A simple economic model of endangered species preservation in the United States

Concern for the acceleration in threats to species diversity in the United States led to the passage of the Endangered Species Act of 1973. In this paper, this legislation is examined in an economic context. A simple model is developed where management and constraints on economic activity are substitutes in the production of species stocks. Whether economic growth constraints (the primary policy tool of the 1973 Act) are justified for preservation purposes depends on technical substitution possibilities, relative cost ratios, and the existence of budget constraints for species management. Since the same combination of these factors will not occur for all species, it is argued that more flexibility in endangered species policy may preserve the same levels of species stocks at lower costs to society.     

Economic land use, ecosystem services and microfounded species dynamics

In an integrated economy–ecosystem model humans choose their land use and leave the residual land as habitat for three species forming a food chain. The size of habitat determines the diversity and abundance of species. That biodiversity generates, in turn, a flow of ecosystem services with public-good characteristics for human consumption. The ecosystem submodel yields (rather than assumes!) population growth functions with each species’ growth depending on the size of habitat. First the relationship between habitat and species growth (sustenance, decline and extinction) is explored. The laissez-faire economy is shown to result in an underprovision of habitat making the case for land use restrictions for nature protection. The optimal land use policy is characterized with full regard of ecosystem dynamics. Finally, labor-augmenting technical change is introduced to generate ever increasing pressure towards further habitat reductions. In the laissez-faire economy the habitat is consequently squeezed to zero in the long-run so that all species are doomed. Social optimality demands, however, to refrain from using all land for economic purposes despite ever growing labor productivity.     

Using citizen science data to identify the sensitivity of species to human land use

Conservation practitioners must contend with an increasing array of threats that affect biodiversity. Citizen scientists can provide timely and expansive information for addressing these threats across large scales, but their data may contain sampling biases. We used randomization procedures to account for possible sampling biases in opportunistically reported citizen science data to identify species’ sensitivities to human land use. We analyzed 21,044 records of 143 native reptile and amphibian species reported to the Carolina Herp Atlas from North Carolina and South Carolina between 1 January 1990 and 12 July 2014. Sensitive species significantly associated with natural landscapes were 3.4 times more likely to be legally protected or treated as of conservation concern by state resource agencies than less sensitive species significantly associated with human‐dominated landscapes. Many of the species significantly associated with natural landscapes occurred primarily in habitats that had been nearly eradicated or otherwise altered in the Carolinas, including isolated wetlands, longleaf pine savannas, and Appalachian forests. Rare species with few reports were more likely to be associated with natural landscapes and 3.2 times more likely to be legally protected or treated as of conservation concern than species with at least 20 reported occurrences. Our results suggest that opportunistically reported citizen science data can be used to identify sensitive species and that species currently restricted primarily to natural landscapes are likely at greatest risk of decline from future losses of natural habitat. Our approach demonstrates the usefulness of citizen science data in prioritizing conservation and in helping practitioners address species declines and extinctions at large extents.     

The dilemma of pest suppression in the conservation of endangered species

In the conservation of endangered species, suppression of a population of one native species to benefit another poses challenges. Examples include predator control and nest parasite reduction. Less obvious is the control of blood-feeding arthropods. We conducted a case study of the effect of native black flies (Simulium spp.) on reintroduced Whooping Cranes (Grus americana). Our intent was to provide a science-driven approach for determining the effects of blood-feeding arthropods on endangered vertebrates and identifying optimal management actions for managers faced with competing objectives. A multiyear experiment demonstrated that black flies reduce nest success in cranes by driving incubating birds off their nests. We used a decision-analytic approach to develop creative management alternatives and evaluate trade-offs among competing objectives. We identified 4 management objectives: establish a self-sustaining crane population, improve crane well-being, maintain native black flies as functional components of the ecosystem, and minimize costs. We next identified potential management alternatives: do nothing, suppress black flies, force crane renesting to occur after the activity period of black flies, relocate releases of cranes, suppress black flies and relocate releases, or force crane renesting and relocate releases. We then developed predictions on constructed scales of 0 (worst-performing alternative) to 1 (best-performing alternative) to indicate how alternative actions performed in terms of management objectives. The optimal action depended on the relative importance of each objective to a decision maker. Only relocating releases was a dominated alternative, indicating that it was not optimal regardless of the relative importance of objectives. A rational decision maker could choose any other management alternative we considered. Recognizing that decisions involve trade-offs that must be weighed by decision makers is crucial to identifying alternatives that best balance multiple management objectives. Given uncertainty about the population dynamics of blood-feeding arthropods, an adaptive management approach could offer substantial benefits.     

Modeled historical land use and land cover for the conterminous United States

The landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.     

土地利用变化对生物多样性的影响

土地利用变化对生物多样性影响是生物多样性受到威胁的重要因素.文章对土地利用变化对基因多样性、物种多样性、生态系统多样性影响方面的研究进行了总结分析,并提出了新的展望.土地利用变化对基因多样性的影响涉及了对物种生境的隔离、农牧业活动对物种改良和生境条件的改变方面,目前还主要集中在对少数物种繁殖过程方面影响的研究;土地利用变化对物种多样性影响包括对物种优势度和丰富度、种间关系、物种分布格局、物种入侵和灭绝方面的影响,目前对物种丰富性和多样性影响方面研究较多,对物种灭绝、物种入侵和种间关系影响方面的研究极少,且还限于大型动物和植物,对微生物和小型动植物研究却很少;土地利用变化对生态系统的影响涉及了对生态系统结构组成及分布方面的影响.另外,目前缺少土地利用变化对基因多样性、物种多样性和生态系统多样性综合影响方面的研究,难以量化和预测土地利用变化对生物多样性影响效应.未来需要综合考虑基因多样性、物种多样性和生态系统多样性方面,系统开展土地利用变化对生物多样性影响的趋势和机制方面的研究,定量预测土地利用变化对生物多样性的影响.     

濒危植物疏花水柏枝种子萌发的生态学特性

疏花水柏枝Myricaria laxiflora分布于我国三峡从宜昌至重庆段长江干流的消落带,分布区十分狭小.三峡工程兴建后,疏花水柏枝将失去绝大部分的生境而成为濒危物种.通过设置一系列控制实验测试了土壤水质量分数,温度和土壤类型对疏花水柏枝种子萌发的生态学的影响.实验结果表明,土壤水质量分数、温度和土壤类型对种子萌发率都有显著影响.其中种子萌发率随土壤水质量分数增加而增大,土壤水质量分数达到饱和程度时萌发率达到最大值;高温条件下的种子萌发率高于低温,种子萌发率在21～27℃达到最大值;种子在河沙基质上萌发好于在沙土基质上.结合分布区萌发季节的环境条件分析,土壤水质量分数是限制该物种分布于消落带的关键作用因子.据此就该物种的种群保护与重建提出了一些建议.     

西双版纳民族村寨土地利用的景观影响

采用参与性农村评估法 ,并结合地方农业统计年鉴 ,从村级水平对西双版纳巴卡小寨和大卡老寨 2个民族村寨土地利用的景观影响作了初步调查与分析。结果表明 ,人多地少的巴卡小寨因无大面积的公益林等自然景观而使其人为干扰强度指数为 3.196 5 ,较大卡老寨强烈 ;受干扰景观中的粮食作物地和经济作物园斑块较多 ,景观破碎度分别为 0 .0 6 92和 0 .0 980hm-2 ,均大于大卡老寨。大卡老寨因为具有公益林、风景林和水体 ,其景观多样性为 1.4 5 95 ,以公益林、经济作物园和粮食作物地为优势景观 ;大卡老寨景观均匀度和优势度分别为 0 .6 6 4 2和 0 .7377,均大于巴卡小寨。 2个村寨的粮食作物地和经济作物园面积较大 ,表明粮食生产与经济作物种植是山区发展的出路所在 ,而水田面积的扩大和稳定有利于提高人口承载力。各景观类型的规模因受市场、技术等方面的影响而逐年波动 ,但从长时间来看又趋于稳定。民族文化政策和市场对 2个村寨土地利用和景观格局影响较大。     

吉林西部土地利用/覆被时空变化驱动力分析

针对吉林两部土地利用/覆被情况,基于TM影像,借助人机交互解译方法,结合1:10万地形图获得1986年、1996年、2000年和2004年的4期土地利用/覆被变化(LUCC)矢量数据.利用土地利用动态度模型、土地利用转移矩阵.全面揭示研究区15年的LUCC时空变化特征,结果表明.盐碱地扩张,湿地、水域萎缩和草地退化已经成为吉林西部生态环境恶化的突出表现.结合研究区的实际情况选取总人口数、农业人口数、粮食总产置等12个指标作为LUCC:变化的丰十会经济驱动因子,借助多元线性回归模型,建立主要土地利用类型的驱动力模型.结果表明吉林西部土地利用变化的最主要社会经济因子是农业人口数、农民人均纯收入、农业生产技术(农业机械总动力、化肥施用量)和农村用电量,同时提出相应的生态环境保护和社会经济措施.     

Framing the search for a theory of land use

ABSTRACT

Land system science and affiliated research linked to sustainability require improved understanding and theorization of land and its change as a social-ecological system (SES). The absence of a general land-use theory, anchored in the social subsystem but with explicit links to the environmental subsystem, hampers this effort. Drawing on land-use explanations, meta-analyses, and associated frameworks, we advance a broad framework structure of eight elements – aggregations of explanatory variables – with links to the biophysical subsystem, for systematic comparisons of extant explanations. Tests and models can be employed to identify which set of variables and their configurations provide robust explanations of across land uses, identifying the potential for theory development. The framework and its application are applicable to both top-down and bottom-up explanatory approaches employed in the social sciences. Links to the environmental subsystem invite future exploration of SES explanations that reach across the different dimensions of global change and sustainability science.     

Assessing the shelf life of cost‐efficient conservation plans for species at risk across gradients of agricultural land use

High costs of land in agricultural regions warrant spatial prioritization approaches to conservation that explicitly consider land prices to produce protected‐area networks that accomplish targets efficiently. However, land‐use changes in such regions and delays between plan design and implementation may render optimized plans obsolete before implementation occurs. To measure the shelf life of cost‐efficient conservation plans, we simulated a land‐acquisition and restoration initiative aimed at conserving species at risk in Canada's farmlands. We accounted for observed changes in land‐acquisition costs and in agricultural intensity based on censuses of agriculture taken from 1986 to 2011. For each year of data, we mapped costs and areas of conservation priority designated using Marxan. We compared plans to test for changes through time in the arrangement of high‐priority sites and in the total cost of each plan. For acquisition costs, we measured the savings from accounting for prices during site selection. Land‐acquisition costs and land‐use intensity generally rose over time independent of inflation (24–78%), although rates of change were heterogeneous through space and decreased in some areas. Accounting for spatial variation in land price lowered the cost of conservation plans by 1.73–13.9%, decreased the range of costs by 19–82%, and created unique solutions from which to choose. Despite the rise in plan costs over time, the high conservation priority of particular areas remained consistent. Delaying conservation in these critical areas may compromise what optimized conservation plans can achieve. In the case of Canadian farmland, rapid conservation action is cost‐effective, even with moderate levels of uncertainty in how to implement restoration goals.     

科尔沁沙地土地利用变化对土壤特性的影响

在中国科学院奈曼沙漠化研究站放牧试验场周围,选取了不同利用方式和类型的草地（封育和放牧）、林地（乔木和灌木）和农田（灌溉和非灌溉）为研究样地,调查了0～30cm土层每隔10cm的土壤水分质量分数和有机养分（有机碳和全氮）,分析了土地利用变化对土壤水分质量分数和有机养分的影响。结果发现,垂直空间分布上,无论哪种土地类型样地,土壤水分质量分数和有机养分各土层间均无显著差异性（P〉0.05）,土层垂直变化对土壤特性影响均较小。在不同土地利用方式水平空间分布上,土壤水分质量分数和有机养分（土壤有机碳和全氮）灌木林地均显著高于乔木林地（P〈0.05）,而封育草地和放牧草地间以及灌溉农田与非灌溉农田间土壤水分质量分数和有机养分均无显著差异性（P〉0.05）。不同土地利用类型水平分布上,草地土壤水分质量分数显著低于林地和农田（P〈0.05）,而土壤养分质量分数草地显著高于林地和农田（P〈0.05）。分析表明,对沙质草地进行围栏封育和旱作农田退耕还林还草的同时,对水浇农田实行保护性耕作和精细管理,有利于沙地土壤环境改善与生态系统恢复。     

Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks

Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.     

The effectiveness of the US endangered species act: An econometric analysis using matching methods

Diametrically opposed views of the effectiveness of the United States Endangered Species Act (ESA) co-exist more than 30 years after the Act's creation. The evidence marshaled to date for and against the ESA suffers from a problem common in analyses of biodiversity protection measures: the absence of a well-chosen control group. We demonstrate how matching methods can be used to select such a control group and thereby estimate how species listed under the ESA would have fared had they not been listed. Our results show that listing a species under the ESA is, on average, detrimental to species recovery if not combined with substantial government funds. In contrast, listed species with such funding tend to improve. Our analysis offers not only new insights into a controversial debate, but also a methodology to guide conservation scientists in evaluating the effectiveness of society's responses to biodiversity loss.     

The cost of endangered species protection: Evidence from auctions for natural resources

This paper examines the effect that endangered species regulation has on natural resource development. Specifically, we use data from competitive auctions to estimate the effect that land-use regulation protecting endangered caribou in the Canadian province of Alberta has on the price producers pay for the right to extract oil. We exploit a regression discontinuity design to evaluate how prices differ along regulation boundaries that constrain resource development. The auction format and the regulation discontinuity allow us to measure the total cost of the regulation. We find that producers pay 24% less on average for oil leases that are regulated and that the total net present value cost of the regulation exceeds $1.15 billion for leases sold between 2003 and 2012, all of which is borne by the government. In spite of these costs, the populations of endangered caribou remain in widespread decline.     

Projecting population trends of endangered amphibian species in the face of uncertainty: A pattern-oriented approach

Amphibian populations have been declining worldwide for the last three decades. Determining the risk of extinction is one of the major goals of amphibian conservation, yet few quantitative models have been developed for amphibian populations. Like most rare or threatened populations, there is a paucity of life history data available for most amphibian populations. Data on the critical juvenile life stage are particularly lacking. Pattern oriented modeling (POM) has been used successfully to estimate life history parameters indirectly when critical data lacking, but has not been applied to amphibian populations. We describe a spatially explicit, individual-based, stochastic simulation model developed to project population dynamics of pond-breeding amphibian populations. We parameterized the model with life history and habitat data collected for the endangered Houston toad (Bufohoustonensis), a species for which there is a high degree of uncertainty for juvenile and adult male survival. During model evaluation, we focused on explicitly reducing this uncertainty, evaluating 16 different versions of the model that represented the range of parametric uncertainty for juvenile and adult male survival. Following POM protocol, we compared simulation results to four population-level patterns observed in the field: population size, adult sex ratio, proportion of toads returning to their natal pond, and mean maximum distance moved. Based on these comparisons, we rejected 11 of the 16 model versions. Results of the remaining versions confirmed that population persistence depends heavily on juvenile survival, and further suggested that probability of juvenile survival is likely between 0.0075 and 0.015 (previous estimates ranged from 0.003 to 0.02), and that annual male survival is near 0.15 (previous estimates ranged up to 0.43).