The global wildland-urban interface.

The wildland-urban interface (WUI) is where buildings and wildland vegetation meet or intermingle1,2. It is where human-environmental conflicts and risks can be concentrated, including the loss of houses and lives to wildfire, habitat loss and fragmentation and the spread of zoonotic diseases3. However, a global analysis of the WUI has been lacking. Here, we present a global map of the 2020 WUI at 10 m resolution using a globally consistent and validated approach based on remote sensing-derived datasets of building area4 and wildland vegetation5. We show that the WUI is a global phenomenon, identify many previously undocumented WUI hotspots and highlight the wide range of population density, land cover types and biomass levels in different parts of the global WUI. The WUI covers only 4.7% of the land surface but is home to nearly half its population (3.5 billion). The WUI is especially widespread in Europe (15% of the land area) and the temperate broadleaf and mixed forests biome (18%). Of all people living near 2003-2020 wildfires (0.4 billion), two thirds have their home in the WUI, most of them in Africa (150 million). Given that wildfire activity is predicted to increase because of climate change in many regions6, there is a need to understand housing growth and vegetation patterns as drivers of WUI change.

Wildlife mortality risk posed by high and low traffic roads.

Wildlife mortality due to collisions with vehicles (roadkill) is one of the predominant negative effects exerted by roads on many wildlife species. Reducing roadkill is therefore a major component of wildlife conservation. Roadkill is affected by various factors, including road attributes and traffic volume. It is theorized that the effect of traffic volume on roadkill probability should be unimodal. However, empirical evidence for this theory is lacking. Using a large-scale roadkill database of 18 wildlife species in Israel, encompassing 2846 km of roads over 10 years, we explored the effects of traffic volume and road attributes (e.g., road lighting, verge vegetation) on roadkill probability with a multivariate generalized linear mixed model. A unimodal effect of traffic volume was identified for the striped hyena (Hyaena hyaena), whereas 5 species demonstrated a novel quadratic U-shaped effect (e.g., golden jackal [Canis aureus]). Four species showed a negative linear effect (e.g., wild boar [Sus scrofa]). We also identified varying effects of road attributes on roadkill. For instance, road lighting and roadside trees decreased roadkill for several species, whereas bus stops and concrete guardrails led to increased roadkill. The theorized unimodal effect of traffic volume may only apply to large, agile species, and the U-shaped effect could be related to intraspecies variability in traffic avoidance behavior. In general, we found that both high-traffic and low-traffic roads can pose a high mortality risk for wildlife. It is therefore important to monitor roadkill on low-traffic roads and adapt road attributes to mitigate roadkill. Road design for effective roadkill mitigation includes reducing the use of concrete guardrails and median barriers where possible and avoiding dense bushes in verge landscaping. These measures are complemented by employing wildlife detection systems, driver warnings, and seasonal speed reduction measures on low-traffic roads identified as roadkill hotspots.

Riesgo de mortalidad de fauna presentado por las carreteras de mucho y poco tráfico Denneboom et al. 23­229 Resumen La mortalidad de fauna por colisiones con vehículos es uno de los efectos negativos predominantes que tienen las carreteras sobre muchas especies. Por lo tanto, la reducción de esta mortalidad es un componente principal de la conservación de la fauna. Esta mortalidad se ve afectada por varios factores, incluyendo las características de la carretera y el volumen de tráfico. Se piensa que el efecto del volumen de tráfico sobre la probabilidad de las colisiones debería ser unimodal; sin embargo, la evidencia empírica para esta teoría no es suficiente. Usamos una base de datos de colisiones de 18 especies de fauna en Israel que engloba 2,846 km de carreteras durante diez años para explorar con un modelo mixto lineal generalizado multivariado los efectos del volumen de tráfico y las características de la carretera (p. ej., iluminación, vegetación de borde) sobre la probabilidad de colisiones. Identificamos un efecto unimodal del volumen del tráfico para la hiena rayada (Hyaena hyaena), mientras que cinco especies demostraron un efecto cuadrático novedoso en forma de U, como el chacal dorado (Canis aureus). Cuatro especies mostraron un efecto negativo lineal, como el jabalí salvaje (Sus scrofa). También identificamos varios efectos de las características de la carretera sobre las colisiones. Por ejemplo, la iluminación y los árboles en los bordes disminuyeron las colisiones para varias especies, mientras que las paradas de camión y los quitamiedos de concreto resultaron en un incremento de las colisiones. La teoría del efecto unimodal del volumen de tráfico podría aplicar sólo para especies grandes y ágiles, mientras que el efecto en forma de U podría relacionarse con la variabilidad de comportamiento para evitar colisiones que hay entre las especies. En general, descubrimos que tanto las carreteras con poco y mucho tráfico pueden representar un riesgo de mortalidad para la fauna. Por lo tanto, es importante monitorear las colisiones en las carreteras con poco tráfico y adaptar las características de la carretera para mitigar las colisiones. El diseño de las carreteras para una mitigación efectiva incluye reducir el uso de quitamiedos de concreto y barreras centrales en donde sea posible y evitar los arbustos densos en el paisajismo de los bordes. Estas medidas están complementadas con el uso de sistemas de detección de fauna, señalamientos para los conductores y medidas estacionales de reducción de la velocidad en las carreteras de poco tráfico identificadas como puntos calientes de colisiones.

Rapid growth of the US wildland-urban interface raises wildfire risk.

The wildland-urban interface (WUI) is the area where houses and wildland vegetation meet or intermingle, and where wildfire problems are most pronounced. Here we report that the WUI in the United States grew rapidly from 1990 to 2010 in terms of both number of new houses (from 30.8 to 43.4 million; 41% growth) and land area (from 581,000 to 770,000 km2; 33% growth), making it the fastest-growing land use type in the conterminous United States. The vast majority of new WUI areas were the result of new housing (97%), not related to an increase in wildland vegetation. Within the perimeter of recent wildfires (1990-2015), there were 286,000 houses in 2010, compared with 177,000 in 1990. Furthermore, WUI growth often results in more wildfire ignitions, putting more lives and houses at risk. Wildfire problems will not abate if recent housing growth trends continue.

Species with moderate intraspecific trait variability are locally abundant within an environmentally heterogeneous subtropical forest.

Species with large intraspecific trait variability (ITV) have larger niche breadth than species with low ITV and thus are expected to be more abundant at the local scale. However, whether the positive ITV-abundance relationship holds in heterogeneous local environments remains uncertain. Using an individual-based trait dataset encompassing three leaf traits (leaf area, specific leaf area, and leaf dry mass content) of 20,248 individuals across 80 species in an environmentally heterogeneous subtropical forest in eastern China, ITV for each trait of each species was estimated by rarefaction. Resource-based niche breadth and marginality (the absolute distance between the mean resource states used by a species and the mean plot-wise resource states) were estimated simultaneously by the K-S method and the outlying mean index, respectively. Species with moderate ITV were often locally abundant, while species with large or small ITV were locally rare. This unimodal relationship between ITV and species abundance persisted when traits were analyzed separately and for all tree size classes. There was also a hump-backed relationship between niche breadth and marginality, and ITV was positively associated with niche breadth. The combined results suggest either a trade-off between the benefit from expanding niche breadth to adapt to multiple habitats and the disadvantage of reducing competitive ability, or a scarcity of favorable resources. Our results do not support the traditional thought that ITV positively correlates with species abundance in heterogeneous local environments. Instead, our study suggests that moderate-rather than large-intraspecific trait variability increases species abundance at local scales.

Factors related to building loss due to wildfires in the conterminous United States.

Wildfire is globally an important ecological disturbance affecting biochemical cycles and vegetation composition, but also puts people and their homes at risk. Suppressing wildfires has detrimental ecological effects and can promote larger and more intense wildfires when fuels accumulate, which increases the threat to buildings in the wildland-urban interface (WUI). Yet, when wildfires occur, typically only a small proportion of the buildings within the fire perimeter are lost, and the question is what determines which buildings burn. Our goal was to examine which factors are related to building loss when a wildfire occurs throughout the United States. We were particularly interested in the relative roles of vegetation, topography, and the spatial arrangement of buildings, and how their respective roles vary among ecoregions. We analyzed all fires that occurred within the conterminous United States from 2000 to 2010 and digitized which buildings were lost and which survived according to Google Earth historical imagery. We modeled the occurrence as well as the percentage of buildings lost within clusters using logistic and linear regression. Overall, variables related to topography and the spatial arrangement of buildings were more frequently present in the best 20 regression models than vegetation-related variables. In other words, specific locations in the landscape have a higher fire risk, and certain development patterns can exacerbate that risk. Fire policies and prevention efforts focused on vegetation management are important, but insufficient to solve current wildfire problems. Furthermore, the factors associated with building loss varied considerably among ecoregions suggesting that fire policy applied uniformly across the United States will not work equally well in all regions and that efforts to adapt communities to wildfires must be regionally tailored.

Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities.

Species co-occurrence analysis is commonly used to assess how interspecific interactions dictate community assembly. Non-random co-occurrences, however, may also emerge from niche differences as well as environmental heterogeneity. The relationships between species co-occurrence patterns, environmental heterogeneity and species niches are not fully understood, due to complex interactions among them. To analyse the relationships among these patterns and processes, I developed synthetic community models and analysed a large dataset of tree species across the conterminous United States. Niche overlap and environmental heterogeneity had significant and contrasting effects on species co-occurrence patterns, in both modelled and real communities. Niche breadth, in turn, affected the effect sizes of both variables on species co-occurrence patterns. The effect of niche breadth on the relationship between co-occurrence and niche overlap was markedly consistent between modelled and real communities, while its effect on the relationship between co-occurrence and environmental heterogeneity was mostly consistent between real and modelled data. The results of this analysis highlight the complex and interactive effects of species niche overlap, niche breadth and environmental heterogeneity on species co-occurrence patterns. Therefore, inferring ecological processes from co-occurrence patterns without accounting for these fundamental characteristics of species and environments may lead to biased conclusions.

Environmental heterogeneity affects the location of modelled communities along the niche-neutrality continuum.

The continuum hypothesis has been proposed as a means to reconcile the contradiction between the niche and neutral theories. While past research has shown that species richness affects the location of communities along the niche-neutrality continuum, there may be extrinsic forces at play as well. We used a spatially explicit continuum model to quantify the effects of environmental heterogeneity, comprising abundance distribution and spatial configuration of resources, on the degree of community neutrality. We found that both components of heterogeneity affect the degree of community neutrality and that species' dispersal characteristics affect the neutrality-heterogeneity relationship. Narrower resource abundance distributions decrease neutrality, while spatial configuration, which is manifested by spatial aggregation of resources, decreases neutrality at higher aggregation levels. In general, the degree of community neutrality was affected by complex interactions among spatial configuration of resources, their abundance distributions and the dispersal characteristics of species in the community. Our results highlight the important yet overlooked role of the environment in dictating the location of communities along the hypothesized niche-neutrality continuum.

A European-scale analysis reveals the complex roles of anthropogenic and climatic factors in driving the initiation of large wildfires.

Analysing wildfire initiation patterns and identifying their primary drivers is essential for the development of more efficient fire prevention strategies. However, such analyses have traditionally been conducted at local or national scales, hindering cross-border comparisons and the formulation of broad-scale policy initiatives. In this study, we present an analysis of the spatial variability of wildfire initiations across Europe, focusing specifically on moderate to large fires (> 100 ha), and examining the influence of both human and climatic factors on initiation areas. We estimated drivers of fire initiation using machine learning algorithms, specifically Random Forest (RF), covering the majority of the European territory (referred to as the "ET scale"). The models were trained using data on fire initiations extracted from a satellite burned area product, comprising fires occurring from 2001 to 2019. We developed six RF models: three considering all fires larger than 100 ha, and three focused solely on the largest events (> 1000 ha). Models were developed using climatic and human predictors separately, as well as both types of predictors mixed together. We found that both climatic and mixed models demonstrated moderate predictive capacity, with AUC values ranging from 79 % to 81 %; while models based only on human variables have had poor predictive capacity (AUC of 60 %). Feature importance analysis, using Shapley Additive Explanations (SHAP), allowed us to assess the primary drivers of wildfire initiations across the European Territory. Aridity and evapotranspiration had the strongest effect on fire initiation. Among human variables, population density and aging had considerable effects on fire initiation, the former with a strong effect in mixed models estimating large fires, while the latter had a more important role in the prediction of very large fires. Distance to roads and forest-agriculture interfaces were also relevant in some initiation models. A better understanding of drivers of main fire events should help designing European forest fire management strategies, particularly in the light of growing importance of climate change, as it would affect both fire severity and areas at risk. Factors of fire initiation should also be part of a comprehensive approach for fire risk assessment, reduction and adaption, contributing to more effective wildfire management and mitigation across the continent.

Globe-LFMC 2.0, an enhanced and updated dataset for live fuel moisture content research.

Globe-LFMC 2.0, an updated version of Globe-LFMC, is a comprehensive dataset of over 280,000 Live Fuel Moisture Content (LFMC) measurements. These measurements were gathered through field campaigns conducted in 15 countries spanning 47 years. In contrast to its prior version, Globe-LFMC 2.0 incorporates over 120,000 additional data entries, introduces more than 800 new sampling sites, and comprises LFMC values obtained from samples collected until the calendar year 2023. Each entry within the dataset provides essential information, including date, geographical coordinates, plant species, functional type, and, where available, topographical details. Moreover, the dataset encompasses insights into the sampling and weighing procedures, as well as information about land cover type and meteorological conditions at the time and location of each sampling event. Globe-LFMC 2.0 can facilitate advanced LFMC research, supporting studies on wildfire behaviour, physiological traits, ecological dynamics, and land surface modelling, whether remote sensing-based or otherwise. This dataset represents a valuable resource for researchers exploring the diverse LFMC aspects, contributing to the broader field of environmental and ecological research.

Mammal responses to global changes in human activity vary by trophic group and landscape.

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human-wildlife interactions along gradients of human influence.

Using structure locations as a basis for mapping the wildland urban interface.

The wildland urban interface (WUI) delineates the areas where wildland fire hazard most directly impacts human communities and threatens lives and property, and where houses exert the strongest influence on the natural environment. Housing data are a major problem for WUI mapping. When housing data are zonal, the concept of a WUI neighborhood can be captured easily in a density measure, but variations in zone (census block) size and shape introduce bias. Other housing data are points, so zonal issues are avoided, but the neighborhood character of the WUI is lost if houses are evaluated individually. Our goal was to develop a consistent method to map the WUI that is able to determine where neighborhoods (or clusters of houses) exist, using just housing location and wildland fuel data. We used structure and vegetation maps and a moving window analysis, with various window sizes representing neighborhood sizes, to calculate the neighborhood density of both houses and wildland vegetation. Mapping four distinct areas (in WI, MI, CA and CO) the method resulted in amounts of WUI comparable to those of zonal mapping, but with greater precision. We conclude that this hybrid method is a useful alternative to zonal mapping from the neighborhood to the landscape scale, and results in maps that are better suited to operational fire management (e.g., fuels reduction) needs, while maintaining consistency with conceptual and U.S. policy-specific WUI definitions.

Assessment of storm impact on coral reef structural complexity.

Extreme weather events are increasing in frequency and magnitude. Consequently, it is important to understand their effects and remediation. Resilience reflects the ability of an ecosystem to absorb change, which is important for understanding ecological dynamics and trajectories. To describe the impact of a powerful storm on coral reef structural complexity, we used novel computational tools and detailed 3D reconstructions captured at three time points over three years. Our data-set Reefs4D of 21 co-registered image-based models enabled us to calculate the differences at seven sites over time and is released with the paper. We employed six geometrical metrics, two of which are new algorithms for calculating fractal dimension of reefs in full 3D. We conducted a multivariate analysis to reveal which sites were affected the most and their relative recovery. We also explored the changes in fractal dimension per size category using our cube-counting algorithm. Three metrics showed a significant difference between time points, i.e., decline and subsequent recovery in structural complexity. The multivariate analysis and the results per size category showed a similar trend. Coral reef resilience has been the subject of seminal studies in ecology. We add important information to the discussion by focusing on 3D structure through image-based modeling. The full picture shows resilience in structural complexity, suggesting that the reef has not gone through a catastrophic phase shift. Our novel analysis framework is widely transferable and useful for research, monitoring, and management.

Multidimensional differentiation in foraging resource use during breeding of two sympatric top predators.

Ecologically-similar species were found to develop specific strategies to partition their resources, leading to niche differentiation and divergence, in order to avoid interspecific competition. Our study determines multi-dimensional differentiation of two sympatric top-predators, long-legged buzzards (LLB) and short-toed eagles (STE), which recently became sympatric during their breeding season in the Judean Foothills, Israel. By combining information from comprehensive diet and movement analyses we found four dimensions of differentiation: (1) Geographic foraging area: LLB tended to forage relatively close to their nests (2.35 ± 0.62 km), while STE forage far from their nest (13.03 ± 2.20 km); (2) Foraging-habitat type: LLBs forage at low natural vegetation, avoiding cultivated fields, whereas STEs forage in cultivated fields, avoiding low natural vegetation; (3) Diurnal dynamics of foraging: LLBs are uniformly active during daytime, whereas STEs activity peaks in the early afternoon; and (4) Food-niche: while both species largely rely on reptiles (47.8% and 76.3% for LLB and STE, respectively), LLB had a more diverse diet and consumed significantly higher percentages of lizards, while STE consumed significantly higher percentages of snakes. Our results suggest that this multidimensional differentiation allows the spatial coexistence of these two dense populations in the study area.

Immigration rates and species niche characteristics affect the relationship between species richness and habitat heterogeneity in modeled meta-communities.

The positive relationship between habitat heterogeneity and species richness is a cornerstone of ecology. Recently, it was suggested that this relationship should be unimodal rather than linear due to a tradeoff between environmental heterogeneity and population sizes. Increased environmental heterogeneity will decrease effective habitat sizes, which in turn will increase the rate of local species extinctions. The occurrence of the unimodal richness-heterogeneity relationship at the habitat scale was confirmed in both empirical and theoretical studies. However, it is unclear whether it can occur at broader spatial scales, for meta-communities in diverse and patchy landscapes. Here, I used a spatially explicit meta-community model to quantify the roles of two species-level characteristics, niche width and immigration rates, on the type of the richness-heterogeneity relationship at the landscape scale. I found that both positive and unimodal richness-heterogeneity relationships can occur in meta-communities in patchy landscapes. The type of the relationship was affected by the interactions between inter-patch immigration rates and species' niche widths. Unimodal relationships were prominent in meta-communities comprising species with wide niches but low inter-patch immigration rates. In contrast, meta-communities consisting of species with narrow niches and high immigration rates exhibited positive relationships. Meta-communities comprising generalist species are therefore likely to exhibit unimodal richness-heterogeneity relationships as long as low immigration rates prevent rescue effects and patches are small. The richness-heterogeneity relationship at the landscape scale is dictated by species' niche widths and inter-patch immigration rates. These immigration rates, in turn, depend on the interaction between species dispersal capabilities and habitat connectivity, highlighting the roles of both species traits and landscape structure in generating the richness-heterogeneity relationship at the landscape scale.

Bird and mammal species composition in distinct geographic regions and their relationships with environmental factors across multiple spatial scales.

Global patters of species distributions and their underlying mechanisms are a major question in ecology, and the need for multi-scale analyses has been recognized. Previous studies recognized climate, topography, habitat heterogeneity and disturbance as important variables affecting such patterns. Here we report on analyses of species composition - environment relationships among different taxonomic groups in two continents, and the components of such relationships, in the contiguous USA and Australia. We used partial Canonical Correspondence Analysis of occurrence records of mammals and breeding birds from the Global Biodiversity Information Facility, to quantify relationships between species composition and environmental variables in remote geographic regions at multiple spatial scales, with extents ranging from 10(5) to 10(7) km(2) and sampling grids from 10 to 10,000 km(2). We evaluated the concept that two elements contribute to the impact of environmental variables on composition: the strength of species' affinity to an environmental variable, and the amount of variance in the variable. To disentangle these two elements, we analyzed correlations between resulting trends and the amount of variance contained in different environmental variables to isolate the mechanisms behind the observed relationships. We found that climate and land use-land cover are responsible for most explained variance in species composition, regardless of scale, taxonomic group and geographic region. However, the amount of variance in species composition attributed to land use / land cover (LULC) was closely related to the amount of intrinsic variability in LULC in the USA, but not in Australia, while the effect of climate on species composition was negatively correlated to the variability found in the climatic variables. The low variance in climate, compared to LULC, suggests that species in both taxonomic groups have strong affinity to climate, thus it has a strong effect on species distribution and community composition, while the opposite is true for LULC.

The role of abiotic environmental conditions and herbivory in shaping bacterial community composition in floral nectar.

Identifying the processes that drive community assembly has long been a central theme in ecology. For microorganisms, a traditional prevailing hypothesis states that "everything is everywhere, but the environment selects". Although the bacterial community in floral nectar may be affected by both atmosphere (air-borne bacteria) and animals as dispersal vectors, the environmental and geographic factors that shape microbial communities in floral nectar are unknown. We studied culturable bacterial communities in Asphodelus aestivus floral nectar and in its typical herbivorous bug Capsodes infuscatus, along an aridity gradient. Bacteria were sampled from floral nectar and bugs at four sites, spanning a geographical range of 200 km from Mediterranean to semi-arid conditions, under open and bagged flower treatments. In agreement with the niche assembly hypothesis, the differences in bacterial community compositions were explained by differences in abiotic environmental conditions. These results suggest that microbial model systems are useful for addressing macro-ecological questions. In addition, similar bacterial communities were found in the nectar and on the surface of the bugs that were documented visiting the flowers. These similarities imply that floral nectar bacteria dispersal is shaped not only by air borne bacteria and nectar consumers as previously reported, but also by visiting vectors like the mirid bugs.

Trends in ecological research during the last three decades--a systematic review.

It is thought that the science of ecology has experienced conceptual shifts in recent decades, chiefly from viewing nature as static and balanced to a conception of constantly changing, unpredictable, complex ecosystems. Here, we ask if these changes are reflected in actual ecological research over the last 30 years. We surveyed 750 articles from the entire pool of ecological literature and 750 articles from eight leading journals. Each article was characterized according to its type, ecological domain, and applicability, and major topics. We found that, in contrast to its common image, ecology is still mostly a study of single species (70% of the studies); while ecosystem and community studies together comprise only a quarter of ecological research. Ecological science is somewhat conservative in its topics of research (about a third of all topics changed significantly through time), as well as in its basic methodologies and approaches. However, the growing proportion of problem-solving studies (from 9% in the 1980s to 20% in the 2000 s) may represent a major transition in ecological science in the long run.

Land use planning and wildfire: development policies influence future probability of housing loss.

Increasing numbers of homes are being destroyed by wildfire in the wildland-urban interface. With projections of climate change and housing growth potentially exacerbating the threat of wildfire to homes and property, effective fire-risk reduction alternatives are needed as part of a comprehensive fire management plan. Land use planning represents a shift in traditional thinking from trying to eliminate wildfires, or even increasing resilience to them, toward avoiding exposure to them through the informed placement of new residential structures. For land use planning to be effective, it needs to be based on solid understanding of where and how to locate and arrange new homes. We simulated three scenarios of future residential development and projected landscape-level wildfire risk to residential structures in a rapidly urbanizing, fire-prone region in southern California. We based all future development on an econometric subdivision model, but we varied the emphasis of subdivision decision-making based on three broad and common growth types: infill, expansion, and leapfrog. Simulation results showed that decision-making based on these growth types, when applied locally for subdivision of individual parcels, produced substantial landscape-level differences in pattern, location, and extent of development. These differences in development, in turn, affected the area and proportion of structures at risk from burning in wildfires. Scenarios with lower housing density and larger numbers of small, isolated clusters of development, i.e., resulting from leapfrog development, were generally predicted to have the highest predicted fire risk to the largest proportion of structures in the study area, and infill development was predicted to have the lowest risk. These results suggest that land use planning should be considered an important component to fire risk management and that consistently applied policies based on residential pattern may provide substantial benefits for future risk reduction.

Multiscale analyses of mammal species composition--environment relationship in the contiguous USA.

Relationships between species composition and its environmental determinants are a basic objective of ecology. Such relationships are scale dependent, and predictors of species composition typically include variables such as climate, topographic, historical legacies, land uses, human population levels, and random processes. Our objective was to quantify the effect of environmental determinants on U.S. mammal composition at various spatial scales. We found that climate was the predominant factor affecting species composition, and its relative impact increased in correlation with the increase of the spatial scale. Another factor affecting species composition is land-use-land-cover. Our findings showed that its impact decreased as the spatial scale increased. We provide quantitative indication of highly significant effect of climate and land-use-land-cover variables on mammal composition at multiple scales.