Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.     

Mechanized Logging, Market Hunting, and a Bank Loan in Congo

Financing for logging of tropical moist forests in the Republic of Congo is commonly sought in the form of loans from multilateral development banks. Pressure from nongovernmental conservation organizations and from within the banks themselves has resulted in their beginning to assess the environmental consequences of such loans. We conducted one of the first such assessments of an African Development Bank loan to a logging company. Geographic isolation, resulting transportation costs, and market demands have forced commercial loggers within the Sangha region of Congo to exploit only the most valuable timber. This form of timber extraction destroys an average of 6.8% of the canopy and thus, unlike clear cutting, was expected to have a minimal impact on wildlife populations. Line transect counts showed, however, that primate abundance was exceedingly low in logged forest. We believe this is not a direct consequence of canopy reduction, but results from the extremely intensive market hunting that coincides with timber surveying and extraction. Weapons and hunting camps were common, and logging company vehicles transported primates, duikers and other game daily. Wildlife laws of Congo are openly violated and they are not enforced. While market hunting is clearly facilitated and intensified by the presence of logging concessions, it is the Congo's highly urbanized population that provides the ever growing demand for meat, a demand not being met through animal husbandry. Thus, although selective logging in the absence of hunting may have only limited adverse effects on wildlife, when the two are combined the consequences are grave for the Sangha region's wildlife. Loans to logging companies from the African Development Bank should incorporate conditions for ensuring wildlife conservation.     

Molecular Systematics, Ethics, and Biological Decision Making under Uncertainty

Abstract: The controversy among Karl and Bowen (1999) , Pritchard (1999) , and Grady and Quattro (1999) over scientific uncertainties and the ethical and political consequences of the black turtle's taxonomic status is caused by incomplete and uncertain scientific knowledge. When faced with cases of uncertainty, conservation biologists need to use ethical rationality, not merely scientific rationality. They should follow three general ethical principles: (1) perform and present unbiased research, (2) promote use of unbiased research by others, and (3) protect human and environmental welfare. Adhering to these principles is difficult because they can conflict, are too general to provide specific guidance in a particular situation, and are not ranked according to which ought to take priority in different situations. One way to deal with these difficulties is to employ a two-stage ethical analysis. This analysis develops general principles (first stage) and then investigates the consequences of adopting each of the principles (second stage). A two-stage ethical analysis applied to the controversy over the black turtle's taxonomic status suggests that even if there are some grounds for expanding conservation biologists' responsibilities to human and environmental welfare, they are not ethically justified in using any means whatsoever to achieve desirable consequences when the public has rights to full information. Conservation biologists do not appear to have grounds for paternalism in this case because it involves value judgments, not merely professional expertise.     

Characterizing Spatial Uncertainty when Integrating Social Data in Conservation Planning

Recent conservation planning studies have presented approaches for integrating spatially referenced social (SRS) data with a view to improving the feasibility of conservation action. We reviewed the growing conservation literature on SRS data, focusing on elicited or stated preferences derived through social survey methods such as choice experiments and public participation geographic information systems. Elicited SRS data includes the spatial distribution of willingness to sell, willingness to pay, willingness to act, and assessments of social and cultural values. We developed a typology for assessing elicited SRS data uncertainty which describes how social survey uncertainty propagates when projected spatially and the importance of accounting for spatial uncertainty such as scale effects and data quality. These uncertainties will propagate when elicited SRS data is integrated with biophysical data for conservation planning and may have important consequences for assessing the feasibility of conservation actions. To explore this issue further, we conducted a systematic review of the elicited SRS data literature. We found that social survey uncertainty was commonly tested for, but that these uncertainties were ignored when projected spatially. Based on these results we developed a framework which will help researchers and practitioners estimate social survey uncertainty and use these quantitative estimates to systematically address uncertainty within an analysis. This is important when using SRS data in conservation applications because decisions need to be made irrespective of data quality and well characterized uncertainty can be incorporated into decision theoretic approaches.     

The Links between Protected Areas, Faiths, and Sacred Natural Sites

Most people follow and are influenced by some kind of spiritual faith. We examined two ways in which religious faiths can in turn influence biodiversity conservation in protected areas. First, biodiversity conservation is influenced through the direct and often effective protection afforded to wild species in sacred natural sites and in seminatural habitats around religious buildings. Sacred natural sites are almost certainly the world's oldest form of habitat protection. Although some sacred natural sites exist inside official protected areas, many thousands more form a largely unrecognized "shadow" conservation network in many countries throughout the world, which can be more stringently protected than state-run reserves. Second, faiths have a profound impact on attitudes to protection of the natural world through their philosophy, teachings, investment choices, approaches to land they control, and religious-based management systems. We considered the interactions between faiths and protected areas with respect to all 11 mainstream faiths and to a number of local belief systems. The close links between faiths and habitat protection offer major conservation opportunities, but also pose challenges. Bringing a sacred natural site into a national protected-area system can increase protection for the site, but may compromise some of its spiritual values or even its conservation values. Most protected-area managers are not trained to manage natural sites for religious purposes, but many sacred natural sites are under threat from cultural changes and habitat degradation. Decisions about whether or not to make a sacred natural site an "official" protected area therefore need to be made on a case-by-case basis. Such sites can play an important role in conservation inside and outside official protected areas. More information about the conservation value of sacred lands is needed as is more informed experience in integrating these into wider conservation strategies. In addition, many protected-area staff need training in how to manage sensitive issues relating to faiths where important faith sites occur in protected areas.     

Contribution of the Natura 2000 Network to Biodiversity Conservation in Italy

Abstract:  The Natura 2000 network is the most important conservation effort being implemented in Europe. Nevertheless, no comprehensive and systematic region—or nationwide evaluation of the effectiveness of the network has been conducted. We used habitat suitability models and extent of occurrence of 468 species of vertebrates to evaluate the contribution of the Natura 2000 network to biodiversity conservation in Italy. We also estimated the population size of 101 species inside the Natura 2000 network to assess its capacity to maintain or improve the population status of listed species. In general the Italian Natura 2000 did not seem to integrate existing protected areas well. The Natura 2000 network increased from 11% to 20% the area devoted to conservation in Italy and the coverage provided to areas with high biodiversity. Nevertheless, some areas with high numbers of species were devoid of conservation areas, and more than 50% of the highly irreplaceable areas were not considered in the system. Moreover, the Natura 2000 network cannot maintain 44–80% (depending on the taxa considered) of the species in a "favorable conservation status" under World Conservation Union Red List criteria. The Natura 2000 network is probably stronger than the results of our analyses suggest. The system is based on a site-specific expert-based strategy and is driven by direct and detailed knowledge of local diversity. Nevertheless, if Natura 2000 is taken to represent the final point of all the EU conservation policies, it will inevitably fail. Its role in conservation could be enhanced by integrating the Natura 2000 system into a more general strategy that considers natural processes and the ecological and evolutionary mechanisms underlying these processes.     

Stochastic Pollution, Permits, and Merger Incentives

Pollution permit regulations introduce nonlinearities into the objective function of a polluting firm. We develop a microeconomic model to show the effects these nonlinearities might have upon firm decisions when emissions are stochastic. Under perfect competition the fraction of planned pollution covered by permits is shown to be separable from planned production. We also demonstrate that permit management incentives may motivate a merger of otherwise independent firms. Incentives to petition for “bubble” coverage are also considered. The model is studied under risk neutrality and risk aversion. Imperfectly competitive situations in the output and permit markets are also analyzed.     

Multiscale Factors Affecting Human Attitudes toward Snow Leopards and Wolves

The threat posed by large carnivores to livestock and humans makes peaceful coexistence between them difficult. Effective implementation of conservation laws and policies depends on the attitudes of local residents toward the target species. There are many known correlates of human attitudes toward carnivores, but they have only been assessed at the scale of the individual. Because human societies are organized hierarchically, attitudes are presumably influenced by different factors at different scales of social organization, but this scale dependence has not been examined. We used structured interview surveys to quantitatively assess the attitudes of a Buddhist pastoral community toward snow leopards (Panthera uncia) and wolves (Canis lupus). We interviewed 381 individuals from 24 villages within 6 study sites across the high‐elevation Spiti Valley in the Indian Trans‐Himalaya. We gathered information on key explanatory variables that together captured variation in individual and village‐level socioeconomic factors. We used hierarchical linear models to examine how the effect of these factors on human attitudes changed with the scale of analysis from the individual to the community. Factors significant at the individual level were gender, education, and age of the respondent (for wolves and snow leopards), number of income sources in the family (wolves), agricultural production, and large‐bodied livestock holdings (snow leopards). At the community level, the significant factors included the number of smaller‐bodied herded livestock killed by wolves and mean agricultural production (wolves) and village size and large livestock holdings (snow leopards). Our results show that scaling up from the individual to higher levels of social organization can highlight important factors that influence attitudes of people toward wildlife and toward formal conservation efforts in general. Such scale‐specific information can help managers apply conservation measures at appropriate scales. Our results reiterate the need for conflict management programs to be multipronged. Factores Multi‐Escala que Afectan las Actitudes Humanas hacia Leopardos de las Nieves y Lobos     

A Behaviorally Explicit Demographic Model Integrating Habitat Selection and Population Dynamics in California Sea Lions

Abstract: Although there has been a call for the integration of behavioral ecology and conservation biology, there are few tools currently available to achieve this integration. Explicitly including information about behavioral strategies in population viability analyses may enhance the ability of conservation biologists to understand and estimate patterns of extinction risk. Nevertheless, most behavioral‐based PVA approaches require detailed individual‐based data that are rarely available for imperiled species. We present a mechanistic approach that incorporates spatial and demographic consequences of behavioral strategies into population models used for conservation. We developed a stage‐structured matrix model that includes the costs and benefits of movement associated with 2 habitat‐selection strategies (philopatry and direct assessment). Using a life table for California sea lions (Zalophus californianus), we explored the sensitivity of model predictions to the inclusion of these behavioral parameters. Including behavioral information dramatically changed predicted population sizes, model dynamics, and the expected distribution of individuals among sites. Estimated population sizes projected in 100 years diverged up to 1 order of magnitude among scenarios that assumed different movement behavior. Scenarios also exhibited different model dynamics that ranged from stable equilibria to cycles or extinction. These results suggest that inclusion of behavioral data in viability models may improve estimates of extinction risk for imperiled species. Our approach provides a simple method for incorporating spatial and demographic consequences of behavioral strategies into population models and may be easily extended to other species and behaviors to understand the mechanisms of population dynamics for imperiled populations.     

Valuing nature in a general equilibrium

We explore the consequences of modeling the demand for environmental quality improvements as a fully integrated part of a general equilibrium demand system in an applied general equilibrium (or CGE) analysis. Demand for non-market goods depends on a full range of relative prices as well as environmental outcomes. We simulate the effects of reducing two air pollutants to improve human health and three ecosystem services provided to households. The ecosystem services make non-separable contributions to household utility. We find that willingness to pay measures of use-based ecosystem services are impacted by changes in demand for complementary market goods. Demand for these goods shifts due to pollution reductions that enhance ecosystem services. Partial equilibrium estimates of these use values can be measured with substantial error if they fail to account for the general equilibrium adjustments caused by pollution. Over 300 calibrations of the model identify the model features important to these errors. We find that effects on ecosystem services associated with non-use values have important implications for the feedback effects on use related measures of economic tradeoffs. This is due to how our model integrates market and non-market effects, reflecting the non-market services importance to general equilibrium market outcomes.     

Improving effectiveness of systematic conservation planning with density data

Systematic conservation planning aims to design networks of protected areas that meet conservation goals across large landscapes. The optimal design of these conservation networks is most frequently based on the modeled habitat suitability or probability of occurrence of species, despite evidence that model predictions may not be highly correlated with species density. We hypothesized that conservation networks designed using species density distributions more efficiently conserve populations of all species considered than networks designed using probability of occurrence models. To test this hypothesis, we used the Zonation conservation prioritization algorithm to evaluate conservation network designs based on probability of occurrence versus density models for 26 land bird species in the U.S. Pacific Northwest. We assessed the efficacy of each conservation network based on predicted species densities and predicted species diversity. High‐density model Zonation rankings protected more individuals per species when networks protected the highest priority 10‐40% of the landscape. Compared with density‐based models, the occurrence‐based models protected more individuals in the lowest 50% priority areas of the landscape. The 2 approaches conserved species diversity in similar ways: predicted diversity was higher in higher priority locations in both conservation networks. We conclude that both density and probability of occurrence models can be useful for setting conservation priorities but that density‐based models are best suited for identifying the highest priority areas. Developing methods to aggregate species count data from unrelated monitoring efforts and making these data widely available through ecoinformatics portals such as the Avian Knowledge Network will enable species count data to be more widely incorporated into systematic conservation planning efforts.     

A 2.5‐million‐year perspective on coarse‐filter strategies for conserving nature's stage

Climate change will require novel conservation strategies. One such tactic is a coarse‐filter approach that focuses on conserving nature's stage (CNS) rather than the actors (individual species). However, there is a temporal mismatch between the long‐term goals of conservation and the short‐term nature of most ecological studies, which leaves many assumptions untested. Paleoecology provides a valuable perspective on coarse‐filter strategies by marshaling the natural experiments of the past to contextualize extinction risk due to the emerging impacts of climate change and anthropogenic threats. We reviewed examples from the paleoecological record that highlight the strengths, opportunities, and caveats of a CNS approach. We focused on the near‐time geological past of the Quaternary, during which species were subjected to widespread changes in climate and concomitant changes in the physical environment in general. Species experienced a range of individualistic responses to these changes, including community turnover and novel associations, extinction and speciation, range shifts, changes in local richness and evenness, and both equilibrium and disequilibrium responses. Due to the dynamic nature of species responses to Quaternary climate change, a coarse‐filter strategy may be appropriate for many taxa because it can accommodate dynamic processes. However, conservationists should also consider that the persistence of landforms varies across space and time, which could have potential long‐term consequences for geodiversity and thus biodiversity.     

Financial Mechanisms for Conservation in Brazil

Abstract:  I reviewed some of the financial mechanisms for biodiversity conservation activities in Brazil. There is a heavy dependence on the public sector, but macroeconomic policies aimed at reducing government spending have resulted in reduced budgets dedicated to public conservation measures. The financial constraints for environmental protection have also increased because of a reduction in foreign aid. Positive signs for the immediate future, however, come from new initiatives that create economic instruments to finance conservation. The most important initiatives include conservation criteria for tax redistribution; environmental compensation; water charges; royalties for electricity, petroleum, and natural gas; tradable obligations for forest reserves; and voluntary measures on the part of the business sector. Resources created from these initiatives have different origins and are managed by different public agencies according to varying laws and policies, so their efficient implementation will require that the institutions involved in biodiversity conservation in Brazil establish a minimum set of common priorities and objectives.     

Local Population Dynamics in Metapopulation Models: Implications for Conservation

Abstract: Habitat fragmentation and the division of populations into spatially separated units have led to the increasing use of metapopulation models to characterize these populations. One prominent model that has served as a heuristic tool was introduced by Levins and is based on a collection of simplifying assumptions that exclude information on the dynamics and spatial distribution of local populations. Levins's and similar models predict the proportion of occupied habitat patches at equilibrium and the conditions needed to avoid total extinction. There are many obvious concerns about using such models, including how realistic alterations might change the predictions and whether occupancy has any relationship to population-level processes. Although many of the assumptions of these simple models are known to be unrealistic, we do not know how the assumptions affect model predictions. We simulated a metapopulation, and our results show that assumptions such as homogeneity of habitat patches, random migration among patches, equivalent extinction probabilities in all patches, and a large number of patches can lead to large overestimations of habitat occupancy. But when we explicitly modeled the underlying population dynamics within each patch, we found (1) that there was a strong correlation between proportion of occupied patches and total metapopulation size and (2) that the distribution of individuals among patches was relatively insensitive to model assumptions. Thus, our results show that although realistic modifications will change model predictions for occupancy, occupancy and population trends will be correlated. These correlations between occupancy and population size suggest that occupancy models may have some utility in conservation applications.     

Insights for Integrated Conservation from Attitudes of People toward Protected Areas Near Hwange National Park,Zimbabwe

Increase in human settlements at the edge of protected areas (PAs) is perceived as a major threat to conservation of biodiversity. Although it is crucial to integrate the interests of surrounding communities into PA management, key drivers of changes in local populations and the effects of conservation on local livelihoods and perceptions remain poorly understood. We assessed population changes from 1990 to 2010 in 9 villages located between 2 PAs with different management policies (access to natural resources or not). We conducted semi‐directive interviews at the household level (n =217) to document reasons for settlement in the area and villager's attitudes toward the PAs. We examined drivers of these attitudes relative to household typology, feelings about conservation, and concerns for the future with mixed linear models. Population increased by 61% from 2000 to 2010, a period of political and economic crisis in Zimbabwe. Forty‐seven percent of immigrants were attracted by the area; others had been resettled from other villages or were returning to family lands. Attitudes toward PAs were generally positive, but immigrants attracted by the area and who used resources within the PA with fewer restrictions expressed more negative attitudes toward PAs. Household location, losses due to wild animals, and restrictions on access to natural resources were the main drivers of this negative attitude. Profit‐seeking migrants did not expect these constraints and were particularly concerned with local overpopulation and access to natural resources. To avoid socio‐ecological traps near PAs (i.e., unforeseen reduced adaptive capacity) integrated conservation should address mismatches between management policy and local expectations. This requires accounting for endogenous processes, for example, local socio‐ecological dynamics and values that shape the coexistence between humans and wildlife. Percepciones para Conservación Integrada a Partir de las Actitudes de las Personas hacia Áreas Protegidas cerca del Parque Nacional Hwangem Zimbabwe     

Predicting tree distributions in an East African biodiversity hotspot: model selection, data bias and envelope uncertainty

The Eastern Arc Mountains (EAMs) of Tanzania and Kenya support some of the most ancient tropical rainforest on Earth. The forests are a global priority for biodiversity conservation and provide vital resources to the Tanzanian population. Here, we make a first attempt to predict the spatial distribution of 40 EAM tree species, using generalised additive models, plot data and environmental predictor maps at sub 1 km resolution. The results of three modelling experiments are presented, investigating predictions obtained by (1) two different procedures for the stepwise selection of predictors, (2) down-weighting absence data, and (3) incorporating an autocovariate term to describe fine-scale spatial aggregation. In response to recent concerns regarding the extrapolation of model predictions beyond the restricted environmental range of training data, we also demonstrate a novel graphical tool for quantifying envelope uncertainty in restricted range niche-based models (envelope uncertainty maps). We find that even for species with very few documented occurrences useful estimates of distribution can be achieved. Initiating selection with a null model is found to be useful for explanatory purposes, while beginning with a full predictor set can over-fit the data. We show that a simple multimodel average of these two best-model predictions yields a superior compromise between generality and precision (parsimony). Down-weighting absences shifts the balance of errors in favour of higher sensitivity, reducing the number of serious mistakes (i.e., falsely predicted absences); however, response functions are more complex, exacerbating uncertainty in larger models. Spatial autocovariates help describe fine-scale patterns of occurrence and significantly improve explained deviance, though if important environmental constraints are omitted then model stability and explanatory power can be compromised. We conclude that the best modelling practice is contingent both on the intentions of the analyst (explanation or prediction) and on the quality of distribution data; generalised additive models have potential to provide valuable information for conservation in the EAMs, but methods must be carefully considered, particularly if occurrence data are scarce. Full results and details of all species models are supplied in an online Appendix.     

Spatial,socio‐economic,and ecological implications of incorporating minimum size constraints in marine protected area network design

Marine protected areas (MPAs) are the cornerstone of most marine conservation strategies, but the effectiveness of each one partly depends on its size and distance to other MPAs in a network. Despite this, current recommendations on ideal MPA size and spacing vary widely, and data are lacking on how these constraints might influence the overall spatial characteristics, socio‐economic impacts, and connectivity of the resultant MPA networks. To address this problem, we tested the impact of applying different MPA size constraints in English waters. We used the Marxan spatial prioritization software to identify a network of MPAs that met conservation feature targets, whilst minimizing impacts on fisheries; modified the Marxan outputs with the MinPatch software to ensure each MPA met a minimum size; and used existing data on the dispersal distances of a range of species found in English waters to investigate the likely impacts of such spatial constraints on the region's biodiversity. Increasing MPA size had little effect on total network area or the location of priority areas, but as MPA size increased, fishing opportunity cost to stakeholders increased. In addition, as MPA size increased, the number of closely connected sets of MPAs in networks and the average distance between neighboring MPAs decreased, which consequently increased the proportion of the planning region that was isolated from all MPAs. These results suggest networks containing large MPAs would be more viable for the majority of the region's species that have small dispersal distances, but dispersal between MPA sets and spill‐over of individuals into unprotected areas would be reduced. These findings highlight the importance of testing the impact of applying different MPA size constraints because there are clear trade‐offs that result from the interaction of size, number, and distribution of MPAs in a network.     

Optimal annual routines: new tools for conservation biology?

Many applied problems in ecology and conservation require prediction, and population models are important tools for that purpose. Formerly, the majority of predictive population models were based on matrix models. As the limitations of classical matrix models have become clearer, the use of individual-based models has increased. These models use behavioral rules imposed at the level of the individual to establish the emergent consequences of those rules at the population level. Individual behaviors in such models use an array of different rule types, from empirically derived probabilities to long-term fitness considerations. There has been surprisingly little discussion of the strengths and weaknesses of these different rule types. Here, we consider different strategies for modeling individual behaviors, together with some problems associated with individual-based models. We propose a novel approach based on modeling optimal annual routines. Annual routines allow individual behaviors to be predicted over a whole annual cycle within the context of long-term fitness considerations. Temporal trade-offs between different behaviors are automatically included in annual routine models, overcoming some of the primary limitations of other individual-based models. Furthermore, as well as population predictions, individual behaviors and indices of condition are emergent features of annual routine models. We show that these can be more sensitive to environmental change than population size, offering alternative, repeatable metrics for monitoring population status. Annual routine models provide no panacea for the problems of data limitations in predictive population modeling. However, as a result of their ability to deal with life-history trade-offs, as well as their potential for relatively rapid and accurate validation and parameterization, we suggest that annual routine models have strong potential for predictive population modeling in applied conservation settings.     

Making more out of sparse data: hierarchical modeling of species communities

Community ecologists and conservation biologists often work with data that are too sparse for achieving reliable inference with species-specific approaches. Here we explore the idea of combining species-specific models into a single hierarchical model. The community component of the model seeks for shared patterns in how the species respond to environmental covariates. We illustrate the modeling framework in the context of logistic regression and presence-absence data, but a similar hierarchical structure could also be used in many other types of applications. We first use simulated data to illustrate that the community component can improve parameterization of species-specific models especially for rare species, for which the data would be too sparse to be informative alone. We then apply the community model to real data on 500 diatom species to show that it has much greater predictive power than a collection of independent species-specific models. We use the modeling approach to show that roughly one-third of distance decay in community similarity can be explained by two variables characterizing water quality, rare species typically preferring nutrient-poor waters with high pH, and common species showing a more general pattern of resource use.     

Population Growth, Human Development, and Deforestation in Biodiversity Hotspots

Abstract:  Human population and development activities affect the rate of deforestation in biodiversity hotspots. We quantified the effect of human population growth and development on rates of deforestation and analyzed the relationship between these causal factors in the 1980s and 1990s. We compared the averages of population growth, human development index (HDI, which measures income, health, and education), and deforestation rate and computed correlations among these variables for countries that contain biodiversity hotspots. When population growth was high and HDI was low there was a high rate of deforestation, but when HDI was high, rate of deforestation was low, despite high population growth. The correlation among variables was significant for the 1990s but not for the 1980s. The relationship between population growth and HDI had a regional pattern that reflected the historical process of development. Based on the changes in HDI and deforestation rate over time, we identified two drivers of deforestation: policy choice and human-development constraints. Policy choices that disregard conservation may cause the loss of forests even in countries that are relatively developed. Lack of development in other countries, on the other hand, may increase the pressure on forests to meet the basic needs of the human population. Deforestation resulting from policy choices may be easier to fix than deforestation arising from human development constraints. To prevent deforestation in the countries that have such constraints, transfer of material and intellectual resources from developed countries may be needed. Popular interest in sustainable development in developed countries can facilitate the transfer of these resources.