SEARCH · Geology Reports

Results for “Landscape Ecology”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 343 records · Page 19Linked to original sources

USGS2026

Vulnerability of different Colorado Plateau land types to drivers of change

Public lands are challenged by a range of pressures—changing climate, increasing visitation, resource extraction—and their effects can span spatial scales, often crossing land management jurisdictional boundaries. Research approaches which explicitly span jurisdictions can support strategies to contend with regional pressures. We assess management-relevant drivers of change—aridification, livestock grazing, invasive species, surface disturbance, and fire—across a patchwork of land management units and agencies on the Colorado Plateau, focusing on southeastern Utah, USA. We use vulnerability analysis, first evaluating exposure to drivers across the landscape, then quantifying sensitivity to each driver across different land types, defined by mapped Ecological Site Groups, a system for classifying landscapes according to physical factors including climate, soils, and topographic setting. We address the questions: 1) how are drivers spatially distributed across the study region; and, 2) based on exposure and sensitivity, are certain land types more vulnerable to these drivers? We find that the study region has high exposure and sensitivity—and thus high vulnerability—to aridification and grazing, but low exposure and vulnerability to other drivers. Although more sensitive land types were not generally more exposed, identifying which areas are most sensitive can guide adaptive measures, like where new uses or disturbances would be least harmful and which areas could be prioritized for restoration. The method we demonstrate is a flexible tool for assessing landscape-scale impacts, is built on nationally available datasets, and can be tailored to different datasets and sensitivity metrics.

Utah↗

USGS2018

A social–ecological perspective for riverscape management in the Columbia River Basin

Riverscapes are complex, landscape-scale mosaics of connected river and stream habitats embedded in diverse ecological and socioeconomic settings. Social–ecological interactions among stakeholders often complicate natural-resource conservation and management of riverscapes. The management challenges posed by the conservation and restoration of wild salmonid populations in the Columbia River Basin (CRB) of western North America are one such example. Because of their ecological, cultural, and socioeconomic importance, salmonids present a complex management landscape due to interacting environmental factors (eg climate change, invasive species) as well as socioeconomic and political factors (eg dams, hatcheries, land-use change, transboundary agreements). Many of the problems in the CRB can be linked to social–ecological interactions occurring within integrated ecological, human–social, and regional–climatic spheres. Future management and conservation of salmonid populations therefore depends on how well the issues are understood and whether they can be resolved through effective communication and collaboration among ecologists, social scientists, stakeholders, and policy makers.

Columbia River Basin↗

USGS2012

A tale of two land uses in the American West: rural residential growth and energy development

This paper describes a spatiotemporal land use map for a rural county in the western United States. Sublette County, Wyoming has undergone recent land use change in the form of heightened rural residential development on private land and increased energy development on both public and private land. In this study we integrate energy production data, population census data, ownership parcel data, and a series of Landsat Thematic Mapper and Enhanced Thematic Mapper scenes (over a 25-year period) to create a map that illustrates the changing landscape. Spatial change on the landscape is mapped at 30 square meters, congruent with a Landsat pixel. Sublette County has a wealth of wildlife and associated habitat which is affected by both types of growth. While we do not attempt to quantify the effect of disturbance on wildlife species, we believe our results can provide important baseline data that can be incorporated into land use planning and ecological-wildlife research at the landscape scale.

Journal of Maps↗

USGS1998

Evaluating landscape health: Integrating societal goals and biophysical process

Evaluating landscape change requires the integration of the social and natural sciences. The social sciences contribute to articulating societal values that govern landscape change, while the natural sciences contribute to understanding the biophysical processes that are influenced by human activity and result in ecological change. Building upon Aldo Leopold's criteria for landscape health, the roles of societal values and biophysical processes in shaping the landscape are explored. A framework is developed for indicators of landscape health and integrity. Indicators of integrity are useful in measuring biological condition relative to the condition in landscapes largely unaffected by human activity, while indicators of health are useful in evaluating changes in highly modified landscapes. Integrating societal goals and biophysical processes requires identification of ecological services to be sustained within a given landscape. It also requires the proper choice of temporal and spatial scales. Societal values are based upon inter-generational concerns at regional scales (e.g. soil and ground water quality). Assessing the health and integrity of the environment at the landscape scale over a period of decades best integrates societal values with underlying biophysical processes. These principles are illustrated in two contrasting case studies: (1) the South Platte River study demonstrates the role of complex biophysical processes acting at a distance; and (2) the Kissimmee River study illustrates the critical importance of social, cultural and economic concerns in the design of remedial action plans. In both studies, however, interactions between the social and the biophysical governed the landscape outcomes. The legacy of evolution and the legacy of culture requires integration for the purpose of effectively coping with environmental change.

Journal of Environmental Management↗

USGS2009

Short- and long-term implications of clearcut and two-age silviculture for conservation of breeding forest birds in the central Appalachians, USA

Two-age (deferment or leave tree) harvesting is used increasingly in even-aged forest management, but long-term responses of breeding avifauna to retention of residual canopy trees have not been investigated. Breeding bird surveys completed in 1994-1996 in two-age and clearcut harvests in the central Appalachian Mountains of West Virginia, USA allowed us to document long-term changes in these stands. In 2005 and 2006, we conducted point counts in mature unharvested forest stands and in 19-26 year-old clearcut and two-age harvests from the original study and in younger clearcut and two-age stands (6-10 years old). We found differences in breeding bird metrics among these five treatments and temporal differences in the original stands. Although early-successional species are typically absent from group selection cuts, they were almost as common in young two-age stands as clearcuts, supporting two-age harvests as an alternative to clearcutting. Although older harvests had lower species richness and diversity, they were beginning to provide habitat for some species of late-successional forest songbirds that were absent or uncommon in young harvests. Overall, late-successional forest-interior species were more flexible in their use of different seral stages; several species used both age classes and harvest types in addition to mature forest, which may reflect the lack of edges in our heavily-forested landscape. Consequently, two-age management provides habitat for a diverse group of species as these stands mature and may be an ecologically sustainable alternative to clearcutting in landscapes where brown-headed cowbirds (Molothrus ater) are uncommon. ?? 2008 Elsevier Ltd.

Biological Conservation↗

USGS2021

Using landscape metrics to characterize towns along an urban-rural gradient

Context Urban-rural gradients are useful tools when examining the influence of human disturbances on ecological, social and coupled systems, yet the most commonly used gradient definitions are based on single broad measures such as housing density or percent forest cover that fail to capture landscape patterns important for conservation. Objectives We present an approach to defining urban–rural gradients that integrates multiple landscape pattern metrics related to ecosystem processes important for natural resources and wildlife sustainability. Methods We develop a set of land cover composition and configuration metrics and then use them as inputs to a cluster analysis process that, in addition to grouping towns with similar attributes, identifies exemplar towns for each group. We compare the outcome of the cluster-based urban-rural gradient typology to outcomes for four commonly-used rule-based typologies and discuss implications for resource management and conservation. Results The resulting cluster-based typology defines five town types (urban, suburban, exurban, rural, and agricultural) and notably identifies a bifurcation along the gradient distinguishing among rural forested and agricultural towns. Landscape patterns (e.g., core and islet forests) influence where individual towns fall along the gradient. Designations of town type differ substantially among the five different typologies, particularly along the middle of the gradient. Conclusions Understanding where a town occurs along the urban-rural gradient could aid local decision-makers in prioritizing and balancing between development and conservation scenarios. Variations in outcomes among the different urban-rural gradient typologies raise concerns that broad-measure classifications do not adequately account for important landscape patterns. We suggest future urban-rural gradient studies utilize more robust classification approaches.

Connecticut. Maine, Massachusetts, New Hampshire, ↗

USGS2022

Agricultural land use shapes dispersal in white-tailed deer (Odocoileus virginianus)

Background Dispersal is a fundamental process to animal population dynamics and gene flow. In white-tailed deer (WTD; Odocoileus virginianus ), dispersal also presents an increasingly relevant risk for the spread of infectious diseases. Across their wide range, WTD dispersal is believed to be driven by a suite of landscape and host behavioral factors, but these can vary by region, season, and sex. Our objectives were to (1) identify dispersal events in Wisconsin WTD and determine drivers of dispersal rates and distances, and (2) determine how landscape features (e.g., rivers, roads) structure deer dispersal paths. Methods We developed an algorithmic approach to detect dispersal events from GPS collar data for 590 juvenile, yearling, and adult WTD. We used statistical models to identify host and landscape drivers of dispersal rates and distances, including the role of agricultural land use, the traversability of the landscape, and potential interactions between deer. We then performed a step selection analysis to determine how landscape features such as agricultural land use, elevation, rivers, and roads affected deer dispersal paths. Results Dispersal predominantly occurred in juvenile males, of which 64.2% dispersed, with dispersal events uncommon in other sex and age classes. Juvenile male dispersal probability was positively associated with the proportion of the natal range that was classified as agricultural land use, but only during the spring. Dispersal distances were typically short (median 5.77 km, range: 1.3–68.3 km), especially in the fall. Further, dispersal distances were positively associated with agricultural land use in potential dispersal paths but negatively associated with the number of proximate deer in the natal range. Lastly, we found that, during dispersal, juvenile males typically avoided agricultural land use but selected for areas near rivers and streams. Conclusion Land use—particularly agricultural—was a key driver of dispersal rates, distances, and paths in Wisconsin WTD. In addition, our results support the importance of deer social environments in shaping dispersal behavior. Our findings reinforce knowledge of dispersal ecology in WTD and how landscape factors—including major rivers, roads, and land-use patterns—structure host gene flow and potential pathogen transmission.

Wisconsin↗

USGS2018

Fear of feces? Trade-offs between disease risk and foraging drive animal activity around raccoon latrines

Fear of predation alters prey behavior, which can indirectly alter entire landscapes. A parasite-induced ecology of fear might also exist if animals avoid parasite-contaminated resources when infection costs outweigh foraging benefits. To investigate whether animals avoid parasite contaminated sites, and if such avoidance balances disease costs and foraging gains, we monitored animal behavior at raccoon latrines – sites that concentrate both seeds and pathogenic parasite eggs. Using wildlife cameras, we documented over 40 potentially susceptible vertebrate species in latrines and adjacent habitat. Latrine contact rates reflected background activity, diet preferences and disease risk. Disease-tolerant raccoons and rats displayed significant site attraction, while susceptible birds and small mammals avoided these high-risk sites. This suggests that parasites, like predators, might create a landscape of fear for vulnerable hosts. Such non-consumptive parasite effects could alter disease transmission, population dynamics, and even ecosystem structure.

California↗

USGS2007

Monitoring boreal forest leaf area index across a Siberian burn chronosequence: A MODIS validation study

Landscapes containing differing amounts of ecological disturbance provide an excellent opportunity to validate and better understand the emerging Moderate Resolution Imaging Spectrometer (MODIS) vegetation products. Four sites, including 1‐year post‐fire coniferous, 13‐year post‐fire deciduous, 24‐year post‐fire deciduous, and >100 year old post‐fire coniferous forests, were selected to serve as a post‐fire chronosequence in the central Siberian region of Krasnoyarsk (57.3°N, 91.6°E) with which to study the MODIS leaf area index (LAI) and vegetation index (VI) products. The collection 4 MODIS LAI product correctly represented the summer site phenologies, but significantly underestimated the LAI value of the >100 year old coniferous forest during the November to April time period. Landsat 7‐derived enhanced vegetation index (EVI) performed better than normalized difference vegetation index (NDVI) to separate the deciduous and conifer forests, and both indices contained significant correlation with field‐derived LAI values at coniferous forest sites ( r 2 = 0.61 and r 2 = 0.69, respectively). The reduced simple ratio (RSR) markedly improved LAI prediction from satellite measurements ( r 2 = 0.89) relative to NDVI and EVI. LAI estimates derived from ETM+ images were scaled up to evaluate the 1 km resolution MODIS LAI product; from this analysis MODIS LAI overestimated values in the low LAI deciduous forests (where LAI<5) and underestimated values in the high LAI conifer forests (where LAI>6). Our results indicate that further research on the MODIS LAI product is warranted to better understand and improve remote LAI quantification in disturbed forest landscapes over the course of the year.

Krasnoyarsk Kray↗

USGS2019

A multi-indicator spatial similarity approach for evaluating ecological restoration scenarios

Context The greater Everglades region in Florida (USA) is an area of wetlands that has been altered and reduced to 50% of its original area and faces multiple threats. Spatial landscape analysis can help guide a large and complex ecosystem restoration process, involving billions of dollars and multiple groups of stakeholders. Objectives To guide Everglades restoration efforts, we evaluated ecological performance of different hydrologic restoration scenarios using a novel technique, the structural similarity index (SSIM), which quantitatively compares similarity between pairs of gridded maps in terms of mean, variance, and covariance. Methods Using the SSIM, we evaluated system-wide performance of apple snails, American alligators, Great egrets, and long- and short-hydroperiod vegetation types under multiple restoration scenarios that varied in water management strategies, amounts of water storage, removal of levees and canals (decompartmentalization), and seepage control barriers. We then compared species and habitat responses under each restoration scenario to a target scenario simulating the historical, natural system. Results The SSIM approach provides a reliable means of scenario comparison, accounting for both the local magnitude and spatial structure of the underlying data. Our results demonstrated that decompartmentalization benefits the indicator species. In general, scenarios with increased water storage were closer to the target scenario. Conclusions This spatial comparison technique is useful for evaluating restoration efforts at multiple spatial scales, ranging from the entire ecosystem down to individual compartments or sub-compartments. The results can be used to inform management and restoration efforts and to guide policy for the greater Everglades area.

Florida↗

USGS2018

Impacts of temporal revisit designs on the power to detect trend with a linear mixed model: An application to long-term monitoring of Sierra Nevada lakes

Long-term ecological monitoring programs often use linear mixed models to estimate trend in an ecological indicator sampled across large landscapes. A linear mixed model is versatile for estimating a linear trend in time as well as components of spatial and temporal variationin the case of unbalanced data structures , which are common in complex monitoring designs where limited sampling effort must be optimized over time and space. A power analysis was used to inform a lake chemistry monitoring design, including selecting the most appropriate temporal revisit design. Pilot data from surveys of lakes across large wilderness national parks (Sequoia, Kings Canyon, and Yosemite national parks) were used to obtain variance components for a Monte Carlo power simulation. Using a linear mixed model for a range of temporal revisit designs, sample sizes, and trend magnitudes, we evaluated the power to detect trend, the trend test size, and the relative bias of trend coefficient estimates for four continuous and normally distributed indicators. Contrary to prior research based on large-sample approximations that identified a single panel of sites visited annually as the revisit design generating the highest power, we found that the power to detect a 12-year trend based on the Wald t-test from a linear mixed model may be optimized by obtaining unbalanced data sets with limited to no annual replication. We emphasize the importance of examining variance composition, sample size, and the power and size of the trend test with Monte Carlo simulation when allocating sampling effort over time and space.

Ecological Indicators↗

USGS2019

Spatially-structured statistical network models for landscape genetics

A basic understanding of how the landscape impedes, or creates resistance to, the dispersal of organisms and hence gene flow is paramount for successful conservation science and management. Spatially structured ecological networks are often used to represent spatial landscape‐genetic relationships, where nodes represent individuals or populations and resistance to movement is represented using non‐binary edge weights. Weights are typically assigned or estimated by the user, rather than observed, and validating such weights is challenging. We provide a synthesis of current methods used to estimate edge weights and an overview of common model types, stressing the advantages and disadvantages of each approach and their ability to model landscape‐genetic data. We further explore a set of spatial‐statistical methods that provide ecologists with alternative approaches for modeling spatially explicit processes that may affect genetic structure. This includes an overview of spatial autoregressive models, with a particular focus on how correlation and partial correlation are used to represent neighborhood structure with the inverse of the covariance matrix (i.e., precision matrix). We then demonstrate how to model resistance by specifying an appropriate statistical model on the nodes, conditioned on the edge weights, through the precision matrix. This integration of network ecology and spatial statistics provides a practical analytical framework for landscape‐genetic studies. The results can be used to make statistical inferences about the relative importance of individual landscape characteristics, such as the vegetative cover, hillslope, or the presence of roads or rivers, on gene flow. In addition, the R code we include allows readers to explore landscape‐genetic structure in their own datasets, which will potentially provide new insights into the evolutionary processes that generated ecological networks, as well as valuable information about the optimal characteristics of conservation corridors.

Ecological Monographs↗

USGS2007

Comparative performance of invasive and native Celastrus species across environmental gradients

The ability to understand and predict the success of invasive plant species in their new ranges is increased when there is a sympatric native congener available for comparison. Celastrus orbiculatus (oriental bittersweet) is a liana introduced into the United States in the mid-1800s from East Asia as an ornamental plant. Its native congener, Celastrus scandens (American bittersweet), ranges from the east coast of the United States as far west as Wyoming. In the Northeastern United States, C. orbiculatus is continuing to expand its range while C. scandens appears to be in serious decline. One hypothesis for this decline is that C. scandens does not have such a wide range of ecological tolerances in the current landscape as C. orbiculatus, which seems to tolerate a greater range of resource conditions. To investigate this hypothesis, we transplanted these two species into ten sites that spanned a full range of light and soil moisture conditions to compare their establishment and performance in terms of aboveground growth (biomass and height) and mortality. After two years, C. orbiculatus showed significantly lower mortality and greater biomass across all resource conditions compared to C. scandens. In addition, C. orbiculatus preferred more mesic soil moisture conditions, while C. scandens performed better in drier soil moisture conditions. Since much of the Northeastern United States is now forested, this preference for mesic soil conditions could make it more successful than C. scandens in the region. This study shows the utility of manipulative experiments, particularly those using congeneric native species as benchmarks, for assessing the causes and predicting the course of invasions. ?? 2007 Springer-Verlag.

Oecologia↗

USGS2014

Moving beyond too little, too late: managing emerging infectious diseases in wild populations requires international policy and partnerships

Emerging infectious diseases (EIDs) are on the rise due to multiple factors, including human facilitated movement of pathogens, broad-scale landscape changes, and perturbations to ecological systems (Jones et al. 2008; Fisher et al. 2012). Epidemics in wildlife are problematic because they can lead to pathogen spillover to new host organisms, erode biodiversity and threaten ecosystems that sustain human societies (Fisher et al. 2012; Kilpatrick 2011). There have been recent calls for large-scale research approaches to combat threats EIDs pose to wildlife (Sleeman 2013). While it is true that developing new analytical models, diagnostic assays and molecular tools will significantly avance outr abilities to respond to disease threats, we also propose that addressing difficult problems in EIDs will require considerable shofts in international health policy and infrastructure. While there are currently international organizations responsbile for rapidly initiating and coordinating preventative measures to control infectious diseases in human, livestock, and arable systems, there are few comparable instiutions that have the authority to implement transnational responses to EIDs in wildlife. This absence of well-developed infastructure hampers the rapid responses necessary to mitigate international spread of EIDs.

EcoHealth↗

USGS2018

Submerged aquatic vegetation mapping in coastal Louisiana through development of a spatial likelihood occurrence (SLOO) model

Determining the spatial distribution of coastal foundation species is essential to accurately determine restoration goals, predict the ecological effects of climate change, and develop habitat management strategies. Mapping the distribution of submerged aquatic vegetation (SAV) species assemblages, which provide important habitat resource and ecological services in Louisiana, has been difficult due to the dynamic nature of SAV occurrence and the limited water clarity across much of the coast. Species distribution models (SDMs) link ecological conditions species occurrence across landscapes, and can predict the distribution of species across un-sampled or hard to sample areas and support the development of habitat maps. To predict SAV distribution in coastal Louisiana, a SDM was developed and projected across the landscape to create a spatial likelihood of occurrence (SLOO) model describing the probability of SAV presence in aquatic habitats. SAV presence and absence data were examined from over 500 field observations in relation to physical and hydrologic variables, including exposure, turbidity, water level, and salinity. A binary logistic regression model (p < 0.0001) identified three significant predictors of SAV presence: mean winter salinity, exposure, and turbidity. As each of these variables increased, the probability of SAV presence in the summer growing season decreased. The spatial application of this SDM helps to predict the likelihood of occurrence across the coastal landscape, creating a valuable tool to describe un-sampled SAV habitat and estimate future changes in habitat availability.

Louisiana↗

USGS2023

Does post-fire recovery of native grasses across abiotic-stress and invasive-grass gradients match theoretical predictions, in sagebrush steppe?

Interactions among species can strongly affect how plant communities reassemble after disturbances, and variability among native and invasive species across environmental gradients must be known in order to manage plant-community recovery. The stress-gradient hypothesis (SGH) predicts species interactions will be more positive in abiotically stressful conditions and conversely, more negative in benign conditions, and the resistance-resilience concept (RRC) may predict where and when invasions will complicate ecosystem recovery. We evaluated how abiotic stress and biotic interactions determine native bunchgrass abundances across environmental gradients using additive models of cover data from over 500 plots re-measured annually for 5 years as they recovered naturally (untreated) after a megafire (>100,000 ha) in sagebrush steppe threated by the invasive-grass and fire cycle. The species included native bunchgrasses, bluebunch wheatgrass ( Pseudoroegneria spicata ) and Sandberg bluegrass ( Poa secunda ), and the exotic and invasive annual cheatgrass ( Bromus tectorum ). We asked whether associations between native bunchgrasses and cheatgrass were context dependent and if the SGH could help predict interspecific associations between species in a semiarid environment. The association of cover of each native bunchgrass to cheatgrass was not uniform, and instead varied from neutral to negative across environmental gradients in both space and time (i.e., weather), to which the species had nonlinear and sometimes threshold-like responses. Consistent with the SGH, bunchgrasses were generally more negatively related to cheatgrass (i.e., putative competition) in conditions which increased the cover of each bunchgrass – which were higher elevations and temperatures and lower solar heatload, and, for Sandberg bluegrass, drier conditions. There were few indications of positive interactions (i.e., putative facilitation) in stressful conditions, and instead associations were again negative, albeit weaker, in some of the conditions evaluated. Synthesis . These findings demonstrate that the negative association among native bunchgrasses and cheatgrass is context dependent and is determined by the abundances of both interacting species which is driven by environmental stress. This led to a hypothesis that together Sandberg bluegrass and bluebunch wheatgrass provide complementary resistance to cheatgrass at the landscape level, despite their different ecology and contrary to the management preference for bluebunch wheatgrass. Sandberg bluegrass might be critical for providing resistance against cheatgrass where invasion potential is greatest, i.e., at lower elevations, where bluebunch wheatgrass is scarce.

Global Ecology and Conservation↗

USGS2014

Pluvial lakes in the Great Basin of the western United States: a view from the outcrop

Paleo-lakes in the western United States provide geomorphic and hydrologic records of climate and drainage-basin change at multiple time scales extending back to the Miocene. Recent reviews and studies of paleo-lake records have focused on interpretations of proxies in lake sediment cores from the northern and central parts of the Great Basin. In this review, emphasis is placed on equally important studies of lake history during the past ∼30 years that were derived from outcrop exposures and geomorphology, in some cases combined with cores. Outcrop and core records have different strengths and weaknesses that must be recognized and exploited in the interpretation of paleohydrology and paleoclimate. Outcrops and landforms can yield direct evidence of lake level, facies changes that record details of lake-level fluctuations, and geologic events such as catastrophic floods, drainage-basin changes, and isostatic rebound. Cores can potentially yield continuous records when sampled in stable parts of lake basins and can provide proxies for changes in lake level, water temperature and chemistry, and ecological conditions in the surrounding landscape. However, proxies such as stable isotopes may be influenced by several competing factors the relative effects of which may be difficult to assess, and interpretations may be confounded by geologic events within the drainage basin that were unrecorded or not recognized in a core. The best evidence for documenting absolute lake-level changes lies within the shore, nearshore, and deltaic sediments that were deposited across piedmonts and at the mouths of streams as lake level rose and fell. We review the different shorezone environments and resulting deposits used in such reconstructions and discuss potential estimation errors. Lake-level studies based on deposits and landforms have provided paleohydrologic records ranging from general changes during the past million years to centennial-scale details of fluctuations during the late Pleistocene and Holocene. Outcrop studies have documented the integration histories of several important drainage basins, including the Humboldt, Amargosa, Owens, and Mojave river systems, that have evolved since the Miocene within the active tectonic setting of the Great Basin; these histories have influenced lake levels in terminal basins. Many pre-late Pleistocene lakes in the western Great Basin were significantly larger and record wetter conditions than the youngest lakes. Outcrop-based lake-level data provide important checks on core-based proxy interpretations; we discuss four such comparisons. In some cases, such as for Lakes Owens and Manix, outcrop and core data synthesis yields stronger and more complete records; in other cases, such as for Bonneville and Lahontan, conflicts point toward reconsideration of confounding factors in interpretation of core-based proxies.

Great Basin↗

USGS2025

Idiosyncratic spatial scaling of biodiversity–disease relationships

High host biodiversity is hypothesized to dilute the risk of vector-borne diseases if many host species are ‘dead ends' that cannot effectively transmit the disease and low-diversity areas tend to be dominated by competent host species. However, many studies on biodiversity–disease relationships characterize host biodiversity at single, local spatial scales, which complicates efforts to forecast disease risk if associations between host biodiversity and disease change with spatial scale. Here, our objective is to evaluate the spatial scaling of relationships between host biodiversity and Borrelia (the bacterial taxon which causes Lyme disease) infection prevalence in small mammals. We compared the associations between infection prevalence and small mammal host diversity for local communities (individual plots) and metacommunities (multiple plots aggregated within a landscape) sampled by the National Ecological Observatory Network (NEON), an emerging continental-scale environmental monitoring program with a hierarchical sampling design. We applied a multispecies, spatially-stratified capture–recapture model to a trapping dataset to estimate five small mammal biodiversity metrics, which we used to predict infection status for a subset of trapped individuals. We found that relationships between Borrelia infection prevalence and biodiversity did indeed vary when biodiversity was quantified at different spatial scales but that these scaling behaviors were idiosyncratic among the five biodiversity metrics. For example, species richness of local communities showed a negative (dilution) effect on infection prevalence, while species richness of the small mammal metacommunity showed a positive (amplification) effect on infection prevalence. Our modeling approach can inform future analyses as data from similar monitoring programs accumulate and become increasingly available through time. Our results indicate that a focus on single spatial scales when assessing the influence of biodiversity on disease risk provides an incomplete picture of the complexity of disease dynamics in ecosystems.

Ecography↗