Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Ecological Modeling”

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

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

At least 991 records · Page 55Linked to original sources
USGS2005

Estimating size and composition of biological communities by modeling the occurrence of species

We develop a model that uses repeated observations of a biological community to estimate the number and composition of species in the community. Estimators of community-level attributes are constructed from model-based estimators of occurrence of individual species that incorporate imperfect detection of individuals. Data from the North American Breeding Bird Survey are analyzed to illustrate the variety of ecologically important quantities that are easily constructed and estimated using our model-based estimators of species occurrence. In particular, we compute site-specific estimates of species richness that honor classical notions of species-area relationships. We suggest extensions of our model to estimate maps of occurrence of individual species and to compute inferences related to the temporal and spatial dynamics of biological communities.

Journal of the American Statistical Association↗
USGS2020

The Fire and Tree Mortality Database, for empirical modeling of individual tree mortality after fire

Wildland fires have a multitude of ecological effects in forests, woodlands, and savannas across the globe. A major focus of past research has been on tree mortality from fire, as trees provide a vast range of biological services. We assembled a database of individual-tree records from prescribed fires and wildfires in the United States. The Fire and Tree Mortality (FTM) database includes records from 164,293 individual trees with records of fire injury (crown scorch, bole char, etc.), tree diameter, and either mortality or top-kill up to ten years post-fire. Data span 142 species and 62 genera, from 409 fires occurring from 1981-2016. Additional variables such as insect attack are included when available. The FTM database can be used to evaluate individual fire-caused mortality models for pre-fire planning and post-fire decision support, to develop improved models, and to explore general patterns of individual fire-induced tree death. The database can also be used to identify knowledge gaps that could be addressed in future research.

Scientific Data↗
USGS2022

Geomorphic controls on floodplain connectivity, ecosystem services, and sensitivity to climate change: An example from the lower Missouri River

Floodplains of large rivers are exploited for agricultural production, industrial and municipal development, and transportation infrastructure. Recently, increased frequency of costly floods has prompted consideration of whether offsetting benefits might accrue from management of floodplains for ecosystem services. We employed a simple inundation model for 800 km of the Lower Missouri River, USA, to evaluate spatial and temporal distributions of ecological floodplain inundation metrics and how those distributions might vary with levee removal and climatic change. The model evaluates inundation at 30 × 30 m resolution on a daily basis over 82 years of record. We quantified provisioning of waterfowl habitat and potential denitrification. Spatial variability is affected by ongoing geomorphic adjustments that affect floodplain connectivity. Statistical models indicate that available floodplain area and recent aggradation are predictive of most inundation metrics. Connectivity is sensitive to climate-change scenarios that predict increased floodplain inundation during spring waterfowl migrations; the greatest sensitivity to future climate exists where channel-floodplain geomorphology presently enhances floodplain connectivity. Evaluation of floodplain denitrification indicates that on average, the nonleveed part of the floodplain could denitrify 0.05%–1.7% of the mean annual nitrogen load of the river. Levee removal could increase this rate to only 3.6% of the nitrogen load. The capacity of floodplain connectivity to influence certain ecosystem services is highly variable in space along the Lower Missouri River and may be appreciably influenced by climate change. Hence, decisions to optimize management of large-river floodplains are likely to be highly location dependent.

Illinois, Iowa, Kansas, Missouri, Nebraska, South ↗
USGS2013

CO 2 uptake and ecophysiological parameters of the grain crops of midcontinent North America: estimates from flux tower measurements

We analyzed net CO 2 exchange data from 13 flux tower sites with 27 site-years of measurements over maize and wheat fields across midcontinent North America. A numerically robust “light-soil temperature-VPD”-based method was used to partition the data into photosynthetic assimilation and ecosystem respiration components. Year-round ecosystem-scale ecophysiological parameters of apparent quantum yield, photosynthetic capacity, convexity of the light response, respiration rate parameters, ecological light-use efficiency, and the curvature of the VPD-response of photosynthesis for maize and wheat crops were numerically identified and interpolated/extrapolated. This allowed us to gap-fill CO 2 exchange components and calculate annual totals and budgets. VPD-limitation of photosynthesis was systematically observed in grain crops of the region (occurring from 20 to 120 days during the growing season, depending on site and year), determined by the VPD regime and the numerical value of the curvature parameter of the photosynthesis-VPD-response, σ VPD . In 78% of the 27 site-years of observations, annual gross photosynthesis in these crops significantly exceeded ecosystem respiration, resulting in a net ecosystem production of up to 2100 g CO 2 m −2 year −1 . The measurement-based photosynthesis, respiration, and net ecosystem production data, as well as the estimates of the ecophysiological parameters, provide an empirical basis for parameterization and validation of mechanistic models of grain crop production in this economically and ecologically important region of North America.

Agriculture, Ecosystems and Environment↗
USGS2021

Developing species-age cohorts from forest inventory and analysis data to parameterize a forest landscape model

Simulating long-term, landscape level changes in forest composition requires estimates of stand age to initialize succession models. Detailed stand ages are rarely available, and even general information on stand history often is lacking. We used data from USDA Forest Service Forest Inventory and Analysis (FIA) database to estimate broad age classes for a forested landscape to simulate changes in landscape composition and structure relative to climate change at Fort Drum, a 43,000 ha U.S. Army installation in northwestern New York. Using simple linear regression, we developed relationships between tree diameter and age for FIA site trees from the host and adjacent ecoregions and applied those relationships to forest stands at Fort Drum. We observed that approximately half of the variation in age was explained by diameter breast height (DBH) across all species studied ( r 2 = 0.42 for sugar maple Acer saccharum to 0.63 for white ash Fraxinus americana ). We then used age-diameter relationships from published research on northern hardwood species to calibrate results from the FIA-based analysis. With predicted stand age, we used tree species life histories and environmental conditions represented by ecological site types to parameterize a stochastic forest landscape model (LANDIS-II) to spatially and temporally model successional changes in forest communities at Fort Drum. Forest stands modeled over 100 years without significant disturbance appeared to reflect expected patterns of increasing dominance by shade-tolerant mesophytic tree species such as sugar maple, red maple ( Acer rubrum ), and eastern hemlock ( Tsuga canadensis ) where soil moisture was sufficient. On drier sandy soils, eastern white pine ( Pinus strobus ), red pine ( P. resinosa ), northern red oak ( Quercus rubra ), and white oak ( Q. alba ) continued to be important components throughout the modeling period with no net loss at the landscape scale. Our results suggest that despite abundant precipitation and relatively low evapotranspiration rates for the region, low soil water holding capacity and fertility may be limiting factors for the spread of mesophytic species on excessively drained soils in the region. Increasing atmospheric temperatures projected for the region could alter moisture regimes for many coarse-textured soils providing a possible mechanism for expansion of xerophytic tree species.

New York↗
USGS2023

Both Landsat- and LiDAR-derived measures predict forest bee response to large-scale wildfire

Large-scale disturbances such as wildfire can have profound impacts on the composition, structure, and functioning of ecosystems. Bees are critical pollinators in natural settings and often respond positively to wildfires, particularly in forests where wildfire leads to more open conditions and increased floral resources. The use of Light Detection and Ranging (LiDAR) provides opportunities for quantifying habitat features across large spatial scales and is increasingly available to scientists and land managers for post-fire habitat assessment. We evaluated the extent to which LiDAR-derived forest structure measurements can predict forest bee communities after a large, mixed-severity fire. We hypothesized that LiDAR measurements linked to post-fire forest structure would improve our ability to predict bee abundance and species richness when compared to satellite-based maps of burn severity. To test this hypothesis, we sampled wild bee communities within the Douglas Fire Complex in southwestern Oregon, USA. We then used LiDAR and Landsat data to quantify forest structure and burn severity, respectively, across bee sampling locations. We found that the LiDAR forest structure model was the best predictor of abundance, whereas the Landsat burn severity model had better predictive ability for species richness. Furthermore, the Landsat burn severity model was better at predicting the presence and species richness of bumble bees (Bombus spp.), an ecologically distinct and economically important group within the Pacific Northwest. We posit that the divergent responses of the two modeling approaches are due to distinct responses by bee taxa to variation in forest structure as mediated by wildfire, with bumble bees in particular depending on closed-canopy forest for some portions of their life cycle. Our study demonstrates that LiDAR data can provide information regarding the drivers of bee abundance in post-wildfire conifer forest, and that both remote sensing approaches are useful for predicting components of wild bee diversity after large-scale wildfire.

Oregon↗
USGS2024

Predicting responses to climate change using a joint species, spatially dependent physiologically guided abundance model

Predicting the effects of warming temperatures on the abundance and distribution of organisms under future climate scenarios often requires extrapolating species–environment correlations to climatic conditions not currently experienced by a species, which can result in unrealistic predictions. For poikilotherms, incorporating species' thermal physiology to inform extrapolations under novel thermal conditions can result in more realistic predictions. Furthermore, models that incorporate species and spatial dependencies may improve predictions by capturing correlations present in ecological data that are not accounted for by predictor variables. Here, we present a joint species, spatially dependent physiologically guided abundance (jsPGA) model for predicting multispecies responses to climate warming. The jsPGA model uses a basis function approach to capture both species and spatial dependencies. We apply the jsPGA model to predict the response of eight fish species to projected climate warming in thousands of lakes in Minnesota, USA. By the end of the century, the cold-adapted species was predicted to have high probabilities of extirpation across its current range—with 10% of lakes currently inhabited by this species having an extirpation probability >0.90. The remaining species had varying levels of predicted changes in abundance, reflecting differences in their thermal physiology. Though the model did not identify many strong species dependencies, the variation in estimated spatial dependence across species suggested that accounting for both dependencies was important for predicting the abundance of these fishes. The jsPGA model provides a new tool for predicting changes in the abundance, distribution, and extirpation probability of poikilotherms under novel thermal conditions.

Minnesota↗
USGS2021

Identifying mismatches between conservation area networks and vulnerable populations using spatial randomization

Grassland birds are among the most globally threatened bird groups due to substantial degradation of native grassland habitats. However, the current network of grassland conservation areas may not be adequate for halting population declines and biodiversity loss. Here, we evaluate a network of grassland conservation areas within Wisconsin, U.S.A., that includes both large Focal Landscapes and smaller targeted conservation areas (e.g., Grassland Bird Conservation Areas, GBCAs) established within them. To date, this conservation network has lacked baseline information to assess whether the current placement of these conservation areas aligns with population hot spots of grassland-dependent taxa. To do so, we fitted data from thousands of avian point-count surveys collected by citizen scientists as part of Wisconsin's Breeding Bird Atlas II with multinomial N -mixture models to estimate habitat–abundance relationships, develop spatially explicit predictions of abundance, and establish ecological baselines within priority conservation areas for a suite of obligate grassland songbirds. Next, we developed spatial randomization tests to evaluate the placement of this conservation network relative to randomly placed conservation networks. Overall, less than 20% of species statewide populations were found within the current grassland conservation network. Spatial tests demonstrated a high representation of this bird assemblage within the entire conservation network, but with a bias toward birds associated with moderately tallgrasses relative to those associated with shortgrasses or tallgrasses. We also found that GBCAs had higher representation at Focal Landscape rather than statewide scales. Here, we demonstrated how combining citizen science data with hierarchical modeling is a powerful tool for estimating ecological baselines and conducting large-scale evaluations of an existing conservation network for multiple grassland birds. Our flexible spatial randomization approach offers the potential to be applied to other protected area networks and serves as a complementary tool for conservation planning efforts globally.

Wisconsin↗
USGS2016

Assessing models of speciation under different biogeographic scenarios; An empirical study using multi-locus and RNA-seq analyses

Evolutionary biology often seeks to decipher the drivers of speciation, and much debate persists over the relative importance of isolation and gene flow in the formation of new species. Genetic studies of closely related species can assess if gene flow was present during speciation, because signatures of past introgression often persist in the genome. We test hypotheses on which mechanisms of speciation drove diversity among three distinct lineages of desert tortoise in the genus Gopherus . These lineages offer a powerful system to study speciation, because different biogeographic patterns (physical vs. ecological segregation) are observed at opposing ends of their distributions. We use 82 samples collected from 38 sites, representing the entire species' distribution and generate sequence data for mtDNA and four nuclear loci. A multilocus phylogenetic analysis in *BEAST estimates the species tree. RNA‐seq data yield 20,126 synonymous variants from 7665 contigs from two individuals of each of the three lineages. Analyses of these data using the demographic inference package ∂a∂i serve to test the null hypothesis of no gene flow during divergence. The best‐fit demographic model for the three taxa is concordant with the *BEAST species tree, and the ∂a∂i analysis does not indicate gene flow among any of the three lineages during their divergence. These analyses suggest that divergence among the lineages occurred in the absence of gene flow and in this scenario the genetic signature of ecological isolation (parapatric model) cannot be differentiated from geographic isolation (allopatric model).

Ecology and Evolution↗
USGS2024

Multi-decadal trophic shifts in Lake Erie yellow perch Perca flavescens

In Lake Erie, yellow perch Perca flavescens support vast commercial and recreational fisheries, yet populations have recently declined. Using N = 5889 yellow perch stomachs collected from 1997 to 2021, we explored trends in the feeding ecology and trophic level of yellow perch with generalized additive models. Models revealed a significant decrease in yellow perch trophic level (−0.15 trophic levels in the last decade), and significant dietary shifts. Yellow perch have shifted away from feeding on piscine prey and round goby Neogobius melanostomus over the 25-year period, and now feed on invertebrates more frequently—including invasive waterfleas ( Bythotrephes longimanus and Cercopagis pengoi ) and chironomids. Dietary patterns appear to reflect broad ecological changes—invasive waterfleas have proliferated while populations of forage fish and round goby have declined. Furthermore, hypoxia events have increased in duration and severity, which may explain observed increases in chironomid consumption, which are hypoxia tolerant. This study demonstrates trophic adaptability in yellow perch, which have changed feeding behavior and trophic position in response to novel invaders and changing environmental conditions.

Lake Erie↗
USGS2021

Historical changes in plant water use and need in the continental United States

A robust method for characterizing the biophysical environment of terrestrial vegetation uses the relationship between Actual Evapotranspiration (AET) and Climatic Water Deficit (CWD). These variables are usually estimated from a water balance model rather than measured directly and are often more representative of ecologically-significant changes than temperature or precipitation. We evaluate trends and spatial patterns in AET and CWD in the Continental United States (CONUS) during 1980–2019 using a gridded water balance model. The western US had linear regression slopes indicating increasing CWD and decreasing AET (drying), while the eastern US had generally opposite trends. When limits to plant performance characterized by AET and CWD are exceeded, vegetation assemblages change. Widespread increases in aridity throughout the west portends shifts in the distribution of plants limited by available moisture. A detailed look at Sequoia National Park illustrates the high degree of fine-scale spatial variability that exists across elevation and topographical gradients. Where such topographical and climatic diversity exists, appropriate use of our gridded data will require sub-setting to an appropriate area and analyzing according to categories of interest such as vegetation communities or across obvious physical gradients. Recent studies have successfully applied similar water balance models to fire risk and forest structure in both western and eastern U.S. forests, arid-land spring discharge, amphibian colonization and persistence in wetlands, whitebark pine mortality and establishment, and the distribution of arid-land grass species and landscape scale vegetation condition. Our gridded dataset is available free for public use. Our findings illustrate how a simple water balance model can identify important trends and patterns at site to regional scales. However, at finer scales, environmental heterogeneity is driving a range of responses that may not be simply characterized by a single trend.

PLoS ONE↗
USGS2017

Moving forward in circles: Challenges and opportunities in modeling population cycles

Population cycling is a widespread phenomenon, observed across a multitude of taxa in both laboratory and natural conditions. Historically, the theory associated with population cycles was tightly linked to pairwise consumer–resource interactions and studied via deterministic models, but current empirical and theoretical research reveals a much richer basis for ecological cycles. Stochasticity and seasonality can modulate or create cyclic behaviour in non-intuitive ways, the high-dimensionality in ecological systems can profoundly influence cycling, and so can demographic structure and eco-evolutionary dynamics. An inclusive theory for population cycles, ranging from ecosystem-level to demographic modelling, grounded in observational or experimental data, is therefore necessary to better understand observed cyclical patterns. In turn, by gaining better insight into the drivers of population cycles, we can begin to understand the causes of cycle gain and loss, how biodiversity interacts with population cycling, and how to effectively manage wildly fluctuating populations, all of which are growing domains of ecological research.

Ecology Letters↗
USGS2025

Environmental drivers of productivity explain population patterns of an Arctic-nesting goose across a half-century

Joint estimation of demographic rates and population size has become an essential tool in ecology because it enables evaluating mechanisms for population change and testing hypotheses about drivers of demography in a single modeling framework. This approach provides a comprehensive perspective on population dynamics and how animal populations will respond to global pressures in future years. However, long-term data for such analyses are often limited in quantity and quality. We developed an integrated population model combining data on demography and population size from nine different sources to understand the population ecology of the lesser snow goose ( Anser caerulescens caerulescens ) in the Pacific Flyway in North America from 1970 to 2022. We divided the flyway population into Wrangel Island and Western Arctic subpopulations and assessed demographic mechanisms for population change and environmental and anthropogenic drivers that influenced demography. During 1970–2022, the estimated spring population of snow geese in the Pacific Flyway increased from ~300,000 to ~2,300,000. Short-term changes in population growth rate were primarily driven by changes in productivity in the Western Arctic and productivity and immigration in Wrangel Island. Changes in hunting and natural mortality had less influence on short-term but likely contributed to the pronounced long-term population growth. Early snowmelt positively influenced per capita productivity in both regions, and warm, rainy weather during the non-breeding season was associated with high per capita productivity in the Western Arctic. In the Western Arctic, per capita productivity was negatively associated with population size, and adult natural mortality was positively associated with population size, indicating density-dependent regulation in this subpopulation. In Wrangel Island, warm weather in early fall decreased juvenile natural mortality. Our results demonstrate that per capita productivity and immigration, rather than adult survival, were the primary mechanisms of short-term population change in this long-lived species. Our results also indicate that environmental conditions and density-dependent effects can impact population dynamics more than harvest, even for a long-lived, commonly harvested species. We demonstrate that a warming climate can have multiple effects on demography, emphasizing the importance of assessing a variety of spatial and temporal factors when predicting how populations might respond to large-scale environmental changes. This emphasizes the importance of conservation plans that consider these environmental drivers, although this may complicate direct management of such populations.

Ecological Applications↗
USGS2020

Identifying candidate reference reaches to assess the physical and biological integrity of wadeable streams in different ecoregions and among stream sizes

Efforts to quantify disturbances to aquatic systems often use landscape-level metrics, presumably linked to ecological integrity, but fewer studies have directly linked ecological integrity to instream habitat, and applied these results to unsampled stream reaches throughout a landscape. We developed a flexible, quantitative approach that characterizes stream impairment across a landscape and identifies least-disturbed stream reaches to serve as benchmarks for high quality physical habitat and ecological integrity. Fish and macroinvertebrate community characteristics, reach-level physical habitat and water quality metrics were summarized in 891 wadeable stream reaches across two ecoregions in Missouri, USA. The influence of reach and water-quality characteristics as well as landscape-level variables on 7 fish and 3 macroinvertebrate community biological indicator metrics was then modeled using boosted regression trees (BRTs). On average, reach-level models explained more variance (25 and 27% in the two ecoregions examined) in biotic metrics than landscape-level models (18% and 20%). Abiotic and biotic associations differed among ecoregions and stream sizes, however, reach-level habitat (e.g., bankfull width/depth ratio, channel incision height) and water quality (e.g., dissolved oxygen, total chlorophyll) were consistently top predictors. At the landscape scale, fish richness in the agriculturally dominated ecoregion increased with decreased fragmentation/flow modification, while invertebrate metrics responded to agricultural disturbances. Invertebrate metrics in the forested ecoregion showed community degradation apparent with crop coverage as low as 8-10% of the riparian zone, while urban impairment was best detected using invertebrate indicators of biotic integrity and measures of fish trophic ecology. Relationships among landscape-scale variables and reach characteristics identified as top predictors in BRTs also highlighted potential mechanistic relationships among landscape, habitat, and measures of ecological integrity. Using the results of the landscape-level models, estimates for overall ecological integrity were predicted for over 28,000 stream reaches throughout Missouri, and a total of 1,423 candidate reference reaches were identified. The objective approach to characterizing stream impairment developed in this study offers specific advantages, including a reach and landscape-level evaluation of human disturbance as well as an inductive, multi-metric determination of ecological integrity.

Missouri↗
USGS2015

Characterization of shrubland ecosystem components as continuous fields in the northwest United States

Accurate and consistent estimates of shrubland ecosystem components are crucial to a better understanding of ecosystem conditions in arid and semiarid lands. An innovative approach was developed by integrating multiple sources of information to quantify shrubland components as continuous field products within the National Land Cover Database (NLCD). The approach consists of several procedures including field sample collections, high-resolution mapping of shrubland components using WorldView-2 imagery and regression tree models, Landsat 8 radiometric balancing and phenological mosaicking, medium resolution estimates of shrubland components following different climate zones using Landsat 8 phenological mosaics and regression tree models, and product validation. Fractional covers of nine shrubland components were estimated: annual herbaceous, bare ground, big sagebrush, herbaceous, litter, sagebrush, shrub, sagebrush height, and shrub height. Our study area included the footprint of six Landsat 8 scenes in the northwestern United States. Results show that most components have relatively significant correlations with validation data, have small normalized root mean square errors, and correspond well with expected ecological gradients. While some uncertainties remain with height estimates, the model formulated in this study provides a cross-validated, unbiased, and cost effective approach to quantify shrubland components at a regional scale and advances knowledge of horizontal and vertical variability of these components.

California, Idaho, Nevada, Oregon↗
USGS2009

Modeling individual animal histories with multistate capture–recapture models

Many fields of science begin with a phase of exploration and description, followed by investigations of the processes that account for observed patterns. The science of ecology is no exception, and recent decades have seen a focus on understanding key processes underlying the dynamics of ecological systems. In population ecology, emphasis has shifted from the state variable of population size to the demographic processes responsible for changes in this state variable: birth, death, immigration, and emigration. In evolutionary ecology, some of these same demographic processes, rates of birth and death, are also the determinants of fitness. In animal population ecology, the estimation of state variables and their associated vital rates is especially problematic because of the difficulties in sampling such populations and detecting individual animals. Indeed, early capture–recapture models were developed for the purpose of estimating population size, given the reality that all animals are not caught or detected at any sampling occasion. More recently, capture–recapture models for open populations were developed to draw inferences about survival in the face of these same sampling problems. The focus of this paper is on multi‐state mark–recapture models (MSMR), which first appeared in the 1970s but have undergone substantial development in the last 15 years. These models were developed to deal explicitly with biological variation, in that animals in different “states” (classes defined by location, physiology, behavior, reproductive status, etc.) may have different probabilities of survival and detection. Animal transitions between states are also stochastic and themselves of interest. These general models have proven to be extremely useful and provide a way of thinking about a remarkably wide range of important ecological processes. These methods are now at a stage of refinement and sophistication where they can readily be used by biologists to tackle a wide range of important issues in ecology. In this paper, we draw together information on the state of the art in multistate mark–recapture methods, explaining the models and illustrating their use. We provide a modeling philosophy and a series of general principles on how to conduct analyses. We cover key issues and features, and we anticipate the ways in which we expect the models to develop in the years ahead.

Advances in Ecological Research↗
USGS2006

Report of the USGS Coastal and Marine Geology Modeling Workshop, Pacific Marine Science Center, Santa Cruz, CA, March 22-23, 2005

A U.S. Geological Survey (USGS) Coastal and Marine Geology (CMG) Modeling Workshop was held to discuss the general topic of coastal modeling, defined broadly to include circulation, waves, sediment transport, water quality, ecology, sediment diagenesis, morphology change, and coastal evolution, on scales ranging from seconds and a few centimeters (individual ripples) to centuries (coastal evolution) and thousands of kilometers (tsunami propagation). The workshop was convened at the suggestion of CMG Program Management to improve communication among modelers and model users, assess modeling-related activities being conducted at the three centers (Florida Integrated Science Center, FISC; Pacific Marine Science Center; PMSC; and Woods Hole Science Center; WHSC), and develop goals, strategies, and plans for future modeling activities. The workshop represents a step toward developing a five-year strategic plan, and was timed to provide input for the FY06 prospectus. The workshop was held at the USGS Pacific Marine Science Center in Santa Cruz on March 22-23, 2005.

Open-File Report↗
USGS2007

Patch-occupancy models indicate human activity as major determinant of forest elephant Loxodonta cyclotis seasonal distribution in an industrial corridor in Gabon

The importance of human activity and ecological features in influencing African forest elephant ranging behaviour was investigated in the Rabi-Ndogo corridor of the Gamba Complex of Protected Areas in southwest Gabon. Locations in a wide geographical area with a range of environmental variables were selected for patch-occupancy surveys using elephant dung to assess seasonal presence and absence of elephants. Patch-occupancy procedures allowed for covariate modelling evaluating hypotheses for both occupancy in relation to human activity and ecological features, and detection probability in relation to vegetation density. The best fitting models for old and fresh dung data sets indicate that (1) detection probability for elephant dung is negatively related to the relative density of the vegetation, and (2) human activity, such as presence and infrastructure, are more closely associated with elephant distribution patterns than are ecological features, such as the presence of wetlands and preferred fresh fruit. Our findings emphasize the sensitivity of elephants to human disturbance, in this case infrastructure development associated with gas and oil production. Patch-occupancy methodology offers a viable alternative to current transect protocols for monitoring programs with multiple covariates.

Biological Conservation↗