首页 | 本学科首页   官方微博 | 高级检索  
相似文献
 共查询到4条相似文献,搜索用时 0 毫秒
1.
Abstract: Classifying species according to their risk of extinction is a common practice and underpins much conservation activity. The reliability of such classifications rests on the accuracy of threat categorizations, but very little is known about the magnitude and types of errors that might be expected. The process of risk classification involves combining information from many sources, and understanding the quality of each source is critical to evaluating the overall status of the species. One common criterion used to classify extinction risk is a decline in abundance. Because abundance is a direct measure of conservation status, counts of individuals are generally the preferred method of evaluating whether populations are declining. Using the thresholds from criterion A of the International Union for Conservation of Nature (IUCN) Red List (critically endangered, decline in abundance of >80% over 10 years or 3 generations; endangered, decline in abundance of 50–80%; vulnerable, decline in abundance of 30–50%; least concern or near threatened, decline in abundance of 0–30%), we assessed 3 methods used to detect declines solely from estimates of abundance: use of just 2 estimates of abundance; use of linear regression on a time series of abundance; and use of state‐space models on a time series of abundance. We generated simulation data from empirical estimates of the typical variability in abundance and assessed the 3 methods for classification errors. The estimates of the proportion of falsely detected declines for linear regression and the state‐space models were low (maximum 3–14%), but 33–75% of small declines (30–50% over 15 years) were not detected. Ignoring uncertainty in estimates of abundance (with just 2 estimates of abundance) allowed more power to detect small declines (95%), but there was a high percentage (50%) of false detections. For all 3 methods, the proportion of declines estimated to be >80% was higher than the true proportion. Use of abundance data to detect species at risk of extinction may either fail to detect initial declines in abundance or have a high error rate.  相似文献   

2.
         下载免费PDF全文
Many long‐distance migrating shorebird (i.e., sandpipers, plovers, flamingos, oystercatchers) populations are declining. Although regular shorebird monitoring programs exist worldwide, most estimates of shorebird population trends and sizes are poor or nonexistent. We built a state‐space model to estimate shorebird population trends. Compared with more commonly used methods of trend estimation, state‐space models are more mechanistic, allow for the separation of observation and state process, and can easily accommodate multivariate time series and nonlinear trends. We fitted the model to count data collected from 1990 to 2013 on 18 common shorebirds at the 2 largest coastal wetlands in southern Africa, Sandwich Harbour (a relatively pristine bay) and Walvis Bay (an international harbor), Namibia. Four of the 12 long‐distance migrant species declined since 1990: Ruddy Turnstone (Arenaria interpres), Little Stint (Calidris minuta), Common Ringed Plover (Charadrius hiaticula), and Red Knot (Calidris canutus). Populations of resident species and short‐distance migrants increased or were stable. Similar patterns at a key South African wetland suggest that shorebird populations migrating to southern Africa are declining in line with the global decline, but local conditions in southern Africa's largest wetlands are not contributing to these declines. State‐space models provide estimates of population levels and trends and could be used widely to improve the current state of water bird estimates.  相似文献   

3.
4.
Despite the high profile of amphibian declines and the increasing threat of drought and fragmentation to aquatic ecosystems, few studies have examined long‐term rates of change for a single species across a large geographic area. We analyzed growth in annual egg‐mass counts of the Columbia spotted frog (Rana luteiventris) across the northwestern United States, an area encompassing 3 genetic clades. On the basis of data collected by multiple partners from 98 water bodies between 1991 and 2011, we used state‐space and linear‐regression models to measure effects of patch characteristics, frequency of summer drought, and wetland restoration on population growth. Abundance increased in the 2 clades with greatest decline history, but declined where populations are considered most secure. Population growth was negatively associated with temporary hydroperiods and landscape modification (measured by the human footprint index), but was similar in modified and natural water bodies. The effect of drought was mediated by the size of the water body: populations in large water bodies maintained positive growth despite drought, whereas drought magnified declines in small water bodies. Rapid growth in restored wetlands in areas of historical population declines provided strong evidence of successful management. Our results highlight the importance of maintaining large areas of habitat and underscore the greater vulnerability of small areas of habitat to environmental stochasticity. Similar long‐term growth rates in modified and natural water bodies and rapid, positive responses to restoration suggest pond construction and other forms of management can effectively increase population growth. These tools are likely to become increasingly important to mitigate effects of increased drought expected from global climate change. Papeles de las Características del Fragmento, Frecuencia de Sequía y Restauración en las Tendencias a Largo Plazo de un Anfibio Ampliamente Distribuido  相似文献   

设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号