<p> The spatial grain<sup>1</sup> at which ecological patterns are observed profoundly influences the inferences made about the underlying processes. In the case of species responses to environmental variation, only a limited number of grains – which I term "response grains" – are biologically meaningful to a particular species. In section I of this thesis, I summarize the development of this concept in ecology, describe its significance for ecological inference and information intended to support conservation planning, and introduce several potential approaches to measure – both directly and indirectly – a species' response grain(s).</p><p> While multi-grain studies of species-environment relationships are now relatively common, such studies typically consider a limited number of grains, based on either the spatial resolution of available environmental data, or the dimensions of landscape features predicted to be important for the species of interest (e.g. a reproductive site or an important food resource). The potentially confounding influences of environment spatial structure, and the spatial grain at which the analysis itself is performed ("analysis grain"), are often not considered. In section II of this thesis, I describe these important aspects of scale, and use a virtual species analysis to investigate their individual and joint impacts 'I use the terms "grain" and "extent" as commonly applied in geography and ecology. Spatial "grain" refers to the minimum mapping unit, analogous to a pixel or grid cell, and is most similar to the term "resolution." Spatial "extent" refers to the total area under consideration, and is equivalent to the concept of "study area." on the ability of standard analysis methods to detect and measure species-environment relationships. I show that the explanatory power of simple species distribution models generally declines with analysis grain. Moreover, a coarser response grain by the virtual species only marginally mitigates this trend, indicating that measurements of species-environment relationships at coarse analysis grains may not be wholly reliable.</p><p> In section III of this thesis, I synthesize ecological theory to describe two likely response grains for mobile vertebrate species: one equivalent to the (relatively fine) grain at which individuals identify profitable areas and use environmental resources, and a second equivalent to the (relatively coarse) grain equivalent to a species' typical home range. Based on the hierarchical structure of species-environment associations expected from well-established ecological theory, I extend occupancy modeling methods to develop a multi-grain, multi-level occupancy model. Through scale optimization within one model level, I measure the finest response grain for <i>Tockus deckeni</i> – a medium-sized, omnivorous hornbill native to East African savannas. By disentangling this species' niche relationships at multiple grains, we reveal that fine sites suitable for <i>T. deckeni</i> use are much more abundant than coarse sites suitable for its occupancy.</p><p> While ecological theory suggests that several species traits or attributes – primarily body size, home range size, trophic level, and degree of environmental or dietary specialization – determine the size of a species' response grain, very few studies have tested these expectations. In section IV of this thesis, I apply two approaches from the field of movement ecology to a large set of GPS telemetry data from four East African birds of varying body sizes Animal movement trajectories record the responses of individuals to the environmental conditions they encounter; thus, movement data should be particularly well suited to provide information about response grain. We find that, in general, response grain increases with both trophic position and home range size. Some study species exhibited a much smaller response grain than expected (under the most well-established theoretical expectation, based on body size), likely due to its low trophic position, narrow diet, and geometric constraints imposed by a small home range.</p><p> In section V of this thesis, I discuss how the information gained about species response grains in sections I – IV should be interpreted and applied in the contemporary context of modeling species distributions under expected changes to climate and land use. Analysts often select a "fine, local" or "coarse, range-wide" modeling approach based on the available data on environmental conditions and occurrences of the species of interest. However, in identifying multiple response grains and sets of species-environment relationships, we have shown that these two approaches capture different (though not strictly independent) ecological processes. Given these findings, as well as recent rapid expansions in sources of occurrence and environmental data, I provide practical advice for analysts Finally, I express several concluding thoughts about the overall work presented here.</p><p> <sup>1</sup>I use the terms "grain" and "extent" as commonly applied in geography and ecology. Spatial "grain" refers to the minimum mapping unit, analogous to a pixel or grid cell, and is most similar to the term "resolution." Spatial "extent" refers to the total area under consideration, and is equivalent to the concept of "study area."</p><p>
| Identifer | oai:union.ndltd.org:PROQUEST/oai:pqdtoai.proquest.com:10783456 |
| Date | 11 April 2018 |
| Creators | Mertes, Katherine |
| Publisher | Yale University |
| Source Sets | ProQuest.com |
| Language | English |
| Detected Language | English |
| Type | thesis |
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