Multiscale Context for Change in Alpine Tundra

高山苔原受到气候变化的威胁，因为它所在的低温气候可能会在全球范围内减少。本研究将通过对北美西部高寒冻土带群落结构在多空间尺度上的研究，为气候变化对北美西部高寒冻土带的响应提供背景。重点是与高山冻土带多样性有关的过程的空间范围。本研究探讨了共同生长的植物物种混合（或次生物种多样性）在土壤特征上沿精细的空间尺度梯度存在差异的猜想。土壤梯度嵌套在由地形（如斜坡形状和位置）决定的更广泛的地理尺度梯度中，这些环境进一步嵌套在气候变量（辐射、温度和降水）的区域梯度中。例如，一个地点的降水水量取决于地形如何改变雪的再分配，植物可利用的融雪量受到土壤质地的影响。将收集有关高山冻土带地点物种丰富度的新数据，并用于推导生物多样性（相关）变量。场地条件（自变量）土壤和地表条件将在精细尺度上进行检查；地形测量是更一般的条件，因为它们比植物的范围更大，将在中等尺度上进行检查，并将根据为山区地形开发的外推，在粗尺度上检查来自已建立的气象站的气候变量。为了探索物种组成的可能关系，将采用三种分析方法：植被和环境差异两两差异的Mantel回归；基于正则对应分析的多尺度排序群落组成因变量的多水平回归是通过附加排序得到的。对于群落多样性，将采用以物种丰富度为因变量的多水平回归。本研究将通过测试跨空间尺度的层次关系，促进我们对生物多样性和群落生物地理学的理解。将开发多层次模型，以解决在更大范围内影响植物多样性和群落结构的层次控制，而不是在以前的生态研究中所做的。这项研究将为研究气候变化的潜在生态响应提供新的视角，因为它将考虑到存在于最精细尺度上的空间异质性。研究结果将为国家公园管理局的资源管理者提供有关高山苔原生物多样性未来可能发生变化的信息，这是一种重要的视觉和美学资源。更广泛地说，这项研究将改进解释并有助于全球高山监测网络的发现。

Alpine tundra is threatened by climate change because the low-temperature climates where it exists may be reduced globally. This study will provide a context for the response of alpine tundra in western North America to climate change by investigating the community structure of alpine tundra at multiple spatial scales. The focus is on the spatial extent of processes relevant to alpine tundra diversity. This study examines the conjecture that the mix of plant species growing together (or secondarily species diversity) differs along fine spatial scale gradients in soil characteristics. Soil gradients are nested within broader geographic-scale gradients determined by topography such as slope shape and position and these environments are further nested within regional gradients in climate variables (radiation, temperature, and precipitation). For example, the amount of water from precipitation at a site is modified by how the terrain alters the redistribution of snow, and the snowmelt available to plants is affected by soil texture. New data on the abundance of species on alpine tundra sites will be collected and used to derive biodiversity (dependent) variables. Site conditions (independent variables) of soil and surficial conditions will be examined at fine scale; topographic measures, which are more general conditions given that they are at larger extents than the plants, will be examined at a middle scale, and climate variables from established weather stations will be examined at coarse scale based on extrapolations developed for mountain topography. In order to explore possible relationships, three analytical methods will be applied for species composition: Mantel regression with pairwise dissimilarities of vegetation and environmental difference; multiscale ordination using canonical correspondence analysis; and multilevel regression with community composition dependent variables statistically derived by additional ordinations. For community diversity, multilevel regression will be used with species richness as the dependent variable. This research will advance our understanding of biodiversity and community biogeography by testing hierarchical relations across spatial scales. Multilevel models will be developed to address the kind of hierarchical controls that affect plant diversity and community structure across greater range of scales than done in prior ecological research. This research will provide new insight into potential ecological responses to climate change, which is a large-scale phenomenon, because it will take into account the spatial heterogeneity that exists at the finest scale. The results will inform National Park Service resource managers about possible future change in alpine tundra biodiversity, an important visual and aesthetic resource. More broadly, this study will improve interpretation and contribute to the findings of a global alpine monitoring network.