Using occupancy models to investigate space partitioning between two sympatric large predators, the jaguar and puma in central Brazil

Coexistence of sympatric species is mediated by resource partitioning. Pumas occur sympatrically with jaguars throughout most of the jaguar's range but few studies have investigated space partitioning between both species. Here, camera trapping and occupancy models accounting for imperfect detection were employed in a Bayesian framework to investigate space partitioning between the jaguar and puma in Emas National Park (ENP), central Brazil. Jaguars were estimated to occupy 54.1% and pumas 39.3% of the sample sites. Jaguar occupancy was negatively correlated with distance to water and positively correlated with the amount of dense habitat surrounding the camera trap. Puma occupancy only showed a weak negative correlation with distance to water and with jaguar presence. Both species were less often present at the same site than expected under independent distributions. Jaguars had a significantly higher detection probability at cameras on roads than at off-road locations. For pumas, detection was similar on and off-road. Results indicate that both differences in habitat use and active avoidance shape space partitioning between jaguars and pumas in ENP. Considering its size, the jaguar is likely the competitively dominant of the two species. Owing to its habitat preferences, suitable jaguar habitat outside the park is probably sparse. Consequently, the jaguar population is likely largely confined to the park, while the puma population is known to extend into ENP's surroundings. (C) 2011 Deutsche Gesellschaft fur Saugetierkunde. Published by Elsevier GmbH. All rights reserved.

Strong inference from transect sign surveys : combining spatial autocorrelation and misclassification occupancy models to quantify the detectability of a recovering carnivore

Funding — Forest Enterprise Scotland and the University of Aberdeen provided funding for the project. The Carnegie Trust supported the lead author, E. McHenry, in this research through the award of a tuition fees bursary.

Factors affecting southern water vole (Arvicola sapidus) detection and occupancy probabilities in Mediterranean farmland

Failure to detect a species at sites where it is present (i.e. imperfect detection) is known to occur frequently, but this is often disregarded in monitoring programs and metapopulation studies. Here we modelled for the first time the probability of patch occupancy by a threatened small mammal, the southern water vole (Arvicola sapidus, while accounting for the probability of detection given occupancy. Based on replicated presence sign surveys conducted in autumn (November–December 2013) and winter (February–March 2014) in a farmland landscape, we used occupancy detection modelling to test the effects of vegetation, sampling effort, observer experience, and rainfall on detection probability. We then assessed whether occupancy was related to patch size, isolation, vegetation, or presence of water, after correcting for imperfect detection. The mean detection probabilities of water vole signs in autumn (0.71) and winter (0.81) indicated that false absences may be generated in about 20–30% of occupied patches surveyed by a single observer on a single occasion. There was no statistical support for the effects of covariates on detectability. After controlling for imperfect detection, the mean probabilities of occupancy in autumn (0.31) and winter (0.29) were positively related to patch size and presence of water, and negatively so, albeit weakly, to patch isolation. Overall, our study underlined the importance of accounting for imperfect detection in sign surveys of small mammals such as water voles, pointing out the need to use occupancy detection modelling together with replicate surveys for accurately estimating occupancy and the factors affecting it.

Community-managed forests and wildlife-friendly agriculture play a subsidiary but not substitutive role to protected areas for the endangered Asian elephant

Global conservation policy is increasingly debating the feasibility of reconciling wildlife conservation and human resource requirements in land uses outside protected areas (PAs). However, there are few quantitative assessments of whether or to what extent these `wildlife-friendly' land uses fulfill a fundamental function of PAs-to separate biodiversity from anthropogenic threats. We distinguish the role of wildlife-friendly land uses as being (a) subsidiary, whereby they augment PAs with secondary habitat, or (b) substitutive, wherein they provide comparable habitat to PAs. We tested our hypotheses by investigating the influence of land use and human presence on space-use intensity of the endangered Asian elephant (Elephas maximus) in a fragmented landscape comprising PAs and wildlife-friendly land uses. We applied multistate occupancy models to spatial data on elephant occurrence to estimate and model the overall probability of elephants using a site, and the conditional probability of high-intensity use given that elephants use a site. The probability of elephants using a site regardless of intensity did not vary between PAs and wildlife-friendly land uses. However, high-intensity use declined with distance to PM, and this effect was accentuated by an increase in village density. Therefore, while wildlife-friendly land uses did play a subsidiary conservation role, their potential to substitute for PAs was offset by a strong human presence. Our findings demonstrate the need to evaluate the role of wildlife-friendly land uses in landscape-scale conservation; for species that have conflicting resource requirements with people, PAs are likely to provide crucial refuge from growing anthropogenic threats. (C) 2014 Elsevier Ltd. All rights reserved.

Protected area networks and savannah bird biodiversity in the face of climate change and land degradation

The extent to which climate change might diminish the efficacy of protected areas is one of the most pressing conservation questions. Many projections suggest that climate-driven species distribution shifts will leave protected areas impoverished and species inadequately protected while other evidence suggests that intact ecosystems within protected areas will be resilient to change. Here, we tackle this problem empirically. We show how recent changes in distribution of 139 Tanzanian savannah bird species are linked to climate change, protected area status and land degradation. We provide the first evidence of climate-driven range shifts for an African bird community. Our results suggest that the continued maintenance of existing protected areas is an appropriate conservation response to the challenge of climate and environmental change.

Hide-and-seek in vegetation: time-to-detection is an efficient design for estimating detectability and occurrence

Ecology and conservation require reliable data on the occurrence of animals and plants. A major source of bias is imperfect detection, which, however, can be corrected for by estimation of detectability. In traditional occupancy models, this requires repeat or multi-observer surveys. Recently, time-to-detection models have been developed as a cost-effective alternative, which requires no repeat surveys and hence costs could be halved. We compared the efficiency and reliability of time-to-detection and traditional occupancy models under varying survey effort. Two observers independently searched for 17 plant species in 44100m(2) Swiss grassland quadrats and recorded the time-to-detection for each species, enabling detectability to be estimated with both time-to-detection and traditional occupancy models. In addition, we gauged the relative influence on detectability of species, observer, plant height and two measures of abundance (cover and frequency). Estimates of detectability and occupancy under both models were very similar. Rare species were more likely to be overlooked; detectability was strongly affected by abundance. As a measure of abundance, frequency outperformed cover in its predictive power. The two observers differed significantly in their detection ability. Time-to-detection models were as accurate as traditional occupancy models, but their data easier to obtain; thus they provide a cost-effective alternative to traditional occupancy models for detection-corrected estimation of occurrence.

Detection histories for eight species of Amazona parrots in Venezuela during the NeoMaps bird surveys in 2010

Documenting changes in distribution is necessary for understanding species' response to environmental changes, but data on species distributions are heterogeneous in accuracy and resolution. Combining different data sources and methodological approaches can fill gaps in knowledge about the dynamic processes driving changes in species-rich, but data-poor regions. We combined recent bird survey data from the Neotropical Biodiversity Mapping Initiative (NeoMaps) with historical distribution records to estimate potential changes in the distribution of eight species of Amazon parrots in Venezuela. Using environmental covariates and presence-only data from museum collections and the literature, we first used maximum likelihood to fit a species distribution model (SDM) estimating a historical maximum probability of occurrence for each species. We then used recent, NeoMaps survey data to build single-season occupancy models (OM) with the same environmental covariates, as well as with time- and effort-dependent detectability, resulting in estimates of the current probability of occurrence. We finally calculated the disagreement between predictions as a matrix of probability of change in the state of occurrence. Our results suggested negative changes for the only restricted, threatened species, Amazona barbadensis, which has been independently confirmed with field studies. Two of the three remaining widespread species that were detected, Amazona amazonica, Amazona ochrocephala, also had a high probability of negative changes in northern Venezuela, but results were not conclusive for Amazona farinosa. The four remaining species were undetected in recent field surveys; three of these were most probably absent from the survey locations (Amazona autumnalis, Amazona mercenaria and Amazona festiva), while a fourth (Amazona dufresniana) requires more intensive targeted sampling to estimate its current status. Our approach is unique in taking full advantage of available, but limited data, and in detecting a high probability of change even for rare and patchily-distributed species. However, it is presently limited to species meeting the strong assumptions required for maximum-likelihood estimation with presence-only data, including very high detectability and representative sampling of its historical distribution.

European mink (Mustela lutreola) and American mink (Neovison vison) detection histories in Northern Spain between 2000 and 2011

Understanding changes over time in the distribution of interacting native and invasive species that may be symptomatic of competitive exclusion is critical to identify the need for and effectiveness of management interventions. Occupancy models greatly increase the robustness of inference that can be made from presence/absence data when species are imperfectly detected, and recent novel developments allow for the quantification of the strength of interaction between pairs of species. We used a two-species multi-season occupancy model to quantify the impact of the invasive American mink on the native European mink in Spain through the analysis of their co-occurrence pattern over twelve years (2000 - 2011) in the entire Spanish range of European mink distribution, where both species were detected by live trapping but American mink were culled. We detected a negative temporal trend in the rate of occupancy of European mink and a simultaneous positive trend in the occupancy of American mink. The species co-occurred less often than expected and the native mink was more likely to become extinct from sites occupied by the invasive species. Removal of American mink resulted in a high probability of local extinction where it co-occurred with the endemic mink, but the overall increase in the probability of occupancy over the last decade indicates that the ongoing management is failing to halt its spread. More intensive culling effort where both species co-exist as well as in adjacent areas where the invasive American mink is found at high densities is required in order to stop thedecline of European mink.

Corrected mean-field models for spatially-dependent advection-diffusion-reaction phenomena

In the exclusion-process literature, mean-field models are often derived by assuming that the occupancy status of lattice sites is independent. Although this assumption is questionable, it is the foundation of many mean-field models. In this work we develop methods to relax the independence assumption for a range of discrete exclusion process-based mechanisms motivated by applications from cell biology. Previous investigations that focussed on relaxing the independence assumption have been limited to studying initially-uniform populations and ignored any spatial variations. By ignoring spatial variations these previous studies were greatly simplified due to translational invariance of the lattice. These previous corrected mean-field models could not be applied to many important problems in cell biology such as invasion waves of cells that are characterised by moving fronts. Here we propose generalised methods that relax the independence assumption for spatially inhomogeneous problems, leading to corrected mean-field descriptions of a range of exclusion process-based models that incorporate (i) unbiased motility, (ii) biased motility, and (iii) unbiased motility with agent birth and death processes. The corrected mean-field models derived here are applicable to spatially variable processes including invasion wave type problems. We show that there can be large deviations between simulation data and traditional mean-field models based on invoking the independence assumption. Furthermore, we show that the corrected mean-field models give an improved match to the simulation data in all cases considered.

Object identification based on 3D spatial models of construction sites

On obstacle-cluttered construction sites, understanding the motion characteristics of objects is important for anticipating collisions and preventing accidents. This study investigates algorithms for object identification applications that can be used by heavy equipment operators to effectively monitor congested local environment. The proposed framework contains algorithms for three-dimensional spatial modeling and image matching that are based on 3D images scanned by a high-frame rate range sensor. The preliminary results show that an occupancy grid spatial modeling algorithm can successfully build the most pertinent spatial information, and that an image matching algorithm is best able to identify which objects are in the scanned scene.

Incorporating spatial correlations into multispecies mean-field models

In biology, we frequently observe different species existing within the same environment. For example, there are many cell types in a tumour, or different animal species may occupy a given habitat. In modelling interactions between such species, we often make use of the mean field approximation, whereby spatial correlations between the locations of individuals are neglected. Whilst this approximation holds in certain situations, this is not always the case, and care must be taken to ensure the mean field approximation is only used in appropriate settings. In circumstances where the mean field approximation is unsuitable we need to include information on the spatial distributions of individuals, which is not a simple task. In this paper we provide a method that overcomes many of the failures of the mean field approximation for an on-lattice volume-excluding birth-death-movement process with multiple species. We explicitly take into account spatial information on the distribution of individuals by including partial differential equation descriptions of lattice site occupancy correlations. We demonstrate how to derive these equations for the multi-species case, and show results specific to a two-species problem. We compare averaged discrete results to both the mean field approximation and our improved method which incorporates spatial correlations. We note that the mean field approximation fails dramatically in some cases, predicting very different behaviour from that seen upon averaging multiple realisations of the discrete system. In contrast, our improved method provides excellent agreement with the averaged discrete behaviour in all cases, thus providing a more reliable modelling framework. Furthermore, our method is tractable as the resulting partial differential equations can be solved efficiently using standard numerical techniques.

Building macroscale models from microscale probabilistic models : a general probabilistic approach for nonlinear diffusion and multispecies phenomena

A discrete agent-based model on a periodic lattice of arbitrary dimension is considered. Agents move to nearest-neighbor sites by a motility mechanism accounting for general interactions, which may include volume exclusion. The partial differential equation describing the average occupancy of the agent population is derived systematically. A diffusion equation arises for all types of interactions and is nonlinear except for the simplest interactions. In addition, multiple species of interacting subpopulations give rise to an advection-diffusion equation for each subpopulation. This work extends and generalizes previous specific results, providing a construction method for determining the transport coefficients in terms of a single conditional transition probability, which depends on the occupancy of sites in an influence region. These coefficients characterize the diffusion of agents in a crowded environment in biological and physical processes.

Statistical thermodynamics of lattice models in zeolites: Implications of local versus global mean field interactions

The statistical thermodynamics of adsorption in caged zeolites is developed by treating the zeolite as an ensemble of M identical cages or subsystems. Within each cage adsorption is assumed to occur onto a lattice of n identical sites. Expressions for the average occupancy per cage are obtained by minimizing the Helmholtz free energy in the canonical ensemble subject to the constraints of constant M and constant number of adsorbates N. Adsorbate-adsorbate interactions in the Brag-Williams or mean field approximation are treated in two ways. The local mean field approximation (LMFA) is based on the local cage occupancy and the global mean field approximation (GMFA) is based on the average coverage of the ensemble. The GMFA is shown to be equivalent in formulation to treating the zeolite as a collection of interacting single site subsystems. In contrast, the treatment in the LMFA retains the description of the zeolite as an ensemble of identical cages, whose thermodynamic properties are conveniently derived in the grand canonical ensemble. For a z coordinated lattice within the zeolite cage, with epsilon(aa) as the adsorbate-adsorbate interaction parameter, the comparisons for different values of epsilon(aa)(*)=epsilon(aa)z/2kT, and number of sites per cage, n, illustrate that for -1 0. We compare the isotherms predicted with the LMFA with previous GMFA predictions [K. G. Ayappa, C. R. Kamala, and T. A. Abinandanan, J. Chem. Phys. 110, 8714 (1999)] (which incorporates both the site volume reduction and a coverage-dependent epsilon(aa)) for xenon and methane in zeolite NaA. In all cases the predicted isotherms are very similar, with the exception of a small steplike feature present in the LMFA for xenon at higher coverages. (C) 1999 American Institute of Physics. [S0021-9606(99)70333-8].

Agent-based parking occupancy simulation

The existing parking simulations, as most simulations, are intended to gain insights of a system or to make predictions. The knowledge they have provided has built up over the years, and several research works have devised detailed parking system models. This thesis work describes the use of an agent-based parking simulation in the context of a bigger parking system development. It focuses more on flexibility than on fidelity, showing the case where it is relevant for a parking simulation to consume dynamically changing GIS data from external, online sources and how to address this case. The simulation generates the parking occupancy information that sensing technologies should eventually produce and supplies it to the bigger parking system. It is built as a Java application based on the MASON toolkit and consumes GIS data from an ArcGis Server. The application context of the implemented parking simulation is a university campus with free, on-street parking places.