Modeling freshwater fish distributions using multiscale landscape data: A case study of six narrow range endemics

Species distribution models (SDMs) have become integral tools in scientific research and conservation planning. Despite progress in the assessment of various statistical models for use in SDMs, little has been done in way of evaluating appropriate ecological models. In this paper, we evaluate the multiscale filter framework as a suitable theoretical model for predicting freshwater fish distributions in the upper Green River system (Ohio River drainage), USA. The spatial distributions of six fishes with contrasting biogeographies were modeled using boosted regression trees and multiscale landscape data. Species biogeography did not appear to affect predictive performance and all models performed well statistically with receiver operating characteristic area under the curve (AUC) ranging from 0.87 to 0.98. Predictive maps show accurate estimations of ranges for five of six species based on historical collections. The relative influence of each type of environmental feature and spatial scale varied markedly with between species. A hierarchical effect was detected for narrowly distributed species. These species were highly influenced by soil composition at larger spatial scales and land use/land cover (LULC) patterns at more proximal scales. Conversely, LULC pattern was the most influential feature for widely distributed at all spatial scales. Using multiscale data capable of capturing hierarchical landscape influences allowed production of accurate predictive models and provided further insight into factors controlling freshwater fish distributions.     

Spatial scale and species identity influence the indigenous-alien diversity relationship in springtails

Although theory underlying the invasion paradox, or the change in the relationship between the richness of alien and indigenous species from negative to positive with increasing spatial scale, is well developed and much empirical work on the subject has been undertaken, most of the latter has concerned plants and to a lesser extent marine invertebrates. Here we therefore examine the extent to which the relationships between indigenous and alien species richness change from the local metacommunity to the interaction neighborhood scales, and the influences of abundance, species identity, and environmental favorability thereon, in springtails, a significant component of the soil fauna. Using a suite of modeling techniques, including generalized least squares and geographically weighted regressions to account for spatial autocorrelation or nonstationarity of the data, we show that the abundance and species richness of both indigenous and alien species at the metacommunity scale respond strongly to declining environmental favorability, represented here by altitude. Consequently, alien and indigenous diversity covary positively at this scale. By contrast, relationships are more complex at the interaction neighborhood scale, with the relationship among alien species richness and/or density and the density of indigenous species varying between habitats, being negative in some, but positive in others. Additional analyses demonstrated a strong influence of species identity, with negative relationships identified at the interaction neighborhood scale involving alien hypogastrurid springtails, a group known from elsewhere to have negative effects on indigenous species in areas where they have been introduced. By contrast, diversity relationships were positive with the other alien species. These results are consistent with both theory and previous empirical findings for other taxa, that interactions among indigenous and alien species change substantially with spatial scale and that environmental favorability may play a key role in explaining the larger scale patterns. However, they also suggest that the interactions may be affected by the identity of the species concerned, especially at the interaction neighborhood scale.     

The theory behind,and the challenges of,conserving nature's stage in a time of rapid change

Most conservation planning to date has focused on protecting today's biodiversity with the assumption that it will be tomorrow's biodiversity. However, modern climate change has already resulted in distributional shifts of some species and is projected to result in many more shifts in the coming decades. As species redistribute and biotic communities reorganize, conservation plans based on current patterns of biodiversity may fail to adequately protect species in the future. One approach for addressing this issue is to focus on conserving a range of abiotic conditions in the conservation‐planning process. By doing so, it may be possible to conserve an abiotically diverse “stage” upon which evolution will play out and support many actors (biodiversity). We reviewed the fundamental underpinnings of the concept of conserving the abiotic stage, starting with the early observations of von Humboldt, who mapped the concordance of abiotic conditions and vegetation, and progressing to the concept of the ecological niche. We discuss challenges posed by issues of spatial and temporal scale, the role of biotic drivers of species distributions, and latitudinal and topographic variation in relationships between climate and landform. For example, abiotic conditions are not static, but change through time—albeit at different and often relatively slow rates. In some places, biotic interactions play a substantial role in structuring patterns of biodiversity, meaning that patterns of biodiversity may be less tightly linked to the abiotic stage. Furthermore, abiotic drivers of biodiversity can change with latitude and topographic position, meaning that the abiotic stage may need to be defined differently in different places. We conclude that protecting a diversity of abiotic conditions will likely best conserve biodiversity into the future in places where abiotic drivers of species distributions are strong relative to biotic drivers, where the diversity of abiotic settings will be conserved through time, and where connectivity allows for movement among areas providing different abiotic conditions.     

Spatial scaling of avian population dynamics: population abundance, growth rate, and variability

Synchrony in population fluctuations has been identified as an important component of population dynamics. In a previous study, we determined that local-scale (<15-km) spatial synchrony of bird populations in New England was correlated with synchronous fluctuations in lepidopteran larvae abundance and with the North Atlantic Oscillation. Here we address five questions that extend the scope of our earlier study using North American Breeding Bird Survey data. First, do bird populations in eastern North America exhibit spatial synchrony in abundances at scales beyond those we have documented previously? Second, does spatial synchrony depend on what population metric is analyzed (e.g., abundance, growth rate, or variability)? Third, is there geographic concordance in where species exhibit synchrony? Fourth, for those species that exhibit significant geographic concordance, are there landscape and habitat variables that contribute to the observed patterns? Fifth, is spatial synchrony affected by a species' life history traits? Significant spatial synchrony was common and its magnitude was dependent on the population metric analyzed. Twenty-four of 29 species examined exhibited significant synchrony in population abundance: mean local autocorrelation (rho)= 0.15; mean spatial extent (mean distance where rho=0) = 420.7 km. Five of the 29 species exhibited significant synchrony in annual population growth rate (mean local autocorrelation = 0.06, mean distance = 457.8 km). Ten of the 29 species exhibited significant synchrony in population abundance variability (mean local autocorrelation = 0.49, mean distance = 413.8 km). Analyses of landscape structure indicated that habitat variables were infrequent contributors to spatial synchrony. Likewise, we detected no effects of life history traits on synchrony in population abundance or growth rate. However, short-distance migrants exhibited more spatially extensive synchrony in population variability than either year-round residents or long-distance migrants. The dissimilarity of the spatial extent of synchrony across species suggests that most populations are not regulated at similar spatial scales. The spatial scale of the population synchrony patterns we describe is likely larger than the actual scale of population regulation, and in turn, the scale of population regulation is undoubtedly larger than the scale of individual ecological requirements.     

The influence of host diversity and composition on epidemiological patterns at multiple spatial scales

Spatial patterns of pathogen prevalence are determined by ecological processes acting across multiple spatial scales. Host-pathogen interactions are influenced by community composition, landscape structure, and environmental factors. Explaining prevalence patterns requires an understanding of how local determinants of infection, such as community composition, are mediated by landscape characteristics and regional-scale environmental drivers. Here we investigate the role of local community interactions and the effects of landscape structure on the dynamics of barley and cereal yellow dwarf viruses (B/CYDV) in the open meadows of the Cascade Mountains of Oregon. B/CYDV is an aphid-transmitted, generalist pathogen of over 100 wild and cultivated grass species. We used variance components analysis and model selection techniques to partition the sources of variation in B/CYDV prevalence and to determine which abiotic and biotic factors influence host-pathogen interactions in a Cascades meadowsystem. B/CYDV prevalence in Cascades meadows varied by host species identity, with a significantly higher proportion of infected Festuca idahoensis individuals than Elymus glaucus or Bromus carinatus. Although there was significant variation in prevalence among host species and among meadows in the same meadow complex, there was no evidence of any significant variation in prevalence among different meadow complexes at a larger spatial scale. Variation in prevalence among meadows was primarily associated with the local community context (host identity, the relative abundance of different host species, and host species richness) and the physical landscape attributes of the meadow. These results highlight the importance of local host community composition, mediated by landscape characteristics such as meadow aspect, as a determinant of the spatial pattern of infection of a multi-host pathogen.     

Biotic and abiotic controls of Argentine ant invasion success at local and landscape scales

Although the ecological success of introduced species hinges on biotic interactions and physical conditions, few experimental studies--especially on animals--have simultaneously investigated the relative importance of both types of factors. The lack of such research may stem from the common assumption that native and introduced species exhibit similar environmental tolerances. Here we combine experimental and spatial modeling approaches (1) to determine the relative importance of biotic and abiotic controls of Argentine ant (Linepithema humile) invasion success, (2) to examine how the importance of these factors changes with spatial scale in southern California (USA), and (3) to assess how Argentine ants differ from native ants in their environmental tolerances. A factorial field experiment that combined native ant removal with irrigation revealed that Argentine ants failed to invade any dry plots (even those lacking native ants) but readily invaded all moist plots. Native ants slowed the spread of Argentine ants into irrigated plots but did not prevent invasion. In areas without Argentine ants, native ant species showed variable responses to irrigation. At the landscape scale, Argentine ant occurrence was positively correlated with minimum winter temperature (but not precipitation), whereas native ant diversity increased with precipitation and was negatively correlated with minimum winter temperature. These results are of interest for several reasons. First, they demonstrate that fine-scale differences in the physical environment can eclipse biotic resistance from native competitors in determining community susceptibility to invasion. Second, our results illustrate surprising complexities with respect to how the abiotic factors limiting invasion can change with spatial scale, and third, how native and invasive species can differ in their responses to the physical environment. Idiosyncratic and scale-dependent processes complicate attempts to forecast where introduced species will occur and how their range limits may shift as a result of climate change.     

Matching spatial distributions of the sea star Echinaster sepositus and crustose coralline algae in shallow rocky Mediterranean communities

Understanding why a species is present in a particular location and the consequences of its presence is complex but necessary to identify the mechanisms that generate and maintain ecological diversity. The common sea star Echinaster sepositus can be either very abundant or non-existing in nearby localities of the western Mediterranean. Yet, the factors that shape its distribution and the impact of the sea star on natural communities remain uninvestigated. Here, we quantified multiple biotic and abiotic factors that may affect the distribution of E. sepositus and tested whether this sea star can shape the organization of the community it inhabits. Our results showed that the distribution of this sea star was highly contagious and positively correlated with the abundance and distribution of crustose coralline algae from tens of meters to tens of kilometers. Despite significant differences in community composition between localities with high or low abundance of the sea star, experimental addition of E. sepositus to natural communities failed to shift the composition of the algal community in 4 months. Overall, our results suggest that within habitat variability in the abundance of crustose coralline algae may explain the abundance of E. sepositus at multiple geographic scales, emphasizing the need to investigate small-scale processes at larger geographic scales.     

Climate, habitat, and species interactions at different scales determine the structure of a Neotropical bat community

Climate, habitat, and species interactions are factors that control community properties (e.g., species richness, abundance) across various spatial scales. Usually, researchers study how a few properties are affected by one factor in isolation and at one scale. Hence, there are few multi-scale studies testing how multiple controlling factors simultaneously affect community properties at different scales. We ask whether climate, habitat structure, or insect resources at each of three spatial scales explains most of the variation in six community properties and which theory best explains the distribution of selected community properties across a rainfall gradient. We studied a Neotropical insectivorous bat ensemble in the Isthmus of Panama with acoustic monitoring techniques. Using climatological data, habitat surveys, and insect captures in a hierarchical sampling design we determined how much variation of the community properties was explained by the three factors employing two approaches for variance partitioning. Our results revealed that most of the variation in species richness, total abundance, and feeding activity occurred at the smallest spatial scale and was explained by habitat structure. In contrast, climate at large scales explained most of the variation in individual species' abundances. Although each species had an idiosyncratic response to the gradient, species richness peaked at intermediate levels of precipitation, whereas total abundance was very similar across sites, suggesting density compensation. All community properties responded in a different manner to the factor and scale under consideration.     

Scaling range sizes to threats for robust predictions of risks to biodiversity

Assessments of risk to biodiversity often rely on spatial distributions of species and ecosystems. Range‐size metrics used extensively in these assessments, such as area of occupancy (AOO), are sensitive to measurement scale, prompting proposals to measure them at finer scales or at different scales based on the shape of the distribution or ecological characteristics of the biota. Despite its dominant role in red‐list assessments for decades, appropriate spatial scales of AOO for predicting risks of species’ extinction or ecosystem collapse remain untested and contentious. There are no quantitative evaluations of the scale‐sensitivity of AOO as a predictor of risks, the relationship between optimal AOO scale and threat scale, or the effect of grid uncertainty. We used stochastic simulation models to explore risks to ecosystems and species with clustered, dispersed, and linear distribution patterns subject to regimes of threat events with different frequency and spatial extent. Area of occupancy was an accurate predictor of risk (0.81<|r|<0.98) and performed optimally when measured with grid cells 0.1–1.0 times the largest plausible area threatened by an event. Contrary to previous assertions, estimates of AOO at these relatively coarse scales were better predictors of risk than finer‐scale estimates of AOO (e.g., when measurement cells are <1% of the area of the largest threat). The optimal scale depended on the spatial scales of threats more than the shape or size of biotic distributions. Although we found appreciable potential for grid‐measurement errors, current IUCN guidelines for estimating AOO neutralize geometric uncertainty and incorporate effective scaling procedures for assessing risks posed by landscape‐scale threats to species and ecosystems.     

Defining ecologically relevant scales for spatial protection with long‐term data on an endangered seabird and local prey availability

Human activities are important drivers of marine ecosystem functioning. However, separating the synergistic effects of fishing and environmental variability on the prey base of nontarget predators is difficult, often because prey availability estimates on appropriate scales are lacking. Understanding how prey abundance at different spatial scales links to population change can help integrate the needs of nontarget predators into fisheries management by defining ecologically relevant areas for spatial protection. We investigated the local population response (number of breeders) of the Bank Cormorant (Phalacrocorax neglectus), a range‐restricted endangered seabird, to the availability of its prey, the heavily fished west coast rock lobster (Jasus lalandii). Using Bayesian state‐space modeled cormorant counts at 3 colonies, 22 years of fisheries‐independent data on local lobster abundance, and generalized additive modeling, we determined the spatial scale pertinent to these relationships in areas with different lobster availability. Cormorant numbers responded positively to lobster availability in the regions with intermediate and high abundance but not where regime shifts and fishing pressure had depleted lobster stocks. The relationships were strongest when lobsters 20–30 km offshore of the colony were considered, a distance greater than the Bank Cormorant's foraging range when breeding, and may have been influenced by prey availability for nonbreeding birds, prey switching, or prey ecology. Our results highlight the importance of considering the scale of ecological relationships in marine spatial planning and suggest that designing spatial protection around focal species can benefit marine predators across their full life cycle. We propose the precautionary implementation of small‐scale marine protected areas, followed by robust assessment and adaptive‐management, to confirm population‐level benefits for the cormorants, their prey, and the wider ecosystem, without negative impacts on local fisheries.     

Use of Community‐Composition Data to Predict the Fecundity and Abundance of Species

Abstract: Species distribution models are critical tools for the prediction of invasive species spread and conservation of biodiversity. The majority of species distribution models have been built with environmental data. Community ecology theory suggests that species co‐occurrence data could also be used to predict current and potential distributions of species. Species assemblages are the products of biotic and environmental constraints on the distribution of individual species and as a result may contain valuable information for niche modeling. We compared the predictive ability of distribution models of annual grassland plants derived from either environmental or community‐composition data. Composition‐based models were built with the presence or absence of species at a site as predictors of site quality, whereas environment‐based models were built with soil chemistry, moisture content, above‐ground biomass, and solar radiation as predictors. The reproductive output of experimentally seeded individuals of 4 species and the abundance of 100 species were used to evaluate the resulting models. Community‐composition data were the best predictors of both the site‐specific reproductive output of sown individuals and the site‐specific abundance of existing populations. Successful community‐based models were robust to omission of data on the occurrence of rare species, which suggests that even very basic survey data on the occurrence of common species may be adequate for generating such models. Our results highlight the need for increased public availability of ecological survey data to facilitate community‐based modeling at scales relevant to conservation.     

Patterns of distribution and composition of sea urchin assemblages on Brazilian subtropical rocky reefs

Sea urchins are a key group of herbivores in both temperate and tropical food webs because they control macroalgal cover, and consequently influence primary productivity and phase shifts on reefs. Despite being abundant on southwestern Atlantic reefs, sea urchin distributions, and their association with abiotic and biotic variables, are poorly known. In this study, sea urchin assemblages were surveyed in 2011 at multiple depths at eight sites in Arraial do Cabo (Brazil, 22°57′S/41°01′W), with sites split between a colder, more wave-exposed location, and a warmer, more sheltered location. The influence of this large-scale physical gradient, along with changes in depth and substrate complexity, on sea urchin densities was then investigated. Predator biomass was low and did not vary significantly among sites. Among the seven species recorded, Paracentrotus gaimardi, Echinometra lucunter and Arbacia lixula were dominant. Linear mixed-effects models indicated that location was important, with mid-sized P. gaimardi individuals and A. lixula more common at cooler, exposed sites and E. lucunter more abundant at warmer, sheltered sites. Sea urchin densities typically decreased with increasing depth, probably caused by changes in factors such as light, wave exposure, and sedimentation. Substrate complexity had a positive effect on the abundance of all species, presumably because of the increased availability of refuges. Physical gradients have important consequences for urchin distributions and their ecological functions at relatively small spatial scales on these reefs, and should be incorporated into herbivore monitoring programmes. Research is also required to examine how differential sea urchin distributions affect benthic dynamics.     

Paleobiology, community ecology, and scales of ecological pattern

The fossil record provides a wealth of data on the role of regional processes and historical events in shaping biological communities over a variety of time scales. The Quaternary record with its evidence of repeated climatic change shows that both terrestrial and marine species shifted independently rather than as cohesive assemblages over scales of thousands of years. Larger scale patterns also show a strong individualistic component to taxon dynamics; assemblage stability, when it occurs, is difficult to separate from shared responses to low rates of environmental change. Nevertheless, the fossil record does suggest that some biotic interactions influence large-scale ecological and evolutionary patterns, albeit in more diffuse and protracted fashions than those generally studied by community ecologists. These include: (1) the resistance by incumbents to the establishment of new or invading taxa, with episodes of explosive diversification often appearing contingent on the removal of incumbents at extinction events; (2) steady states of within-habitat and global diversity at longer time scales (10(7)-l0(8) yr), despite enormous turnover of taxa; and (3) morphological and biogeographic responses to increased intensities of predation and substratum disturbance over similarly long time scales. The behavior of species and communities over the array of temporal and spatial scales in the fossil record takes on additional significance for framing conservation strategies, and for understanding recovery of species, lineages, and communities from environmental changes.     

The influence of spatial and size scale on phylogenetic relatedness in tropical forest communities

The relative importance of biotic, abiotic, and stochastic processes in structuring ecological communities continues to be a central focus in community ecology. In order to assess the role of phylogenetic relatedness on the nature of biodiversity we first quantified the degree of phylogenetic niche conservatism of several plant traits linked to plant form and function. Next we quantified the degree of phylogenetic relatedness across two fundamental scaling dimensions: plant size and neighborhood size. The results show that phylogenetic niche conservatism is likely widespread, indicating that closely related species are more functionally similar than distantly related species. Utilizing this information we show that three of five tropical forest dynamics plots (FDPs) exhibit similar scale-dependent patterns of phylogenetic structuring using only a spatial scaling axis. When spatial- and size-scaling axes were analyzed in concert, phylogenetic overdispersion of co-occurring species was most important at small spatial scales and in four of five FDPs for the largest size class. These results suggest that phylogenetic relatedness is increasingly important: (1) at small spatial scales, where phylogenetic overdispersion is more common, and (2) in large size classes, where phylogenetic overdispersion becomes more common throughout ontogeny. Collectively, our results highlight the critical spatial and size scales at which the degree of phylogenetic relatedness between constituent species influences the structuring of tropical forest diversity.     

Small-scale grassland assembly patterns differ above and below the soil surface

The existence of deterministic assembly rules for plant communities remains an important and unresolved topic in ecology. Most studies examining community assembly have sampled aboveground species diversity and composition. However, plants also coexist belowground, and many coexistence theories invoke belowground competition as an explanation for aboveground patterns. We used next-generation sequencing that enables the identification of roots and rhizomes from mixed-species samples to measure coexisting species at small scales in temperate grasslands. We used comparable data from above (conventional methods) and below (molecular techniques) the soil surface (0.1 x 0.1 x 0.1 m volume). To detect evidence for nonrandom patterns in the direction of biotic or abiotic assembly processes, we used three assembly rules tests (richness variance, guild proportionality, and species co-occurrence indices) as well as pairwise association tests. We found support for biotic assembly rules aboveground, with lower variance in species richness than expected and more negative species associations. Belowground plant communities were structured more by abiotic processes, with greater variability in richness and guild proportionality than expected. Belowground assembly is largely driven by abiotic processes, with little evidence for competition-driven assembly, and this has implications for plant coexistence theories that are based on competition for soil resources.     

Multi-scale marine biodiversity patterns inferred efficiently from habitat image processing

Cost-effective proxies of biodiversity and species abundance, applicable across a range of spatial scales, are needed for setting conservation priorities and planning action. We outline a rapid, efficient, and low-cost measure of spectral signal from digital habitat images that, being an effective proxy for habitat complexity, correlates with species diversity and requires little image processing or interpretation. We validated this method for coral reefs of the Great Barrier Reef (GBR), Australia, across a range of spatial scales (1 m to 10 km), using digital photographs of benthic communities at the transect scale and high-resolution Landsat satellite images at the reef scale. We calculated an index of image-derived spatial heterogeneity, the mean information gain (MIG), for each scale and related it to univariate (species richness and total abundance summed across species) and multivariate (species abundance matrix) measures of fish community structure, using two techniques that account for the hierarchical structure of the data: hierarchical (mixed-effect) linear models and distance-based partial redundancy analysis. Over the length and breadth of the GBR, MIG alone explained up to 29% of deviance in fish species richness, 33% in total fish abundance, and 25% in fish community structure at multiple scales, thus demonstrating the possibility of easily and rapidly exploiting spatial information contained in digital images to complement existing methods for inferring diversity and abundance patterns among fish communities. Thus, the spectral signal of unprocessed remotely sensed images provides an efficient and low-cost way to optimize the design of surveys used in conservation planning. In data-sparse situations, this simple approach also offers a viable method for rapid assessment of potential local biodiversity, particularly where there is little local capacity in terms of skills or resources for mounting in-depth biodiversity surveys.     

Composite forces shape population dynamics of copepod crustaceans

Understanding the processes that control species abundance and distribution is a major challenge in ecology, yet for a large number of potentially important organisms, we know little about the biotic and abiotic factors that influence population size. One group of aquatic organisms that defies traditional demographic analyses is the Crustacea, particularly those with complex life cycles. We used likelihood techniques and information theoretics to evaluate a suite of models representing alternative hypotheses on factors controlling the abundance of two copepod crustaceans in a small, tropical floodplain lake. Quantitative zooplankton samples were collected at three stations in a Venezuelan floodplain lake from June through December 1984; the average sampling interval was two days. We constructed a series of models with stage structure that incorporated six biotic and abiotic covariates in various combinations to account for temporal changes in abundance of these target species and in their population growth rates. Our analysis produced several novel insights into copepod population dynamics. We found that multiple forces affected the abundance of particular stages, that these factors differed between species as well as among stages within each species, and that biotic processes had the largest effects on copepod population dynamics. Density dependence had a large effect on the survival of Oithona amazonica copepodites and on population growth rate of Diaptomus negrensis.     

Scale-dependent relations in land cover biophysical dynamics

The exploration of the relationships between plant biotic dynamics and scale can reveal important information on ecosystem spatial organization by addressing preservation of information integrity in upscaling/downscaling procedures of land-surface parameterization for environmental modeling applications. Scale-dependent relations of vegetation dynamics are investigated in this study by using emergent biophysical characteristics obtained through a predictive multidimensional model of vegetation anomalies derived from remote-sensing observations. In particular, the analysis is focused on the spatial organization of some phenological parameters including deterministic variations (seasonal range, interannual variability, jump discontinuities) and stochastic components (plant memory, spatial correlations). The analysis is performed using MODIS-based Normalized Difference Vegetation Index (NDVI) 16-day composites for the period from March 2000 to December 2006 over Italy at different levels of spatial aggregation (1-8 km). Scale-dependences of the statistical moments of the phenological parameters are quantified through simple power laws for five distinct vegetated land covers. Results suggest that some biophysical characteristics, especially deterministic components, show no preferential spatial scale for important coverage. In particular, broad-leaved forests and natural grasslands are characterized by deterministic and low-distance spatial components well explained by scale relationships, which are modulated by possible spatiotemporal dynamics of climatic drivers. Agricultural lands show high scale-dependent relations on short-term biophysical memory sources and low-distance spatial components of phenology likely related to hierarchical interactions of anthropogenic and ecological processes; whereas mixed patterns of croplands and natural areas generally present no consistent scaling relations.     

Linking chronic wasting disease to mule deer movement scales: a hierarchical Bayesian approach.

Observed spatial patterns in natural systems may result from processes acting across multiple spatial and temporal scales. Although spatially explicit data on processes that generate ecological patterns, such as the distribution of disease over a landscape, are frequently unavailable, information about the scales over which processes operate can be used to understand the link between pattern and process. Our goal was to identify scales of mule deer (Odocoileus hemionus) movement and mixing that exerted the greatest influence on the spatial pattern of chronic wasting disease (CWD) in northcentral Colorado, USA. We hypothesized that three scales of mixing (individual, winter subpopulation, or summer subpopulation) might control spatial variation in disease prevalence. We developed a fully Bayesian hierarchical model to compare the strength of evidence for each mixing scale. We found strong evidence that the finest mixing scale corresponded best to the spatial distribution of CWD infection. There was also evidence that land ownership and habitat use play a role in exacerbating the disease, along with the known effects of sex and age. Our analysis demonstrates how information on the scales of spatial processes that generate observed patterns can be used to gain insight when process data are sparse or unavailable.