中国遗传资源优先保护等级评价标准的构建

确定科学合理的生物遗传资源优先保护等级,是当前保护生物学研究的一个核心问题。文章通过分析国内外遗传资源优先保护等级评价研究进展,针对遗传资源的特点,对遗传资源与物种关系、遗传资源多样性、境外种群影响、遗传资源价值、潜在利用价值、人工繁育技术、特有情况等方面进行了探讨并提出相应建议,初步确定了遗传资源优先保护等级的评价标准,以期能为生物遗传资源的有效保护和科学管理提供参考依据。     

GIS支持下的秦岭植被景观梯度分析

秦岭植被景观类型丰富,具有过渡性和复杂性特点,植被垂直分带明显. 在分析了大尺度秦岭植被景观空间水平分布格局的基础上,利用基于GIS梯度分析方法,分析秦岭的植被与海拔梯度的关系,得到秦岭不同植被景观类型的斑块数、分布范围、植被分布的海拨高度平均值和标准差,并以太白山为例,对太白山植物种进行了梯度分析. 结果表明,随着海拔高度的增加,太白山依次出现7种植被景观类型:温带草丛→温带落叶灌丛→温带落叶阔叶林→亚热带针叶林→亚热带和热带山地针叶林→草甸→高寒草甸等植被类型,植物种亦发生相应的变化.      

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Integrating intraseasonal grassland dynamics in cross-scale distribution modeling to support waterbird recovery plans

Despite much discussion about the utility of remote sensing for effective conservation, the inclusion of these technologies in species recovery plans remains largely anecdotal. We developed a modeling approach for the integration of local, spatially measured ecosystem functional dynamics into a species distribution modeling (SDM) framework in which other ecologically relevant factors are modeled separately at broad scales. To illustrate the approach, we incorporated intraseasonal water-vegetation dynamics into a cross-scale SDM for the Common Snipe (Gallinago gallinago), which is highly dependent on water and vegetation dynamics. The Common Snipe is an Iberian grassland waterbird characteristic of European agricultural meadows and a member of one of the most threatened bird guilds. The intraseasonal dynamics of water content of vegetation were measured using the standard deviation of the normalized difference water index time series computed from bimonthly images of the Sentinel-2 satellite. The recovery plan for the Common Snipe in Galicia (northwestern Iberian Peninsula) provided an opportunity to apply our modeling framework. Model accuracy in predicting the species’ distribution at a regional scale (resulting from integration of downscaled climate projections with regional habitat–topographic suitability models) was very high (area under the curve [AUC] of 0.981 and Boyce's index of 0.971). Local water-vegetation dynamic models, based exclusively on Sentinel-2 imagery, were good predictors (AUC of 0.849 and Boyce's index of 0.976). The predictive power improved (AUC of 0.92 and Boyce's index of 0.98) when local model predictions were restricted to areas identified by the continental and regional models as priorities for conservation. Our models also performed well (AUC of 0.90 and Boyce's index of 0.93) when projected to updated water-vegetation conditions. Our modeling framework enabled incorporation of key ecosystem processes closely related to water and carbon cycles while accounting for other factors ecologically relevant to endangered grassland waterbirds across different scales, allowed identification of priority areas for conservation, and provided an opportunity for cost-effective recovery planning by monitoring management effectiveness from space.     

Extinction rate of discovered and undiscovered plants in Singapore

Extinction is a key issue in the assessment of global biodiversity. However, many extinction rate measures do not account for species that went extinct before they could be discovered. The highly developed island city–state of Singapore has one of the best-documented tropical floras in the world. This allowed us to estimate the total rate of floristic extinctions in Singapore since 1822 after accounting for sampling effort and crypto extinctions by collating herbaria records. Our database comprised 34,224 specimens from 2076 native species, of which 464 species (22%) were considered nationally extinct. We assumed that undiscovered species had the same annual per-species extinction rates as discovered species and that no undiscovered species remained extant. With classical and Bayesian algorithms, we estimated that 304 (95% confidence interval, 213–414) and 412 (95% credible interval, 313–534) additional species went extinct before they could be discovered, respectively; corresponding total extinction rate estimates were 32% and 35% (range 30–38%). We detected violations of our 2 assumptions that could cause our extinction estimates, particularly the absolute numbers, to be biased downward. Thus, our estimates should be treated as lower bounds. Our results illustrate the possible magnitudes of plant extirpations that can be expected in the tropics as development continues.     

Rapidly assessing cobenefits to advance threat-management alliances

Conservation strategies aimed at reducing threats to biodiversity can have significant implications for multiple sectors in a socioeconomic system, but these cobenefits are often poorly understood. For example, many of the threats to native species also impede agricultural production, yet agriculture is typically perceived as in competition with conservation objectives. Although a comprehensive, multiobjective decision analysis is usually beyond the scope and capacity of conservation decision makers, failing to incorporate key socioeconomic costs and benefits into conservation decision-making processes can result in missed opportunities for diversifying outcomes and creating cost-sharing multisectoral partnerships. We devised a straightforward and readily interpretable approach to incorporate cobenefits into a threat-management prioritization approach. We used it to analyze the agricultural cobenefits of implementing 9 invasive animal management strategies designed to ensure the persistence of 148 threatened species across Australia's Lake Eyre Basin over 50 years. A structured elicitation process with 24 participants (scientists, land managers, agriculturalists, and other stakeholders) was used to collect information on each strategy, including costs, technical and social feasibility, benefits to native threatened species, and cobenefits to agricultural production systems. The costs of targeted invasive animal management to save threatened species across the basin (AU$33 million/year) outweighed the overall benefits to the agricultural industry (estimated AU$226 million/year). The return on investment for these management strategies varied substantially when agricultural cobenefits were considered alongside threatened species benefits and showed synergies and challenges. Our approach demonstrates the value of incorporating cobenefits of conservation actions into cost-effectiveness analyses to guide potential investment and partnerships and to diversify implementation pathways.     

A critical appraisal of population viability analysis

Population viability analysis (PVA) is useful in management of imperiled species. Applications range from research design, threat assessment, and development of management frameworks. Given the importance of PVAs, it is essential that they be rigorous and adhere to widely accepted guidelines; however, the quality of published PVAs is rarely assessed. We evaluated the quality of 160 PVAs of 144 species of birds and mammals published in peer-reviewed journals from 1990 to 2017. We hypothesized that PVA quality would be lower with generic programs than with custom-built programs; be higher for those developed for imperiled species; change over time; and be higher for those published in journals with high impact factors (IFs). Each included study was evaluated based on answers to an evaluation framework containing 32 questions reflecting whether and to what extent the PVA study adhered to published PVA guidelines or contained important PVA components. All measures of PVA quality were generally lower for studies based on generic programs. Conservation status of the species did not affect any measure of PVA quality, but PVAs published in high IF journals were of higher quality. Quality generally declined over time, suggesting the quantitative literacy of PVA practitioners has not increased over time or that PVAs developed by unskilled users are being published in peer-reviewed journals. Only 18.1% of studies were of high quality (score >75%), which is troubling because poor-quality PVAs could misinform conservation decisions. We call for increased scrutiny of PVAs by journal editors and reviewers. Our evaluation framework can be used for this purpose. Because poor-quality PVAs continue to be published, we recommend caution while using PVA results in conservation decision making without thoroughly assessing the PVA quality.     

Ecological features of species range formation in the Altai snowcock

Ecological conditions for the Altai snowcock and the history of formation of its range in the Altai-Sayan mountain region are discussed. The range of this species extends mainly over mountain massifs surrounding the Great Lakes Basin in western Mongolia and the Tuva Basin. These regions are characterized by broken relief with steep slopes. Snowcocks populate both humid high-mountain areas of the Alpine type and dry-steppe areas in middle and low mountains. Expansion of this species to the Altai-Sayan region is attributed to Miocene-Pliocene aridization well manifested in central Asia. The recent distribution of the Altai snowcock over different altitudinal belts is explained by alternation of glaciations and interglacial periods in the Pleistocene and anthropogenic impact in the Holocene. The total abundance of this rare species is estimated at 10000–12000 individuals.