A comparison of remotely sensed environmental predictors for avian distributions
A comparison of remotely sensed environmental predictors for avian distributions
复制标题
鸟类分布遥感环境预测因子的比较
DOI：
10.1007/s10980-022-01406-y
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发表时间：
2022
影响因子：
5.2
通讯作者：
Hutchinson, Rebecca A.
中科院分区：
文献类型：
--
作者：
Hopkins, Laurel M.;Hallman, Tyler A.;Kilbride, John;Robinson, W. Douglas;Hutchinson, Rebecca A.
随着在线平台的可访问性和处理能力的提高，遥感数据摘要越来越多地用于物种分布模型（SDMs）。比较这些环境变量的预测能力可以为sdm的发展提供信息。目的：我们评估了可免费获得的Landsat数据作为SDMs预测集的性能。我们的目标是：(1)比较基于原始光谱带平均值、Tasseled Cap变换和8个不同指数（包括NDVI）的单季节sdm的性能；(2)评估添加标准差、纹理指标和额外季节的性能增益；(3)比较基于这些连续光谱预测集的sdm与基于分类土地覆盖数据（例如森林覆盖率）的sdm的性能。方法采用全州点计数法对美国俄勒冈州13种鸟类建立多尺度sdm。我们比较了基于目标的每个预测集构建的sdm的性能。在陆地卫星衍生的预测集中，建立在原始光谱波段上的SDMs具有最高的整体性能，与流苏帽模型的性能几乎相当。虽然在原始带和流苏帽模型中，标准偏差、纹理指标和额外季节带来的性能收益最小，但在单指数模型中，收益是可观的。分类土地覆盖模型的性能与原始带模型相当。结论当预测性能至关重要时，原始陆地卫星波段是鸟类sdm的强预测因子。当简约变量必不可少时，单个指标（如NDVI）的sdm从附加信息（如标准差）中受益匪浅。
ContextWith greater accessibility and processing power from online platforms, summaries of remotely sensed data are increasingly used in species distribution models (SDMs). Comparisons of the predictive power of these environmental variables could inform SDMs moving forward.ObjectivesWe evaluated the performance of freely available Landsat data as predictor sets for SDMs. Our objectives were to (1) compare the performance of single season SDMs built on mean values of raw spectral bands, Tasseled Cap transformations, and eight different indices, including NDVI, (2) evaluate the performance gain with the addition of standard deviation, textural metrics, and additional seasons, and (3) compare the performance of SDMs built on these continuous spectral predictor sets to SDMs built on classified land cover data (e.g., percent forest cover).MethodsWe used statewide point counts to build multi-scale SDMs for 13 avian species across Oregon, USA. We compared the performance of SDMs built on each predictor set based on our objectives.ResultsOf the Landsat-derived predictor sets, SDMs built on raw spectral bands had the highest overall performance with nearly equivalent performance in Tasseled-Cap models. While performance gains from standard deviations, textural metrics, and additional seasons were minimal in raw-band and Tasseled-Cap models, gains were appreciable in single-index models. Classified land cover models performed equivalently to raw band models.ConclusionsWhen predictive performance is paramount, means of raw Landsat bands are strong predictors for avian SDMs. When parsimonious variables are essential, SDMs of single indices (e.g., NDVI) greatly benefit from additional information, such as standard deviation.
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俄勒冈鸟类：一般参考
DOI：
--
发表时间：
2004
期刊：
影响因子：
--
作者：
Robert I. Frey
通讯作者：
Robert I. Frey
影响因子：
13.5
作者：
Gorelick, Noel;Hancher, Matt;Moore, Rebecca
通讯作者：
Moore, Rebecca
从统计人工制品中解读生态学：样本量、流行率和栖息地专业化对物种分布模型的相互影响，以及小型评估数据集如何夸大绩效指标
DOI：
--
发表时间：
2020
期刊：
Diversity and Distributions: A journal of biological invasions and biodiversity
影响因子：
--
作者：
Tyler A. Hallman;W. Robinson
通讯作者：
W. Robinson
影响因子：
6.6
作者：
Valavi, Roozbeh;Elith, Jane;Guillera-Arroita, Gurutzeta
通讯作者：
Guillera-Arroita, Gurutzeta
建立更好的基线来估计 160 年来的鸟类种群变化并制定历史资料保护目标
影响因子：
6.3
作者：
Tyler A. Hallman;W. Robinson;J. Curtis;E. Alverson
通讯作者：
E. Alverson