million girls of primary school age will never   learn to read and write, compared with 10 million boys.

Increasing and encouraging education among women and girls can have a number of positive ripple effects, including delayed childbearing , healthier children, and an increase in workforce participation. Plenty of evidence suggests a negative correlation between female education and fertility rates.

If increased female education can delay or decrease fertility and provide girls with opportunities beyond an early marriage, it could also help to mitigate current population trends. 

The Effects of Overpopulation

It is only logical that an increase in the world’s population will cause additional strains on resources. More people means an increased demand for food, water, housing, energy, healthcare, transportation, and more. And all that consumption contributes to ecological degradation, increased conflicts, and a higher risk of large-scale disasters like pandemics.  

Ecological Degradation 

An increase in population will inevitably create pressures leading to more deforestation, decreased biodiversity, and spikes in pollution and emissions, which will exacerbate climate change . Ultimately, unless we take action to help minimize further population growth heading into the remainder of this century, many scientists believe the additional stress on the planet will lead to ecological disruption and collapse so severe it threatens the viability of life on Earth as we know it. 

Each spike in the global population has a measurable impact on the planet’s health. According to estimates in a study by Wynes and Nicholas (2017) , a family having one fewer child could reduce emissions by 58.6 tonnes CO2-equivalent per year in developed countries.

Increased Conflicts 

The scarcity brought about by environmental disruption and overpopulation has the potential to trigger an increase in violence and political unrest. We’re already seeing wars fought over water, land, and energy resources in the Middle East and other regions, and the turmoil is likely to increase as the global population grows even larger.

Higher Risk of Disasters and Pandemics 

Many of the recent novel pathogens that have devastated humans around the world, including COVID-19, Zika virus, Ebola, and West Nile virus, originated in animals or insects before passing to humans. Part of the reason the world is entering “ a period of increased outbreak activity ” is because humans are destroying wildlife habitats and coming into contact with wild animals on a more regular basis. Now that we’re in the midst of a pandemic, it has become clear how difficult it is to social distance in a world occupied by nearly 8 billion people.   

Discover the real causes and effects of overpopulation

What can be done about overpopulation.

When addressing overpopulation, it’s crucial to take an approach of providing empowerment while mobilizing against anybody advocating for the use of coercion or violence to solve our problems. The combined efforts of spreading knowledge about family planning, increasing agency among women , and debunking widely held myths about contraception will measurably change the trajectory of the world’s population.

As we carry out our work at Population Media Center (PMC), we see first-hand that spreading awareness about family planning methods and the ecological and economic benefits of having smaller families can change reproductive behavior. For example, listeners of our Burundian radio show Agashi (“Hey! Look Again!”) were 1.7 times more likely than non-listeners to confirm that they were willing to negotiate condom use with a sexual partner and 1.8 times more likely than non-listeners to say that they generally approve of family planning for limiting the number of children.

At PMC we harness the power of storytelling to empower listeners to live healthier and more prosperous lives, which in turn contributes to stabilizing the global population so that people can live sustainably with the world’s renewable resources. Discover how PMC is taking action against overpopulation today!

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Overpopulation: Causes, Effects, and Solutions Essay

Introduction, causes of overpopulation, effects of overpopulation, solutions to overpopulation, works cited.

The concept of overpopulation of the planet is not new. There is a finite amount of space and resources that the planet can offer, and technological advances can only mitigate the situation so much. The first scholar to consider the idea of overpopulation was Thomas Malthusian, who brought it up in a work called “An Essay on the Principle of Population.” He managed to outline the reasons for population growth such as the improvement of standards of living, an abundance of food, and advanced medicine (Barbier 4).

When Malthusian made his predictions, however, he did not consider technological progress. The apocalypse he predicted was averted through innovations in technology and agriculture. Today, in 2016, humanity faces the problem of overpopulation once more. Despite many who dismiss the threat of overpopulation, it is much more real now than it was in 1796, as natural resources are now much fewer than they used to be and the population – much larger.

Although different scholars point to different factors that influence population growth, the core ones remain the same. These factors include the following:

• Advances in food production and agriculture;
• Advances in industry and production;
• Advances in medicine; and
• Poor family planning (Barbier 92).

It is obvious that these four factors are the ones that affect population growth the most. Advances in food production and agriculture create a surplus of food, which allows for population growth without famine as a natural barrier to curb it. Advances in industry and production provide clothes and items for the growing population to use, thus creating and maintaining a higher standard of living. Modern medicine curbs child mortality and effectively prolongs peoples’ lives.

Lastly, poor family planning means families become large and produce many children, with no regard for how it affects the environment. Together, these factors have contributed greatly to the incredible population growth rates today.

Many scholars have identified the disastrous effects overpopulation has on the environment. There are main three points of concern to which overpopulation will inevitably lead:

• Depletion of natural resources;
• Degradation of the environment; and
• Resource wars (Barbier 75).

With consumer culture on the rise, the population requires increasingly more materials to maintain their high standards of living. Everybody wants to have an iPhone, and everybody feels the need to have a personal vehicle. While certain resources, such as wood and energy, are renewable, the rest are not. Eventually, Earth will face a resource crisis, which is only sped up by the ever-increasing population (Toth and Szigeti 284).

More people mean a quicker degradation of the environment. Humanity, in general, has a negative influence on nature. Therefore, the more humans there are, the worse the impact is. This fact is especially true for developing countries, where advances in medicine and agriculture promote population growth, but eco-technologies and recycling are not yet implemented (Cafaro and Crist 75).

As natural resources become more and more depleted, resource wars will follow. Covert resource wars are already being waged, as major powers confront one another over the oil basins located in the Middle East. This competition will become even fiercer in the future as non-renewable resources become less and less common.

There are two popular paths to take when trying to solve the overpopulation problem. The first deals with the roots of overpopulation itself and are aimed at lowering the number of births through state programs, family planning, sex education, and other such initiatives. Such a strategy is already implemented in China, where the government imposes severe financial penalties for having more than one child. The country was forced to face the overpopulation problem earlier than most due to the unprecedented population growth it experienced in the decades prior.

The second route is not aimed at lowering the population but rather at providing for them. This approach involves recycling, using renewable energy, developing eco-clean technologies, and implementing other ideas that slow down and reduce the damage caused by the excess population. Looking for materials and resources outside the planet is futuristic, but it represents a viable strategy nonetheless. Eventually, humanity will have to look for resources in space, as it is impossible to create a completely self-sustaining resource model – some resources will inevitably be lost in the recycling process.

Combining both of these paths into one all-consuming strategy seems like the most reasonable and effective approach to mitigating the problem of overpopulation. Introducing statewide policies on birth control – in addition to popularizing recycling, using renewable energy, and minimizing the damage to the environment – would severely reduce the dangers presented by overpopulation and would buy humanity more time to find a permanent solution (Barbier 184).

As it stands, the effort to combat overpopulation is in its infancy. Outside of a couple of concerned governments who have to deal with overpopulation at home, nobody seems to give the issue the proper attention it deserves. If humanity is to overcome this problem, a united stance and a complex approach are required. This effort would require cooperation between different nations on all levels, as well as a vast informative campaign to make sure the general populace understands the need for such initiatives. Without such a joint effort, any local attempt to deal with the situation at home would have a limited effect.

Barbier, Edward. Economics, Natural-Resource Scarcity and Development, New York: Routledge, 2013. Print.

Cafaro, Phillip, and Eileen Crist. Life on the Brink, Environmentalists Confront Overpopulation, London: The University of Georgia Press, 2012. Print.

Toth, Gergery, and Cecilia Szigeti. “The Historical Ecological Footprint: From Over-Population to Over-Consumption.” Ecological Indicators 60 (2016): 283-291. Print.

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IvyPanda. (2023, October 30). Overpopulation: Causes, Effects, and Solutions. https://ivypanda.com/essays/overpopulation-combating-analysis/

"Overpopulation: Causes, Effects, and Solutions." IvyPanda , 30 Oct. 2023, ivypanda.com/essays/overpopulation-combating-analysis/.

IvyPanda . (2023) 'Overpopulation: Causes, Effects, and Solutions'. 30 October.

IvyPanda . 2023. "Overpopulation: Causes, Effects, and Solutions." October 30, 2023. https://ivypanda.com/essays/overpopulation-combating-analysis/.

1. IvyPanda . "Overpopulation: Causes, Effects, and Solutions." October 30, 2023. https://ivypanda.com/essays/overpopulation-combating-analysis/.

Bibliography

IvyPanda . "Overpopulation: Causes, Effects, and Solutions." October 30, 2023. https://ivypanda.com/essays/overpopulation-combating-analysis/.

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• The Impact of Overpopulation on the Global Environment
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Essay on Deforestation for Students and Children

500+ words essay on deforestation.

Deforestation is the cutting down of trees in the forest in a large number. Deforestation has always been a threat to our environment. But still many humans are continuing this ill practice. Moreover, Deforestation is causing ecological imbalance. Yet, some selfish people have to fill their pockets. Therefore they do not even think about it once. So, the government is trying countermeasures to avert the harm to the environment .

The main purpose of deforestation is to increase the land area. Also, this land area is to set up new industries. And, this all is because of the increase in population. As the population increases the demand for products also increase. So rich businessmen set up these industries to increase profit.

Harmful Effects of Deforestation

There are many harmful effects of deforestation. Some of them are below: Soil erosion: Soil erosion is the elimination of the upper layer of the soil. It takes place when there is removing of trees that bind the soil. As a result wind and water carries away the top layer of the soil.

Moreover, disasters like landslides take place because of this. Furthermore, soil erosion is responsible for various floods. As trees are not present to stop the waters from heavy rainfall’s gush directly to the plains. This results in damaging of colonies where people are living.

Global Warming: Global warming is the main cause of the change in our environment. These seasons are now getting delayed. Moreover, there is an imbalance in their ratios. The temperatures are reaching its extreme points. This year it was 50 degrees in the plains, which is most of all. Furthermore, the glaciers in the Himalayan ranges are melting.

As a result, floods are affecting the hilly regions of our country and the people living there. Moreover, the ratio of water suitable for drinking is also decreasing.

Impact on the water cycle: Since through transpiration, trees release soil water into the environment. Thus cutting of them is decreasing the rate of water in the atmosphere. So clouds are not getting formed. As a result, the agricultural grounds are not receiving proper rainfall. Therefore it is indirectly affecting humans only.

A great threat to wildlife: Deforestation is affecting wildlife as well. Many animals like Dodo, Sabre-toothed Cat, Tasmanian Tiger are already extinct. Furthermore, some animals are on the verge of extinction. That’s because they have lost habitat or their place of living. This is one of the major issues for wildlife protectors.

Get the huge list of more than 500 Essay Topics and Ideas

How to Avert Deforestation?

Deforestation can be averted by various countermeasures. First of all, we should afforestation which is growing of trees in the forest. This would help to resolve the loss of the trees cut down. Moreover, the use of plant-based products should increase.

This would force different industries to grow more trees. As a result, the environment will also get benefit from it. Furthermore, people should grow small plants in their houses. That will help the environment to regain its ability. At last, the government should take strict actions against people. Especially those who are illegally cutting down trees.

FAQs on Essay on Deforestation

Q1. Why is deforestation harmful to our environment?

A1. Deforestation is harmful to our environment because it is creating different problems. These problems are soil erosion, global warming. Moreover, it is also causing different disasters like floods and landslides.

Q2. How are animals affected by deforestation?

A2. Deforestation affects animals as they have lost their habitat. Moreover, herbivores animals get their food from plants and trees. As a result, they are not getting proper food to eat, which in turn is resulting in their extinction

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Biden Administration Restores Wildlife Protections Weakened Under Trump

The rules give federal officials more leeway to protect species in a changing climate. Industry groups are expected to sue.

By Catrin Einhorn

After three years of planning and navigating the slow bureaucracy of federal rule-making, the Biden administration is restoring a series of protections for imperiled animals and plants that had been loosened under President Donald J. Trump.

The rules, proposed last year and now finalized, give federal officials more leeway to protect species in a changing climate; bring back protections for animals that are classified as “threatened” with extinction, which is one step short of “endangered”; and clarify that decisions about whether to list a species must be made without considering economic factors.

They come as countries around the world grapple with a biodiversity crisis that has taken hold as humans have transformed the planet .

“As species face new and daunting challenges, including climate change, degraded and fragmented habitat, invasive species, and wildlife disease, the Endangered Species Act is more important than ever to conserve and recover imperiled species now and for generations to come,” said Martha Williams, director of the U.S. Fish and Wildlife Service, which issued the finalized rules along with the National Oceanic and Atmospheric Administration’s fisheries service. “These revisions underscore our commitment to using all of the tools available to help halt declines and stabilize populations of the species most at-risk.”

Republicans and industry groups had assailed the initial proposal and are expected to do the same with the finalized version. Representative Bruce Westerman, an Arkansas Republican who leads the Natural Resources Committee, accused the Biden administration on Thursday of “undoing crucial reforms and issuing new regulations that will not benefit listed species.”

The rules are expected to set off a new round of lawsuits.

“The imposed Endangered Species Act restrictions are especially harmful to those, such as our farmer/rancher members, who depend on being able to produce their livelihoods through access to and use of natural resources,” the Nevada Farm Bureau Federation wrote in a comment to the proposed changes. Others that have spoken out against them include the oil and gas industry, foresters and states that want more control over managing wildlife.

Conor Bernstein, vice president of communications at the National Mining Association, said that while his group supports the conservation goals of the Endangered Species Act, the law imposes unnecessary restrictions on development and creates regulatory uncertainty.

Environmental groups, on the other hand, have been eagerly awaiting the reversal of the Trump-era rules, but many criticized the Biden administration for leaving some provisions in place.

“This administration is restoring some really important rules for endangered species,” said Mike Leahy, a senior director at the National Wildlife Federation. “But given all the threats they face, we would have liked to see them restore more protections, so their critical habitats can’t be picked apart piece by piece, or past harms to these species can’t be ignored.”

Mr. Leahy said rules protecting threatened and endangered species are especially important because Congress is not providing the funding that federal, state and tribal biologists need to recover them.

The Endangered Species Act, which turned 50 last year, is both lauded and loathed. Those who prioritize environmental health and the protection of America’s wildlife see it as a landmark law that has saved untold species from extinction. Others criticize it for curtailing economic activity and stomping on the rights of states and individuals.

During the Trump administration, officials weakened the law , undoing protections for animals categorized as threatened and allowing regulators to conduct economic assessments when deciding whether a species warrants protection. Environmental groups had argued those assessments had no place in such decisions.

The Biden administration had previously reversed a Trump-era change related to the definition of habitat for endangered animals.

During the public comment period for the new rules, officials received about 468,000 comments from a wide range of groups including those representing various industries, environmental advocates, states and tribes.

Some comments came from individuals, like Carol Ellis of Spokane, Wash., who wrote in support of strengthening the law. “We humans are creating the 6th extinction!” she wrote. “Get with the science.”

Lisa Friedman contributed reporting.

Catrin Einhorn covers biodiversity, climate and the environment for The Times. More about Catrin Einhorn

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Decades of buried trash in landfills is releasing methane , a powerful greenhouse gas, at higher rates than previously estimated, a study says.

Ocean Conservation Namibia is disentangling a record number of seals, while broadcasting the perils of marine debris in a largely feel-good way. Here’s how .

To decarbonize the electrical grid, companies are finding creative ways to store energy during periods of low demand in carbon dioxide storage balloons .

New satellite-based research reveals how land along the East Coast is slumping into the ocean, compounding the danger from global sea level rise . A major culprit: overpumping of groundwater.

Did you know the ♻ symbol doesn’t mean something is actually recyclable ? Read on about how we got here, and what can be done.

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