Climate-change induced uncertainties in future spatial patterns of conservation-related outcomes make it difficult to implement standard conservation-planning paradigms. A recent study translates Markowitz's risk-diversification strategy from finance to conservation settings, enabling conservation agents to use this diversification strategy for allocating conservation and restoration investments across space to minimize the risk associated with such uncertainty. However, this method is information intensive and requires a large number of forecasts of ecological outcomes associated with possible climate-change scenarios for carrying out fine-resolution conservation planning. We developed a technique for iterative, spatial portfolio analysis that can be used to allocate scarce conservation resources across a desired level of subregions in a planning landscape in the absence of a sufficient number of ecological forecasts. We applied our technique to the Prairie Pothole Region in central North America. A lack of sufficient future climate information prevented attainment of the most efficient risk-return conservation outcomes in the Prairie Pothole Region. The difference in expected conservation returns between conservation planning with limited climate-change information and full climate-change information was as large as 30% for the Prairie Pothole Region even when the most efficient iterative approach was used. However, our iterative approach allowed finer resolution portfolio allocation with limited climate-change forecasts such that the best possible risk-return combinations were obtained. With our most efficient iterative approach, the expected loss in conservation outcomes owing to limited climate-change information could be reduced by 17% relative to other iterative approaches.
Establishing legal protection for forest areas is the most common policy used to limit forest loss. This article evaluates the effectiveness of seven Indonesian forest protected areas introduced between 1999 and 2012. Specifically, we explore how the effectiveness of these parks varies over space. Protected areas have mixed success in preserving forest, and it is important for conservationists to understand where they work and where they do not. Observed differences in the estimated treatment effect of protection may be driven by several factors. Indonesia is particularly diverse, with the landscape, forest and forest threats varying greatly from region to region, and this diversity may drive differences in the effectiveness of protected areas in conserving forest. However, the observed variation may also be spurious and arise from differing degrees of bias in the estimated treatment effect over space. In this paper, we use a difference-in-differences approach comparing treated observations and matched controls to estimate the effect of each protected area. We then distinguish the true variation in protected area effectiveness from spurious variation driven by several sources of estimation bias. Based on our most flexible method that allows the data generating process to vary across space, we find that the national average effect of protection preserves an additional 1.1% of forest cover; however the effect of individual parks range from a decrease of 3.4% to an increase of 5.3% and the effect of most parks differ from the national average. Potential biases may affect estimates in two parks, but results consistently show Sebangau National Park is more effective while two parks are substantially less able to protect forest cover than the national average.
Rapid conversion of private land for agricultural and urban use has raised concern worldwide over the loss of ecological services. To inform conservation policy, we model privately optimal land use decisions using a real options framework that assumes both the ecological and commercial values of land are stochastic and that land conversion is irreversible. We analyze permanent and temporary land conservation policy incentives using this dynamic framework to guide policy makers interested in designing efficient payment mechanisms to achieve ecological preservation goals. We find that while the financial cost of temporary policy incentives is generally much lower than permanent policy incentives, this difference is very small in scenarios with high discount rates and lower uncertainties in conversion returns and lower expected trend in conservation returns. Alternately, the financial cost of temporary conservation is substantially lower than that of permanent conservation when the expected trend in conservation returns and uncertainties in conservation and conversion returns is high and the discount rate is low. Comparison with net present value and single‐source uncertainty models indicates that the presence of a second uncertainty increases the option value of delaying conversion, and shows that permanent and temporary policy incentives based on either of the two simpler models can be seriously misguided if multiple uncertainties are present. We illustrate the analytical results with a case study of tropical deforestation in Indonesia where private landowners can either conserve forests and earn carbon credits, or convert to palm oil agriculture and earn profits from the sale of palm oil.
More than 15% of global terrestrial area is under some form of protection and there is a growing impetus to increase this coverage to 30% by 2030. But not all protection is effective and the reasons some countries’ protected areas (PAs) are more effective than others’ are poorly understood. We evaluate the effectiveness of national PA networks established between 2000 and 2012 globally in avoiding forest loss, taking into account underlying deforestation threats using a combination of matching methods and cross-sectional regressions. We then assess which demographic, agricultural, economic, and governance factors are most strongly associated with national PA effectiveness using machine learning methods. We estimate that national PAs established between 2000 and 2012 reduced deforestation in those areas by 72%, avoiding 86 062 km2 of forest loss. The effectiveness of national PAs varied by strictness of protection based on International Union for Conservation of Nature category. Strictly PAs reduced forest loss by 81% compared to what would have occurred without protection, while less strictly PAs reduced forest loss by 67%. Thus, the 26% of new PAs that were strictly protected contributed 39% of the total forest loss avoided within PAs between 2000 and 2012. If every country’s PAs were as effective as the country with the most effective PAs within the same region, they would have increased the area of deforestation avoided by 38%, saving a further 119 082 km2 of forest. Part of the variation in PA effectiveness across countries is explained by the placement of PA in areas facing higher deforestation threat. Countries with lower agricultural activity, higher economic growth and better governance are most strongly associated with greater country-level PA effectiveness.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.