Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
Regional mapping of species‐level continuous foliar cover: beyond categorical vegetation mapping
复制标题
物种级连续叶面覆盖的区域制图：超越分类植被制图
DOI：
10.1002/eap.2081
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发表时间：
2020
影响因子：
5
通讯作者：
Frank D. W. Witmer
中科院分区：
文献类型：
--
作者：
Timm W. Nawrocki;Matthew L. Carlson;Jeanne L. D. Osnas;E. Jamie Trammell;Frank D. W. Witmer
摘要 量化空间格局和检测大面积陆地植被变化的能力取决于将地面植被测量与遥感数据联系起来。与非重叠的分类植被类型（即典型的植被和土地覆盖图）不同，叶面覆盖的物种水平梯度与物种和生态位空间的个体响应的生态理论一致。我们收集了 2012 年至 2017 年北极沿海平原和阿拉斯加布鲁克斯山麓的维管植物、苔藓植物和地衣物种的叶面覆盖数据以及 17 个环境变量。我们将这些数据整合到一个标准化数据库中，其中包含 1998 年至 2017 年在阿拉斯加北部收集的 13 个额外植被调查和监测数据集。绘制北极六种主要和广泛分布的维管植物物种的叶面覆盖模式阿拉斯加，我们使用贝叶斯统计学习方法将地面物种分布和丰度测量结果与环境和多季节光谱协变量进行统计关联。对于 6 个模型物种中的 5 个，我们的模型预测了所观察到的物种水平叶覆盖变化的 36% 至 65%。总体而言，我们的连续叶面覆盖图比现有的分类植被图更能预测观察到的物种分布和丰度的空间异质性。在物种水平上绘制连续叶面覆盖图也揭示了现有植物功能类型方法中聚集所掩盖的生态模式。植被格局的物种层面分析能够独立于主观分类植被类型来量化和监测物种、植被群落和野生动物栖息地的景观层面变化，并有助于跨多个生态尺度整合空间格局。这里描述的新颖的物种级叶面覆盖制图方法提供了有关植物物种在植被群落和野生动物栖息地中的功能作用的空间信息，这些信息在分类植被地图或广义植被聚合体的定量地图中是不可用的。
Abstract The ability to quantify spatial patterns and detect change in terrestrial vegetation across large landscapes depends on linking ground‐based measurements of vegetation to remotely sensed data. Unlike non‐overlapping categorical vegetation types (i.e., typical vegetation and land cover maps), species‐level gradients of foliar cover are consistent with the ecological theories of individualistic response of species and niche space. We collected foliar cover data for vascular plant, bryophyte, and lichen species and 17 environmental variables in the Arctic Coastal Plain and Brooks Foothills of Alaska from 2012 to 2017. We integrated these data into a standardized database with 13 additional vegetation survey and monitoring data sets in northern Alaska collected from 1998 to 2017. To map the patterns of foliar cover for six dominant and widespread vascular plant species in arctic Alaska, we statistically associated ground‐based measurements of species distribution and abundance to environmental and multi‐season spectral covariates using a Bayesian statistical learning approach. For five of the six modeled species, our models predicted 36% to 65% of the observed species‐level variation in foliar cover. Overall, our continuous foliar cover maps predicted more of the observed spatial heterogeneity in species distribution and abundance than an existing categorical vegetation map. Mapping continuous foliar cover at the species level also revealed ecological patterns obscured by aggregation in existing plant functional type approaches. Species‐level analysis of vegetation patterns enables quantifying and monitoring landscape‐level changes in species, vegetation communities, and wildlife habitat independently of subjective categorical vegetation types and facilitates integrating spatial patterns across multiple ecological scales. The novel species‐level foliar cover mapping approach described here provides spatial information about the functional role of plant species in vegetation communities and wildlife habitat that are not available in categorical vegetation maps or quantitative maps of broadly defined vegetation aggregates.
影响因子：
13.5
作者：
Gorelick, Noel;Hancher, Matt;Moore, Rebecca
通讯作者：
Moore, Rebecca