Wildlife in urban settings are a management challenge because wildlife populations and their habitats are often fragmented and degraded, but natural resource managers need information concerning their spatial distribution, spatial turnover, and spatial co-occurrence while accounting for imperfect detection. Based in the Chicago Metropolitan Area during 2009-2012, my study modeled 23 species across 5 wildlife taxa concerning patterns of site occupancy, spatial turnover (i.e., colonization and extinction), and/or spatial co-occurrence at 1-2 spatial scales. In detail, I investigated: (1) detection probabilities, site occupancy, and spatial turnover as affected by habitat and anthropogenic influences at 2 spatial scales for 6 species of songbirds: field sparrows (Spizella pusilla), great crested flycatchers (Myiarchus crinitus), willow flycatchers (Empidonax traillii), bobolinks (Dolichonyx oryzivorus), marsh wrens (Cistothorus palustris), and rose-breasted grosbeaks (Pheucticus ludovicianus); (2) detection probabilities, site occupancy, and spatial turnover as affected by habitat and anthropogenic influences at 2 spatial scales for 3 species of reptiles and 4 species of amphibians: common garter snakes (Thamnophis sirtalis), painted turtles (Chrysemys picta), snapping turtles (Chelydra serpentina), blue-spotted salamanders (Ambystoma laterale), tiger salamanders (Ambystoma tigrinum), green frogs (Rana clamitans), and northern leopard frogs (Rana pipiens); (3) habitat use and landscape site occupancy and spatial turnover as affected by habitat and anthropogenic influences for 4 species of mesocarnivores: coyotes (Canis latrans), raccoons (Procyon lotor), striped skunks (Mephitis mephitis), and Virginia opossums (Didelphis virginiana); and (4) detection probabilities and spatial distributions as affected by local habitat, an interacting species (dominant or subordinate), or both for 6 species of small mammals: short-tailed shrews (Blarina brevicauda), meadow voles (Microtus pennsylvanicus), white-footed mice (Peromyscus leucopus), gray squirrels (Sciurus carolinensis), masked shrews (Sorex cinereus), and eastern chipmunks (Tamias striatus). I elucidate how managers can improve or design their survey techniques that will aid their inference of the distribution of wildlife in the Midwest. This work also provides suburban natural resource managers in the Chicago Metropolitan Area with information concerning land management and land acquisition guidelines to best conserve, attract, or deter the aforementioned wildlife on their properties.

Biodiversity is determined by a myriad of complex processes acting at different scales. Given the current rates of biodiversity loss and change, it is of paramount importance that we improve our understanding of the underlying structure of ecological communities. In this thesis, I focused on Species Abundance Distributions (SAD), as a synthetic measure of biodiversity and community structure, and on Beta (β) diversity patterns, as a description of the spatial variation of species composition. I systematically assessed the effect of scale on both these patterns, analysing a broad range of community data, including different taxa and habitats, from the terrestrial, marine and freshwater realms. Knowledge of the scaling properties of abundance and compositional patterns must be fully integrated in biodiversity research if we are to understand biodiversity and the processes underpinning it, from local to global scales. SADs depict the relative abundance of the species present in a community. Although typically described by unimodal logseries or lognormal distributions, empirical SADs can also exhibit multiple modes. However, the existence of multiple modes in SADs has largely been overlooked, assumed to be due to sampling errors or a rare pattern. Thus, we do not know how prevalent multimodality is, nor do we have an understanding of the factors leading to this pattern. Here, I provided the first global empirical assessment of the prevalence of multimodality across a wide range of taxa, habitats and spatial extents. I employed an improved method combining two model selection tools, and (conservatively) estimated that ~15% of the communities were multimodal with strong support. Furthermore, I showed that the pattern is more common for communities at broader spatial scales and with greater taxonomic diversity (i.e. more phylogenetically diverse communities, since taxonomic diversity was measured as number of families). This suggests a link between multimodality and ecological heterogeneity, broadly defined to incorporate the spatial, environmental, taxonomic and functional variability of ecological systems. Empirical understanding of how spatial scale affects SAD shape is still lacking. Here, I established a gradient in spatial scale spanning several orders of magnitude by decomposing the total extent of several datasets into smaller subsets. I performed an exploratory analysis of how SAD shape is affected by area sampled, species richness, total abundance and taxonomic diversity. Clear shifts in SAD shape can provide information about relevant ecological and spatial mechanisms affecting community structure. There was a clear effect of area, species richness and taxonomic diversity in determining SAD shape, while total abundance did not exhibit any directional effect. The results supported the findings of the previous analysis, with a higher prevalence of multimodal SADs for larger areas and for more taxonomically diverse communities, while also suggesting that species spatial aggregation patterns can be linked to SAD shape. On the other hand, there was a systematic departure from the predictions of two important macroecological theories for SAD across scales, specifically regarding logseries distributions being selected only for smaller scales and when species richness and number of families were proportionally much smaller than the total extent. β diversity quantifies the variation in species composition between sites. Although a fundamental component of biodiversity, its spatial scaling properties are still poorly understood. Here, I tested if two conceptual types of β diversity showed systematic variation with scale, while also explicitly accounting for the two β diversity components, turnover and nestedness (species replacement vs species richness differences). I provided the first empirical analysis of β diversity scaling patterns for different taxa, revealing remarkably consistent scaling curves. Total β diversity and turnover exhibit a power law decay with log area, while nestedness is largely insensitive to scale changes. For the distance decay of similarity analysis, while area sampled affected the overall dissimilarity values, rates of similarity were consistent across large variations in sampled area. Finally, in both these analyses, turnover was the main contributor to compositional change. These results suggest that species are spatially aggregated across spatial scales (from local to regional scales), while also illustrating that substantial change in community structure might occur, despite species richness remaining relatively stable. This systematic and comprehensive analysis of SAD and community similarity patterns highlighted spatial scale, ecological heterogeneity and species spatial aggregation patterns as critical components underlying the results found. This work expanded the range of scales at which both theories deriving SAD and community similarity studies have been developed and tested (from local plots to continents). The results here showed strong departures from two important macroecological theories for SAD at different scales. In addition, the overall findings in this thesis clearly indicate that unified theories of biodiversity (or assuming a set of synthetic minimal assumptions) are unable to accommodate the variability in SADs shape across spatial scales reported here, and cannot fully reproduce community similarity patterns across scales. Incorporating more realistic assumptions, or imposing scale dependent assumptions, may prove to be a fruitful avenue for ecological research regarding the scaling properties of SAD and community similarity patterns. This will allow deriving new predictions and improving the ability of theoretical models to incorporate the variability in abundance and similarity patterns across scales.

No description available.