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首页> 外文期刊>Biological Conservation >Modeling the potential area of occupancy at fine resolution may reduce uncertainty in species range estimates.
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Modeling the potential area of occupancy at fine resolution may reduce uncertainty in species range estimates.

机译:在高分辨率下对潜在的潜在居住区域建模可以减少物种范围估计的不确定性。

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Area of Occupancy (AOO), is a measure of species geographical ranges commonly used for species red listing. In most cases, AOO is estimated using reported localities of species distributions at coarse grain resolution, providing measures subjected to uncertainties of data quality and spatial resolution. To illustrate the ability of fine-resolution species distribution models for obtaining new measures of species ranges and their impact in conservation planning, we estimate the potential AOO of an endangered species in alpine environments. We use field occurrences of relict Empetrum nigrum and maximum entropy modeling to assess whether different sampling (expert versus systematic surveys) may affect AOO estimates based on habitat suitability maps, and the differences between such measurements and traditional coarse-grid methods. Fine-scale models performed robustly and were not influenced by survey protocols, providing similar habitat suitability outputs with high spatial agreement. Model-based estimates of potential AOO were significantly smaller than AOO measures obtained from coarse-scale grids, even if the first were obtained from conservative thresholds based on the Minimal Predicted Area (MPA). As defined here, the potential AOO provides spatially-explicit measures of species ranges which are permanent in the time and scarcely affected by sampling bias. The overestimation of these measures may be reduced using higher thresholds of habitat suitability, but standard rules as the MPA permit comparable measures among species. We conclude that estimates of AOO based on fine-resolution distribution models are more robust tools for risk assessment than traditional systems, allowing a better understanding of species ranges at habitat level.Digital Object Identifier http://dx.doi.org/10.1016/j.biocon.2011.12.030
机译:占用面积(AOO)是对物种红色范围常用的物种地理范围的一种度量。在大多数情况下,AOO是使用报告的粗粒分辨率的物种分布局部性来估计的,从而提供了受数据质量和空间分辨率不确定性影响的措施。为了说明精细分辨率的物种分布模型获得物种范围新度量的能力及其在保护规划中的影响,我们估计了高山环境中濒危物种的潜在AOO。我们使用遗物 Empetrum nigrum 和最大熵模型进行田间调查,以根据栖息地适宜性图评估不同采样(专家与系统调查)是否可能影响AOO估计,以及此类测量值与传统粗略模型之间的差异。网格方法。精细规模的模型表现出色,不受调查协议的影响,可提供相似的栖息地适应性输出,并具有较高的空间一致性。即使是从基于最小预测面积(MPA)的保守阈值获得的第一个方法,基于模型的潜在AOO估计值也要比从粗尺度网格获得的AOO度量值小得多。如此处定义,潜在的AOO提供了物种范围的空间明确度量,这些物种范围在时间上是永久的,几乎不受采样偏差的影响。使用较高的栖息地适应性阈值可以减少对这些措施的高估,但是由于MPA允许在物种间采取类似措施,因此这是标准规则。我们得出的结论是,基于精细分辨率分布模型的AOO估计比传统系统是用于风险评估的更强大的工具,可以更好地了解栖息地一级的物种范围。数字对象标识符http://dx.doi.org/10.1016/ j.biocon.2011.12.030

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