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At least 1,207 records · Page 67Linked to original sources
USGS2011

Ecosystem approach to inland fisheries: Research needs and implementation strategies

Inland fisheries are a vital component in the livelihoods and food security of people throughout the world, as well as contributing huge recreational and economic benefits. These valuable assets are jeopardized by lack of research-based understanding of the impacts of fisheries on inland ecosystems, and similarly the impact of human activities associated with inland waters on fisheries and aquatic biodiversity. To explore this topic, an international workshop was organized in order to examine strategies to incorporate fisheries into ecosystem approaches for management of inland waters. To achieve this goal, a new research agenda is needed that focuses on: quantifying the ecosystem services provided by fresh waters; quantifying the economic, social and nutritional benefits of inland fisheries; improving assessments designed to evaluate fisheries exploitation potential; and examining feedbacks between fisheries, ecosystem productivity and aquatic biodiversity. Accomplishing these objectives will require merging natural and social science approaches to address coupled social-ecological system dynamics. ?? 2010 The Royal Society.

Conference Paper↗
USGS2016

At the nexus of fire, water and society

The societal risks of water scarcity and water-quality impairment have received considerable attention, evidenced by recent analyses of these topics by the 2030 Water Resources Group, the United Nations and the World Economic Forum. What are the effects of fire on the predicted water scarcity and declines in water quality? Drinking water supplies for humans, the emphasis of this exploration, are derived from several land cover types, including forests, grasslands and peatlands, which are vulnerable to fire. In the last two decades, fires have affected the water supply catchments of Denver (CO) and other southwestern US cities, and four major Australian cities including Sydney, Canberra, Adelaide and Melbourne. In the same time period, several, though not all, national, regional and global water assessments have included fire in evaluations of the risks that affect water supplies. The objective of this discussion is to explore the nexus of fire, water and society with the hope that a more explicit understanding of fire effects on water supplies will encourage the incorporation of fire into future assessments of water supplies, into the pyrogeography conceptual framework and into planning efforts directed at water resiliency.

Philosophical Transactions of the Royal Society B:↗
USGS2024

Leveraging natural capital accounting to support businesses with nature-related risk assessments and disclosures

Nature loss threatens businesses, the global economy and financial stability. Understanding and addressing these risks for business will require credible measurement approaches and data. This paper explores how natural capital accounting (NCA) can support business data and information needs related to nature, including disclosures aligned with the Taskforce on Nature-related Financial Disclosures recommendations. As businesses seek to measure, manage and disclose their nature-related risks and opportunities, they will need well-organized, consistent and high-quality information regarding their dependencies and impacts on nature, which few businesses currently collect or track in-house. NCA may be useful for these purposes but has not been widely used or applied by businesses. National NCA guided by the U.N. System of Environmental-Economic Accounting may provide: (i) a useful framework for businesses in conceptualizing, organizing and managing nature-related data and statistics; and (ii) data and information that can directly support business disclosures, corporate NCA and other business applications. This paper explores these opportunities as well as synergies between national and corporate natural capital accounts. In addition, the paper discusses key barriers to advancing the wider use and benefits of NCA for business, including: awareness of NCA, data access, business capabilities related to NCA, spatial and temporal scales of data, audit and assurance considerations, potential risks, and costs and incentives.

Philosophical Transactions of the Royal Society B:↗
USGS2026

The biosphere in the Anthropocene

Earth’s biosphere is in a period of rapid change, resulting from anthropogenic pressures such as climate change, habitat loss and species translocation and extinction. The extraordinary pace of change has led to the suggestion that we live in a new geological epoch of time called the Anthropocene. In this theme issue, we explore the major changes to the terrestrial and marine biospheres, from the deep oceans to the agricultural landscapes of the Anthropocene. We take a deliberately pluralistic approach that represents different viewpoints from the sciences and social sciences, examining our negative and sometimes calamitous impacts on species and ecosystems and our potential for positive interactions with the biosphere, and exploring change over millennia.

Transactions of the Royal Society of London↗
USGS2022

Examination of the interaction between age-specific predation and chronic disease in the Greater Yellowstone Ecosystem

Predators may create healthier prey populations by selectively removing diseased individuals. Predators typically prefer some ages of prey over others, which may, or may not, align with those prey ages that are most likely to be diseased. The interaction of age-specific infection and predation has not been previously explored and likely has sizable effects on disease dynamics. We hypothesize that predator cleansing effects will be greater when the disease and predation occur in the same prey age groups. We examine the predator cleansing effect using a model where both vulnerability to predators and pathogen prevalence vary with age. We tailor this model to chronic wasting disease (CWD) in mule deer and elk populations in the Greater Yellowstone Ecosystem, with empirical data from Yellowstone grey wolves and cougars. Model results suggest that under moderate, yet realistic, predation pressure from cougars and wolves independently, predators may decrease CWD outbreak size substantially and delay the accumulation of symptomatic deer and elk. The magnitude of this effect is driven by the ability of predators to selectively remove late-stage CWD infections that are likely the most responsible for transmission, but this may not be the age class they typically select. Thus, predators that select for infected young adults over uninfected juveniles have a stronger cleansing effect, and these effects are strengthened when transmission rates increase with increasing prey morbidity. There are also trade-offs from a management perspective—that is, increasing predator kill rates can result in opposing forces on prey abundance and CWD prevalence. Our modelling exploration shows that predators have the potential to reduce prevalence in prey populations when prey age and disease severity are considered, yet the strength of this effect is influenced by predators' selection for demography or body condition. Current CWD management focuses on increasing cervid hunting as the primary management tool, and our results suggest predators may also be a useful tool under certain conditions, but not necessarily without additional impacts on host abundance and demography. Protected areas with predator populations will play a large role in informing the debate over predator impacts on disease.

Wyoming↗
USGS2021

Behavioral state-dependent habitat selection and implications for animal translocations

Post-release monitoring of translocated animals is often used to inform future translocation protocols. Quantifying habitat selection of translocated individuals may help identify features that characterize good settlement habitat and thus inform the choice of future release sites. However, translocated animals often undergo post-release behavioural modification, and their habitat selection may vary depending on the underlying behavioural state. To investigate this, we analysed behavioural state-dependent habitat selection in female greater sage-grouse Centrocercus urophasianus translocated from Wyoming to North Dakota, USA, using Hidden Markov Models combined with Integrated Step Selection Analysis. We segmented individual trajectories into behavioural phases corresponding to an exploratory state, characterized by broad and directed movements, and a restricted state, characterized by short and tortuous movements. Then, we quantified habitat selection in each state while accounting for seasonality and individual reproductive status. While in the exploratory state, sage-grouse exhibited natal habitat preference induction by selecting for high sagebrush cover, which is typical of their natal area in Wyoming but not of the release area in North Dakota. In the restricted state, sage-grouse selected for gentle topography and also adjusted their habitat selection to constraints imposed by seasonality and reproductive needs by selecting for high herbaceous cover during brood rearing. Synthesis and applications . Habitat selection of translocated sage-grouse differed between the post-release exploration and the settlement phase. Features selected after settling, not during exploration, are likely indicative of suitable settlement habitat. Our results suggest that areas characterized by gentle topography and high herbaceous cover are well-suited as release sites for sage-grouse translocated during the summer, especially brood-rearing females, and that sagebrush cover may not be a critical factor in determining the appropriateness of release sites for sage-grouse in North Dakota. Our findings highlight the need to consider behaviour when using habitat selection estimates to inform the choice of future release sites.

North Dakota, Wyoming↗
USGS2019

Integration of eDNA-based biological monitoring within the US Geological Survey’s national streamgage network

This study explores the feasibility and utility of integrating environmental DNA (eDNA) assessments of species occurrences into the United States (U.S.) Geological Survey’s national streamgage network. We used an existing network of five gages in southwest Idaho to explore the type of information that could be gained as well as the associated costs and limitations. Hydrologic technicians were trained in eDNA sampling protocols and they collected samples during routine monthly visits to streamgages over an entire water year (2016). We analyzed the eDNA in the filtered water samples to determine the presence of two fish species: bull trout and rainbow trout. We then modeled the spatiotemporal distribution of each species using discharge and temperature data. To assess the influence of the spatial distribution of the gages on the biological information obtained, we also collected eDNA samples from locations between the gages three times during the water year. We found eDNA monitoring at the five gages provided meaningful information about the distribution of both species, especially when detection probabilities accounted for variations in temperature and discharge. Sampling between the gages provided additional information about bull trout distribution — the rarer of the two species. Our study suggests the integration of eDNA sampling into a streamgage network is feasible and could provide a novel and powerful source of biological information for riverine ecosystems in the U.S.

Idaho, Nebraska↗
USGS2017

Statistical design and analysis for plant cover studies with multiple sources of observation errors

Effective wildlife habitat management and conservation requires understanding the factors influencing distribution and abundance of plant species. Field studies, however, have documented observation errors in visually estimated plant cover including measurements which differ from the true value (measurement error) and not observing a species that is present within a plot (detection error). Unlike the rapid expansion of occupancy and N-mixture models for analysing wildlife surveys, development of statistical models accounting for observation error in plants has not progressed quickly. Our work informs development of a monitoring protocol for managed wetlands within the National Wildlife Refuge System. Zero-augmented beta (ZAB) regression is the most suitable method for analysing areal plant cover recorded as a continuous proportion but assumes no observation errors. We present a model extension that explicitly includes the observation process thereby accounting for both measurement and detection errors. Using simulations, we compare our approach to a ZAB regression that ignores observation errors (naïve model) and an “ad hoc” approach using a composite of multiple observations per plot within the naïve model. We explore how sample size and within-season revisit design affect the ability to detect a change in mean plant cover between 2 years using our model. Explicitly modelling the observation process within our framework produced unbiased estimates and nominal coverage of model parameters. The naïve and “ad hoc” approaches resulted in underestimation of occurrence and overestimation of mean cover. The degree of bias was primarily driven by imperfect detection and its relationship with cover within a plot. Conversely, measurement error had minimal impacts on inferences. We found >30 plots with at least three within-season revisits achieved reasonable posterior probabilities for assessing change in mean plant cover. For rapid adoption and application, code for Bayesian estimation of our single-species ZAB with errors model is included. Practitioners utilizing our R-based simulation code can explore trade-offs among different survey efforts and parameter values, as we did, but tuned to their own investigation. Less abundant plant species of high ecological interest may warrant the additional cost of gathering multiple independent observations in order to guard against erroneous conclusions.

Methods in Ecology and Evolution↗
USGS2022

Ignoring species availability biases occupancy estimates in single-scale occupancy models

Most applications of single-scale occupancy models do not differentiate between availability and detectability, even though species availability is rarely equal to one. Species availability can be estimated using multi-scale occupancy models; however, for the practical application of multi-scale occupancy models, it can be unclear what a robust sampling design looks like and what the statistical properties of the multi-scale and single-scale occupancy models are when availability is less than one. Using simulations, we explore the following common questions asked by ecologists during the design phase of a field study: (Q1) what is a robust sampling design for the multi-scale occupancy model when there are a priori expectations of parameter estimates? (Q2) what is a robust sampling design when we have no expectations of parameter estimates? and (Q3) can a single-scale occupancy model with a random effects term adequately absorb the extra heterogeneity produced when availability is less than one and provide reliable estimates of occupancy probability? Our results show that there is a tradeoff between the number of sites and surveys needed to achieve a specified level of acceptable error for occupancy estimates using the multi-scale occupancy model. We also document that when species availability is low (<0.40 on the probability scale), then single-scale occupancy models underestimate occupancy by as much as 0.40 on the probability scale, produce overly precise estimates, and provide poor parameter coverage. This pattern was observed when a random effects term was and was not included in the single-scale occupancy model, suggesting that adding a random-effects term does not adequately absorb the extra heterogeneity produced by the availability process. In contrast, when species availability was high (>0.60), single-scale occupancy models performed similarly to the multi-scale occupancy model. Users can further explore our results and sampling designs across a number of different scenarios using the RShiny app https://gdirenzo.shinyapps.io/multi-scale-occ/ . Our results suggest that unaccounted for availability can lead to underestimating species distributions when using single-scale occupancy models, which can have large implications on inference and prediction, especially for those working in the fields of invasion ecology, disease emergence, and species conservation.

Methods in Ecology and Evolution↗
USGS2019

Factors affecting species richness and distribution spatially and temporally within a protected area using multi-season occupancy models

Exploring trends in species richness and the distribution of individual species over time as well as the factors affecting these trends informs conservation priorities in protecting species and ecosystems as a whole. We used data from 41 park-wide line transect surveys in 2009 and 2014 and multi-season occupancy models with multi-species data to explore trends in species richness and distribution of individual species and factors affecting these trends in Nyungwe National Park (NNP), Rwanda. Mammalian species richness and the distributional range of 5 of the 7 species increased between 2009 and 2014 in NNP. The probability of colonization of a species into a new area in 2014, where it was not present in 2009, was highest in sites with a lower probability of poaching activity, close to tourist trails, and at lower elevations. The probability of colonization with no poaching activity was about 50% but dropped to about 10% with a 100% chance of poaching activity. Duiker species had the largest increase in distribution during the study, while there was a decrease in the distribution of the eastern chimpanzee and blue monkey. Our results suggest that increased patrols should be implemented in areas of the park with low species richness and areas with a low probability of occurrence for species of conservation concern to combat poaching activity and thus increase the probability of a species moving into a new area. Our use of a single multi-season model for multiple species explicitly accounts for imperfect detection and species-specific identities, while allowing for inferences to be made about rarely detected species by sharing covariates with common species. These results can be used to improve conservation planning in NNP for species management and ranger patrol protocols and our modelling framework is broadly applicable to any protected area with presence/absence species field data.

Nyungwe Forest National Park↗
USGS2022

Quantitative meta-analysis reveals no association between mercury contamination and body condition in birds

Mercury contamination is a major threat to the global environment, and is still increasing in some regions despite international regulations. The methylated form of mercury is hazardous to biota, yet its sublethal effects are difficult to detect in wildlife. Body condition can vary in response to stressors, but previous studies have shown mixed effects of mercury on body condition in wildlife. Using birds as study organisms, we provide the first quantitative synthesis of the effect of mercury on body condition in animals. In addition, we explored the influence of intrinsic, extrinsic and methodological factors potentially explaining cross-study heterogeneity in results. We considered experimental and correlative studies carried out in adult birds and chicks, and mercury exposure inferred from blood and feathers. Most experimental investigations (90%) showed a significant relationship between mercury concentrations and body condition. Experimental exposure to mercury disrupted nutrient (fat) metabolism, metabolic rates, and food intake, resulting in either positive or negative associations with body condition. Correlative studies also showed either positive or negative associations, of which only 14% were statistically significant. Therefore, the overall effect of mercury concentrations on body condition was null in both experimental (estimate ± SE = 0.262 ± 0.309, 20 effect sizes, five species) and correlative studies (−0.011 ± 0.020, 315 effect sizes, 145 species). The single and interactive effects of age class and tissue type were accounted for in meta-analytic models of the correlative data set, since chicks and adults, as well as blood and feathers, are known to behave differently in terms of mercury accumulation and health effects. Of the 15 moderators tested, only wintering status explained cross-study heterogeneity in the correlative data set: free-ranging wintering birds were more likely to show a negative association between mercury and body condition. However, wintering effect sizes were limited to passerines, further studies should thus confirm this trend in other taxa. Collectively, our results suggest that ( i ) effects of mercury on body condition are weak and mostly detectable under controlled conditions, and ( ii ) body condition indices are unreliable indicators of mercury sublethal effects in the wild. Food availability, feeding rates and other sources of variation that are challenging to quantify likely confound the association between mercury and body condition in natura . Future studies could explore the metabolic effects of mercury further using designs that allow for the estimation and/or manipulation of food intake in both wild and captive birds, especially in under-represented life-history stages such as migration and overwintering.

Biological Reviews↗
USGS2019

Reserve design to optimize functional connectivity and animal density

Ecological distance-based spatial capture–recapture models (SCR) are a promising approach for simultaneously estimating animal density and connectivity, both of which affect spatial population processes and ultimately species persistence. We explored how SCR models can be integrated into reserve-design frameworks that explicitly acknowledge both the spatial distribution of individuals and their space use resulting from landscape structure. We formulated the design of wildlife reserves as a budget-constrained optimization problem and conducted a simulation to explore 3 different SCR-informed optimization objectives that prioritized different conservation goals by maximizing the number of protected individuals, reserve connectivity, and density-weighted connectivity. We also studied the effect on our 3 objectives of enforcing that the space-use requirements of individuals be met by the reserve for individuals to be considered conserved (referred to as home-range constraints). Maximizing local population density resulted in fragmented reserves that would likely not aid long-term population persistence, and maximizing the connectivity objective yielded reserves that protected the fewest individuals. However, maximizing density-weighted connectivity or preemptively imposing home-range constraints on reserve design yielded reserves of largely spatially compact sets of parcels covering high-density areas in the landscape with high functional connectivity between them. Our results quantify the extent to which reserve design is constrained by individual home-range requirements and highlight that accounting for individual space use in the objective and constraints can help in the design of reserves that balance abundance and connectivity in a biologically relevant manner.

Conservation Biology↗
USGS2021

Mechanistic invasive species management models and their application in conservation

Management strategies to address the challenges associated with invasive species are critical for effective conservation. An increasing variety of mathematical models offer insight into invasive populations, and can help managers identify cost effective prevention, control, and eradication actions. Despite this, as model complexity grows, so does the inaccessibility of these tools to conservation practitioners making decisions about management. Here, we seek to narrow the science-practice gap by reviewing invasive species management models (ISMMs). We define ISMMs as mechanistic models used to explore invasive species management strategies, and include reaction-advection–diffusion models, integrodifference equations, gravity models, particle transport models, nonspatial and spatial discrete-time population growth models, cellular automata, and individual-based models. For each approach, we describe the model framework and its implementation, discuss strengths and weaknesses, and give examples of conservation applications. We conclude by discussing how ISMMs can be used in concert with adaptive management to address scientific uncertainties impeding action and with multiple objective decision processes to evaluate tradeoffs among management objectives. We undertook this review to support more effective decision-making involving invasive species by providing conservation practitioners with the information they need to identify tools most useful for their applications.

Conservation Science and Practice↗
USGS2019

Local niche differences predict genotype associations in sister taxa of desert tortoise

Aims To investigate spatial congruence between ecological niches and genotype in two allopatric species of desert tortoise that are species of conservation concern. Location Mojave and Sonoran Desert ecoregions; California, Nevada, Arizona, Utah, USA. Methods We compare ecological niches of Gopherus agassizii and Gopherus morafkai using species distribution modelling (SDM) and then calibrate a pooled‐taxa distribution model to explore local differences in species–environment relationships based on the spatial residuals of the pooled‐taxa model. We use multiscale geographically weighted regression (MGWR) applied to those residuals to estimate local species–environment relationships that can vary across the landscape. We identify multivariate clusters in these local species–environment relationships and compare them against models of (a) a geographically based taxonomic designation for two sister species and (b) an environmental ecoregion designation, with respect to their ability to predict a genotype association index for these two species. Results We find non‐identical niches for these species, with differences that span physiographic and vegetation niche dimensions. We find evidence for two distinct clusters of local species–environment relationships that when mapped, predict an index of genotype association for the two sister taxa better than did either the geographically based taxonomic designation or an environmental ecoregion designation. Main conclusions Exploring local species–environment relationships by coupling SDM and MGWR can benefit studies of biogeography and conservation. We find that niche separation in habitat selection conforms to genotypic differences between sister taxa of tortoise in a recent secondary contact zone. This result may inform decision making by agencies with regulatory or land management authority for the two sister taxa addressed here.

Arizona, California, Nevada, Utah↗
USGS2025

Non-native bird populations respond differently to their environment and exhibit shifts in ecological niche limits across continents

Aim The degree to which species' niches remain stable over space and time–the niche conservatism hypothesis–is critical for predicting species' responses to environmental change. Tests of this hypothesis typically focus on changes in niche centroids and boundaries. An outstanding question is whether species' environmental associations differ within the interior of their niche space–that is, across the full range of occupied conditions–in original versus novel geographic space. Location Europe and North America. Time Period 1997–2018. Major Taxa Studied Birds. Methods We used over 400,000 observations collected over 22 years and across 28 countries to explore whether two common songbird species—European starling ( Sturnus vulgaris ) and house sparrow ( Passer domesticus ) – exhibit niche conservatism between their native European and non-native North American ranges. We tested for niche conservatism via (1) an ordination approach that quantified change in niche shape and boundaries, and (2) generalised linear mixed effects models to quantify how abundance varied with the interaction between continent and climate or land cover variables. Results The ordination analysis indicated that both European starling and house sparrow exhibited niche conservatism between Europe and North America. However, abundance models revealed continental differences in how the species responded to temperature and land cover. The abundance models also revealed that areas with wetter conditions that were occupied by both species in their native European ranges were available but unoccupied in their non-native North American ranges (i.e., niche unfilling). Main Conclusions Our work demonstrates that species can exhibit apparent consistency in niche boundaries but varied abundance responses to the environment within niche boundaries. Expanding the study of niche conservatism to explore changes both at the edge of and within niche boundaries would improve the ability to assess and predict species' invasion risk or sensitivity to ongoing global change.

Diversity and Distributions↗
USGS2014

Predation on native sculpin by exotic brown trout exceeds that by native cutthroat trout within a mountain watershed (Logan, UT, USA)

We explored potential negative effects of exotic brown trout ( Salmo trutta ) on native sculpin ( Cottus sp.) on the Logan River, Utah, USA by (i) examining factors most strongly correlated with sculpin abundance (e.g., abiotic conditions or piscivory?), (ii) contrasting the extent of brown trout predation on sculpin with that by native cutthroat trout ( Oncorhynchus clarkii utah ) and (iii) estimating the number of sculpin consumed by brown trout along an elevational gradient using bioenergetics. Abundance of sculpin across reaches showed a strong ( r ≥ 0.40) and significant ( P < 0.05) correlation with physical variables describing width (positive) and gradient (negative), but not with abundance of piscivorous brown trout or cutthroat trout. In mainstem reaches containing sculpin, we found fish in 0% of age‐1, 10% of age‐2 and 33% of age‐3 and older brown trout diets. Approximately 81% of fish consumed by brown trout were sculpin. Despite a similar length–gape relationship for native cutthroat trout, we found only two fish (one sculpin and one unknown) in the diets of native cutthroat trout similar in size to age‐3 brown trout. Based on bioenergetics, we estimate that an average large (> 260 mm) brown trout consumes as many as 34 sculpin per year. Nevertheless, results suggest that sculpin abundance in this system is controlled by abiotic factors and not brown trout predation. Additional research is needed to better understand how piscivory influences brown trout invasion success, including in‐stream experiments exploring trophic dynamics and interactions between brown trout and native prey under different environmental conditions.

Utah↗
USGS2025

Precipitation pulse dynamics are not ubiquitous: A global meta-analysis of plant and ecosystem carbon- and water-related pulse responses

Ecosystem responses to precipitation pulses (“pulse responses”) exert a large control over global carbon, water, and energy cycles. However, it is unclear how the timing and magnitude of pulse responses will vary across ecosystems as precipitation regimes shift under accelerating climate change. To address this issue, this study evaluates how plants and ecosystems respond to precipitation pulses and explores potential implications of altered precipitation regimes for the carbon and water cycles. In particular, we conducted a global meta-analysis to quantify the magnitude and timing of plant and ecosystem carbon-related ( A net , NPP, GPP, R eco , R bg ) and water-related (ET, T, Ψ, g s ) responses to 587 precipitation pulses. By analyzing pulse-response metrics published in the primary literature, we evaluated the characteristics of those pulse responses. We assessed whether precipitation pulses lead to a classic pulse response (i.e., a hump-shaped response as described by the pulse-reserve framework), a linear pulse response, a combination of classic and linear, or a lack of a pulse response. If a pulse response occurred, we explored the factors that drove its timing, magnitude, and speed. Our meta-analyses revealed that the classic, hump-shaped response is not ubiquitous, as it only accounted for 52% of the pulse responses. However, when a pulse response did occur, carbon-related responses to precipitation pulses were larger in magnitude (e.g., larger peak) than water-related pulse responses at relatively arid sites. However, at relatively mesic sites, this relationship reversed (i.e., water-related responses to precipitation pulses were larger than carbon-related responses). Additionally, larger precipitation pulse amounts increased water-related response magnitudes more than carbon-related response magnitudes across both arid and mesic sites. Therefore, under future precipitation intensification, carbon-related responses to precipitation pulses may become more decoupled from water-related pulse responses in wetter biomes but more coupled to water-related pulse responses in drier biomes.

Global Change Biology↗
USGS2007

Remote sensing-based predictors improve distribution models of rare, early successional and broadleaf tree species in Utah

1. Compared to bioclimatic variables, remote sensing predictors are rarely used for predictive species modelling. When used, the predictors represent typically habitat classifications or filters rather than gradual spectral, surface or biophysical properties. Consequently, the full potential of remotely sensed predictors for modelling the spatial distribution of species remains unexplored. Here we analysed the partial contributions of remotely sensed and climatic predictor sets to explain and predict the distribution of 19 tree species in Utah. We also tested how these partial contributions were related to characteristics such as successional types or species traits. 2. We developed two spatial predictor sets of remotely sensed and topo-climatic variables to explain the distribution of tree species. We used variation partitioning techniques applied to generalized linear models to explore the combined and partial predictive powers of the two predictor sets. Non-parametric tests were used to explore the relationships between the partial model contributions of both predictor sets and species characteristics. 3. More than 60% of the variation explained by the models represented contributions by one of the two partial predictor sets alone, with topo-climatic variables outperforming the remotely sensed predictors. However, the partial models derived from only remotely sensed predictors still provided high model accuracies, indicating a significant correlation between climate and remote sensing variables. The overall accuracy of the models was high, but small sample sizes had a strong effect on cross-validated accuracies for rare species. 4. Models of early successional and broadleaf species benefited significantly more from adding remotely sensed predictors than did late seral and needleleaf species. The core-satellite species types differed significantly with respect to overall model accuracies. Models of satellite and urban species, both with low prevalence, benefited more from use of remotely sensed predictors than did the more frequent core species. 5. Synthesis and applications. If carefully prepared, remotely sensed variables are useful additional predictors for the spatial distribution of trees. Major improvements resulted for deciduous, early successional, satellite and rare species. The ability to improve model accuracy for species having markedly different life history strategies is a crucial step for assessing effects of global change. ?? 2007 The Authors.

Journal of Applied Ecology↗