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At least 19 recordsLinked to original sources
USGS2009

A spatial model of bird abundance as adjusted for detection probability

Modeling the spatial distribution of animals can be complicated by spatial and temporal effects (i.e. spatial autocorrelation and trends in abundance over time) and other factors such as imperfect detection probabilities and observation-related nuisance variables. Recent advances in modeling have demonstrated various approaches that handle most of these factors but which require a degree of sampling effort (e.g. replication) not available to many field studies. We present a two-step approach that addresses these challenges to spatially model species abundance. Habitat, spatial and temporal variables were handled with a Bayesian approach which facilitated modeling hierarchically structured data. Predicted abundance was subsequently adjusted to account for imperfect detection and the area effectively sampled for each species. We provide examples of our modeling approach for two endemic Hawaiian nectarivorous honeycreepers: 'i'iwi Vestiaria coccinea and 'apapane Himatione sanguinea. ?? 2009 Ecography.

Ecography↗
USGS2006

Importance of spatial autocorrelation in modeling bird distributions at a continental scale

Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.

Ecography↗
USGS2025

Dynamic riskscapes for prey: Disentangling the impact of human and cougar presence on deer behavior using GPS smartphone locations

Prey species adjust their behavior along human-use gradients by balancing risks from predators and humans. During hunting seasons, prey often exhibit strong antipredator responses to humans but may develop tolerance in suburban areas to exploit human-mediated resources. Additionally, areas with high human activity may offer reduced predation risk if apex predators avoid such locations. This study examined mule deer Odocoileus hemionus behavioral responses to risks from humans and their primary predators, cougars Puma concolor , contextualized by differences in risk levels between study sites, individual risk exposure, and human habituation. We framed our investigation using three non-mutually exclusive hypotheses: (H1) neutral impact, (H2) human shielding (human tolerance driven by cougar avoidance), and (H3) super-additive risk (human avoidance dominating behavior). We controlled for deer phenology and diel period, recognizing that deer behavior varies with these temporal dynamics. Spatiotemporal cougar encounter risk was quantified using GPS collar data, while spatiotemporal human encounter risk and use intensity were quantified using GPS smartphone data. Our results supported H2 and H3, emphasizing the significance of site- and individual-level variation in risk exposure and human use intensity. Deer managed cougar risk adaptively, but humans emerged as the dominant perceived risk, varying by study site. At the site with higher cougar density and lower human hunting pressure, deer exhibited antipredator responses to humans based on individual exposure to human activity, except during hunting season, when tolerance for cougars increased. Conversely, humans were the dominant risk at the site with lower cougar density and greater human hunting pressure. Deer behavior varied significantly across a gradient of human use, influenced by nuanced human presence and predation risks, which were discernible using human smartphone data.

Colorado, Utah↗
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↗
USGS2025

The diel niche of brown bears: Constraints on adaptive capacity in human-modified landscapes

D Diel activity rhythms, representing the behavioral pattern of the sleep–wake cycle, may be adjusted by wildlife in response to changes in environmental conditions. An increase in nocturnality is typically recognized as an adaptive strategy to segregate from humans and mitigate heat stress. Numerous studies have investigated spatial patterns and habitat use of large carnivores in human-modified landscapes, but little research has examined their activity rhythms. We compiled Global Positioning System data (2004–2022) for 139 brown bears Ursus arctos from six populations across Europe, representing a human-modified landscape, and the Greater Yellowstone Ecosystem, U.S.A., representing a landscape with limited human impact, which we used to calculate hourly movement rates as an activity proxy. Using a Bayesian approach to model the temporal autocorrelation of activity data, we tested if the extent of nocturnality in brown bears is modulated by intensity of human encroachment, accounting for primary productivity and maximum ambient temperature. All bear populations exhibited a predominantly bimodal, crepuscular pattern of activity, although Yellowstone bears were proportionally more crepuscular and diurnal. Whereas the effect of primary productivity was variable, all European populations became more nocturnal in response to higher human encroachment and reduced diurnal and crepuscular activity at higher summer temperatures, decreasing overall diel activity levels. Yellowstone bears displayed the greatest shift towards nocturnality among all populations in response to increasing human encroachment, and increased nocturnal activity to compensate for lower diurnal and crepuscular activity at higher summer temperatures. Our research indicates that European bears in human-modified landscapes may be reaching a limit in the behavioral plasticity they can manifest in their activity patterns, being already constrained into increased nocturnality. Our findings enhance the understanding of brown bear adaptive capacity to accommodate future changes, such as urbanization and increasing temperatures, to the ecosystems they inhabit.

Ecography↗
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↗
USGS2002

On the estimation of species richness based on the accumulation of previously unrecorded species

Estimation of species richness of local communities has become an important topic in community ecology and monitoring. Investigators can seldom enumerate all the species present in the area of interest during sampling sessions. If the location of interest is sampled repeatedly within a short time period, the number of new species recorded is typically largest in the initial sample and decreases as sampling proceeds, but new species may be detected if sampling sessions are added. The question is how to estimate the total number of species. The data collected by sampling the area of interest repeatedly can be used to build species-accumulation curves: the cumulative number of species recorded as a function of the number of sampling sessions (which we refer to as ?species-accumulation data?). A classic approach used to compute total species richness is to fit curves to the data on species accumulation with sampling effort. This approach does not rest on direct estimation of the probability of detecting species during sampling sessions and has no underlying basis regarding the sampling process that gave rise to the data. Here we recommend a probabilistic, nonparametric estimator for species richness for use with species-accumulation data. We use estimators of population size that were developed for capture-recapture data, but that can be used to estimate the size of species assemblages using species-accumulation data. Models of detection probability account for the underlying sampling process. They permit variation in detection probability among species. We illustrate this approach using data from the North American Breeding Bird Survey (BBS). We describe other situations where species accumulation data are collected under different designs (e.g., over longer periods of time, or over spatial replicates) and that lend themselves to use of capture-recapture models for estimating the size of the community of interest. We discuss the assumptions and interpretations corresponding to each situation.

Alabama, Louisiana, Maine, Maryland, New Hampshire↗
USGS2003

Life history, diversity and distribution: A study of Japanese pteridophytes

Many studies address the relationships between diversity or distribution and attributes of the physical environment. However, how these relationships are connected to variation in life history is poorly understood. This is particularly true in the case of pteridophytes. Japanese ferns and their allies comprise one of the best-known pteridophyte floras in the world. We analyzed ca 600 species of Japanese pteridophytes for which there is detailed information on distribution, reproduction, and chromosome number. Species richness was greatest in groups with a single reproductive mode (sexual, followed by apogamous), but distribution was greatest in species groups with multiple reproductive modes: sexual plus either sterile (irregular in meiosis) or apogamous. Geographical ranges varied greatly among species with small chromosome numbers but were uniformly small among species having high chromosome numbers. Seasonally green (mostly summer green) species had significantly larger distribution ranges than evergreen species. Endemic species had higher proportions of apogamy and sterility than non-endemic species. Seasonally green species had significantly larger distributional ranges, and a smaller proportion of species with apogamous reproduction, than evergreen species. There was no clear relationship between distribution and spore size, either among endemic species, non-endemic species, or all species combined. There was no relationship between spore size and chromosome number when all species were combined. However, positive relationships were detected within three of the nine largest genera, suggesting potential phylogenetic effects. We concluded that habitat availability, rather than dispersability, may be the limiting factor for the distribution of pteridophytes in Japan.

Ecography↗
USGS2014

Topographic, latitudinal and climatic distribution of Pinus coulteri : geographic range limits are not at the edge of the climate envelope

With changing climate, many species are projected to move poleward or to higher elevations to track suitable climates. The prediction that species will move poleward assumes that geographically marginal populations are at the edge of the species' climatic range. We studied Pinus coulteri from the center to the northern (poleward) edge of its range, and examined three scenarios regarding the relationship between the geographic and climatic margins of a species' range. We used herbarium and iNaturalist.org records to identify P. coulteri sites, generated a species distribution model based on temperature, precipitation, climatic water deficit, and actual evapotranspiration, and projected suitability under future climate scenarios. In fourteen populations from the central to northern portions of the range, we conducted field studies and recorded elevation, slope and aspect (to estimate solar insolation) to examine relationships between local and regional distributions. We found that northern populations of P. coulteri do not occupy the cold or wet edge of the species' climatic range; mid-latitude, high elevation populations occupy the cold margin. Aspect and insolation of P. coulteri populations changed significantly across latitudes and elevations. Unexpectedly, northern, low-elevation stands occupy north-facing aspects and receive low insolation, while central, high-elevation stands grow on more south-facing aspects that receive higher insolation. Modeled future climate suitability is projected to be highest in the central, high elevation portion of the species range, and in low-lying coastal regions under some scenarios, with declining suitability in northern areas under most future scenarios. For P. coulteri , the lack of high elevation habitat combined with a major dispersal barrier may limit northward movement in response to a warming climate. Our analyses demonstrate the importance of distinguishing geographically vs. climatically marginal populations, and the importance of quantitative analysis of the realized climate space to understand species range limits.

Ecography↗
USGS2014

Does probability of occurrence relate to population dynamics?

Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate ( r ) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range-wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions. The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K ) and population density ( N ) relate to occurrence probability ( P occ ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, western USA, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments. Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with P occ , while N, and for most regions K, was generally positively correlated with P occ . Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models.

Ecography↗
USGS2014

What do we gain from simplicity versus complexity in species distribution models?

Species distribution models (SDMs) are widely used to explain and predict species ranges and environmental niches. They are most commonly constructed by inferring species' occurrence–environment relationships using statistical and machine-learning methods. The variety of methods that can be used to construct SDMs (e.g. generalized linear/additive models, tree-based models, maximum entropy, etc.), and the variety of ways that such models can be implemented, permits substantial flexibility in SDM complexity. Building models with an appropriate amount of complexity for the study objectives is critical for robust inference. We characterize complexity as the shape of the inferred occurrence–environment relationships and the number of parameters used to describe them, and search for insights into whether additional complexity is informative or superfluous. By building ‘under fit’ models, having insufficient flexibility to describe observed occurrence–environment relationships, we risk misunderstanding the factors shaping species distributions. By building ‘over fit’ models, with excessive flexibility, we risk inadvertently ascribing pattern to noise or building opaque models. However, model selection can be challenging, especially when comparing models constructed under different modeling approaches. Here we argue for a more pragmatic approach: researchers should constrain the complexity of their models based on study objective, attributes of the data, and an understanding of how these interact with the underlying biological processes. We discuss guidelines for balancing under fitting with over fitting and consequently how complexity affects decisions made during model building. Although some generalities are possible, our discussion reflects differences in opinions that favor simpler versus more complex models. We conclude that combining insights from both simple and complex SDM building approaches best advances our knowledge of current and future species ranges.

Ecography↗
USGS2014

Global phylogeography of the avian malaria pathogen Plasmodium relictum based on MSP1 allelic diversity

Knowing the genetic variation that occurs in pathogen populations and how it is distributed across geographical areas is essential to understand parasite epidemiology, local patterns of virulence, and evolution of host-resistance. In addition, it is important to identify populations of pathogens that are evolutionarily independent and thus ‘free’ to adapt to hosts and environments. Here, we investigated genetic variation in the globally distributed, highly invasive avian malaria parasite Plasmodium relictum , which has several distinctive mitochondrial haplotyps (cyt b lineages, SGS1, GRW11 and GRW4). The phylogeography of P. relictum was accessed using the highly variable nuclear gene merozoite surface protein 1 (MSP1), a gene linked to the invasion biology of the parasite. We show that the lineage GRW4 is evolutionarily independent of GRW11 and SGS1 whereas GRW11 and SGS1 share MSP1 alleles and thus suggesting the presence of two distinct species (GRW4 versus SGS1 and GRW11). Further, there were significant differences in the global distribution of MSP1 alleles with differences between GRW4 alleles in the New and the Old World. For SGS1, a lineage formerly believed to have both tropical and temperate transmission, there were clear differences in MSP1 alleles transmitted in tropical Africa compared to the temperate regions of Europe and Asia. Further, we highlight the occurrence of multiple MSP1 alleles in GRW4 isolates from the Hawaiian Islands, where the parasite has contributed to declines and extinctions of endemic forest birds since it was introduced. This study stresses the importance of multiple independent loci for understanding patterns of transmission and evolutionary independence across avian malaria parasites.

Ecography↗
USGS2015

Relating mesocarnivore relative abundance to anthropogenic land-use with a hierarchical spatial count model

There is growing need to develop models of spatial patterns in animal abundance, yet comparatively few examples of such models exist. This is especially true in situations where the abundance of one species may inhibit that of another, such as the intensively-farmed landscape of the Prairie Pothole Region (PPR) of the central United States, where waterfowl production is largely constrained by mesocarnivore nest predation. We used a hierarchical Bayesian approach to relate the distribution of various land-cover types to the relative abundances of four mesocarnivores in the PPR: coyote Canis latrans, raccoon Procyon lotor, red fox Vulpes vulpes, and striped skunk Mephitis mephitis. We developed models for each species at multiple spatial resolutions (41.4 km2, 10.4 km2, and 2.6 km2) to address different ecological and management-related questions. Model results for each species were similar irrespective of resolution. We found that the amount of row-crop agriculture was nearly ubiquitous in our best models, exhibiting a positive relationship with relative abundance for each species. The amount of native grassland land-cover was positively associated with coyote and raccoon relative abundance, but generally absent from models for red fox and skunk. Red fox and skunk were positively associated with each other, suggesting potential niche overlap. We found no evidence that coyote abundance limited that of other mesocarnivore species, as might be expected under a hypothesis of mesopredator release. The relationships between relative abundance and land-cover types were similar across spatial resolutions. Our results indicated that mesocarnivores in the PPR are most likely to occur in portions of the landscape with large amounts of agricultural land-cover. Further, our results indicated that track-survey data can be used in a hierarchical framework to gain inferences regarding spatial patterns in animal relative abundance.

Iowa, Minnesota↗
USGS2015

Distribution of invasive and native riparian woody plants across the western USA in relation to climate, river flow, floodplain geometry and patterns of introduction

Management of riparian plant invasions across the landscape requires understanding the combined influence of climate, hydrology, geologic constraints and patterns of introduction. We measured abundance of nine riparian woody taxa at 456 stream gages across the western USA. We constructed conditional inference recursive binary partitioning models to discriminate the influence of eleven environmental variables on plant occurrence and abundance, focusing on the two most abundant non-native taxa, Tamarix spp. and Elaeagnus angustifolia , and their native competitor Populus deltoides . River reaches in this study were distributed along a composite gradient from cooler, wetter higher-elevation reaches with higher stream power and earlier snowmelt flood peaks to warmer, drier lower-elevation reaches with lower power and later peaks. Plant distributions were strongly related to climate, hydrologic and geomorphic factors, and introduction history. The strongest associations were with temperature and then precipitation. Among hydrologic and geomorphic variables, stream power, peak flow timing and 10-yr flood magnitude had stronger associations than did peak flow predictability, low-flow magnitude, mean annual flow and channel confinement. Nearby intentional planting of Elaeagnus was the best predictor of its occurrence, but planting of Tamarix was rare. Higher temperatures were associated with greater abundance of Tamarix relative to P. deltoides , and greater abundance of P. deltoides relative to Elaeagnus. Populus deltoides abundance was more strongly related to peak flow timing than was that of Elaeagnus or Tamarix . Higher stream power and larger 10-yr floods were associated with greater abundance of P. deltoides and Tamarix relative to Elaeagnus . Therefore, increases in temperature could increase abundance of Tamarix and decrease that of Elaeagnus relative to P. deltoides , changes in peak flow timing caused by climate change or dam operations could increase abundance of both invasive taxa, and dam-induced reductions in flood peaks could increase abundance of Elaeagnus relative to Tamarix and P. deltoides .

Arizona, California, Colorado, Idaho, Kansas, Mont↗
USGS2015

A centroid model of species distribution with applications to the Carolina wren Thryothorus ludovicianus and house finch Haemorhous mexicanus in the United States

Drastic shifts in species distributions are a cause of concern for ecologists. Such shifts pose great threat to biodiversity especially under unprecedented anthropogenic and natural disturbances. Many studies have documented recent shifts in species distributions. However, most of these studies are limited to regional scales, and do not consider the abundance structure within species ranges. Developing methods to detect systematic changes in species distributions over their full ranges is critical for understanding the impact of changing environments and for successful conservation planning. Here, we demonstrate a centroid model for range-wide analysis of distribution shifts using the North American Breeding Bird Survey. The centroid model is based on a hierarchical Bayesian framework which models population change within physiographic strata while accounting for several factors affecting species detectability. Yearly abundance-weighted range centroids are estimated. As case studies, we derive annual centroids for the Carolina wren and house finch in their ranges in the U.S. We further evaluate the first-difference correlation between species’ centroid movement and changes in winter severity, total population abundance. We also examined associations of change in centroids from sub-ranges. Change in full-range centroid movements of Carolina wren significantly correlate with snow cover days (r = −0.58). For both species, the full-range centroid shifts also have strong correlation with total abundance (r = 0.65, and 0.51 respectively). The movements of the full-range centroids of the two species are correlated strongly (up to r = 0.76) with that of the sub-ranges with more drastic population changes. Our study demonstrates the usefulness of centroids for analyzing distribution changes in a two-dimensional spatial context. Particularly it highlights applications that associate the centroid with factors such as environmental stressors, population characteristics, and progression of invasive species. Routine monitoring of changes in centroid will provide useful insights into long-term avian responses to environmental changes.

Ecography↗
USGS2015

Density-dependent home-range size revealed by spatially explicit capture–recapture

The size of animal home ranges often varies inversely with population density among populations of a species. This fact has implications for population monitoring using spatially explicit capture–recapture (SECR) models, in which both the scale of home-range movements σ and population density D usually appear as parameters, and both may vary among populations. It will often be appropriate to model a structural relationship between population-specific values of these parameters, rather than to assume independence. We suggest re-parameterizing the SECR model using k p = σ p √D p , where k p relates to the degree of overlap between home ranges and the subscript p distinguishes populations. We observe that k p is often nearly constant for populations spanning a range of densities. This justifies fitting a model in which the separate k p are replaced by the single parameter k and σ p is a density-dependent derived parameter. Continuous density-dependent spatial variation in σ may also be modelled, using a scaled non-Euclidean distance between detectors and the locations of animals. We illustrate these methods with data from automatic photography of tigers (Panthera tigris) across India, in which the variation is among populations, from mist-netting of ovenbirds (Seiurus aurocapilla) in Maryland, USA, in which the variation is within a single population over time, and from live-trapping of brushtail possums (Trichosurus vulpecula) in New Zealand, modelling spatial variation within one population. Possible applications and limitations of the methods are discussed. A model in which k p is constant, while density varies, provides a parsimonious null model for SECR. The parameter k of the null model is a concise summary of the empirical relationship between home-range size and density that is useful in comparative studies. We expect deviations from this model, particularly the dependence of k p on covariates, to be biologically interesting.

Ecography↗
USGS2015

geoknife: Reproducible web-processing of large gridded datasets

Geoprocessing of large gridded data according to overlap with irregular landscape features is common to many large-scale ecological analyses. The geoknife R package was created to facilitate reproducible analyses of gridded datasets found on the U.S. Geological Survey Geo Data Portal web application or elsewhere, using a web-enabled workflow that eliminates the need to download and store large datasets that are reliably hosted on the Internet. The package provides access to several data subset and summarization algorithms that are available on remote web processing servers. Outputs from geoknife include spatial and temporal data subsets, spatially-averaged time series values filtered by user-specified areas of interest, and categorical coverage fractions for various land-use types.

Ecography↗