Idiosyncratic spatial scaling of biodiversity–disease relationships

Neil A. Gilbert; Graziella Vittoria DiRenzo; Elise Zipkin

doi:10.1111/ecog.07541

Home/Archive/USGS

USGS · 70269940

Idiosyncratic spatial scaling of biodiversity–disease relationships

Neil A. Gilbert·Graziella Vittoria DiRenzo·Elise Zipkin

View original source ↗Export metadata ↓

Abstract

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.

Explore related subjects

Ecography Article

Source-reported bounding extent: 24.871286670280753° to 49.09646929603289° latitude; -106.97439225502573° to -68.62754461055297° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Neil A. Gilbert, Graziella Vittoria DiRenzo, Elise Zipkin. 2025-02-10. Idiosyncratic spatial scaling of biodiversity–disease relationships. https://doi.org/10.1111/ecog.07541

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Microclimate mediates the strength and direction of avian biotic interactions

Theory predicts that that the strength and direction of species interactions can shift from being competitive in benign environments toward being facilitative in stressful environments. However, the environmental context dependency of species interactions has rarely been tested in animal communities. We capitalized on a 15-year, landscape-scale dataset, collected annually in a relatively stable old-growth forest environment to test the long-held hypothesis that the strength and direction of species interactions might be mediated by climatic conditions. It is generally accepted that competitive and facilitative interactions drive the distributions of many species. Using multi-species dynamic occupancy models applied to long-term data, we tested whether annual settlement by bird species could affect either the persistence or settlement by other phylogenetically related species, and whether these interactions are mediated by microclimate. We found that species interactions were influenced by microclimate for some, but not all avian species pairs. Related species pairs more often showed settlement dynamics that were indicative of attraction rather than repulsion. In some cases, competitive interactions at warmer microclimates flipped to become facilitative in colder ones. However, the reverse was also true: facilitative interactions amplified for some species under warm conditions. Furthermore, species pairs that were closely related were more likely to exhibit competitive relationships along at least part of the microclimatic gradient. Our results highlight the importance of using long-term data to incorporate competitive and facilitative interactions into species distribution models and support the notion that the strength and direction of species interactions can be dependent on microclimatic environmental conditions.

Oregon↗

USGS2026

Simulating past and future refugia for temperate trees in northern Italy

During the Quaternary, trees responded to the climatic changes of glacial–interglacial cycles with large-scale range shifts. Over cold glacials, temperate tree species contracted their ranges and survived in areas known as refugia. Several studies point to the Euganean Hills (Colli Euganei), in Veneto, northern Italy, as one of the northernmost European refugia of temperate tree species during the Last Glacial Maximum (LGM, ca 23 000–19 000 calibrated years BP). Using LandClim, a spatially explicit, dynamic forest landscape model, we demonstrate that climate conditions during the LGM likely allowed temperate tree species to persist in the Euganean Hills. The identified refugial locations lie at intermediate to high elevations and in sheltered valleys within the hilly complex. Therefore, the combined palaeoecological and modelling evidence suggests that today's temperate forests of the Euganean Hills have a full glacial legacy. Simulations under future climate conditions suggest a collapse of the sub-mediterranean and oro-mediterranean deciduous forests that are prevalent today and the expansion of thermo-mediterranean evergreen forests (with e.g. Quercus ilex , Q. suber , Olea europaea and Pinus sp.). Specifically, the extrazonal population of oro-mediterranean Fagus sylvatica , which is unique to the Po Plain and likely persisted locally through several glacial–interglacial cycles, is predicted to sharply decline and face local extinction, underscoring a conservation hazard.

Ecography↗

USGS2025

Quantifying landscape-level biodiversity change in an island ecosystem: A 50-year assessment of shifts in the Hawaiian avian community

Hawaii has experienced profound declines in native avifauna alongside the introduction of numerous bird species. While site-specific population studies are common, landscape-level analyses of avian population dynamics are rare, particularly in island ecosystems. To address this gap, we used a density surface model to create a spatio-temporal projection of population densities and distributions across the Island of Hawai‘i, spanning nearly five decades (1976–2023). We incorporated environmental covariates of habitat, precipitation, and elevation, to further refine our projections. Our analysis encompassed nine native and six non-native bird species, inhabiting a range of ecological niches. We found five out of nine native species have declined in density and range size while four were stable. For non-native species, two were stable, one was decreasing, and three were increasing in density and range size. Our landscape projections can inform management by suggesting areas critical for habitat preservation and land acquisition for conservation, identifying where range fragmentation is occurring, and pinpointing locations of multi-species declines that are likely driven by a common cause. Our study demonstrates how long-term, landscape-level monitoring and analyses can advance understanding and addressing biodiversity loss, particularly in vulnerable tropical island ecosystems.

Hawaii↗