Simultaneous modeling of habitat suitability, occupancy and relative abundance: case study of African Elephants in Zimbabwe

Florida Cooperative Fish and Wildlife Research Unit, University of Florida, Gainesville, Florida 32611-0485, USA.
Ecological Applications (Impact Factor: 4.09). 06/2010; 20(4):1173-82. DOI: 10.1890/09-0276.1
Source: PubMed

ABSTRACT The recent development of statistical models such as dynamic site occupancy models provides the opportunity to address fairly complex management and conservation problems with relatively simple models. However, surprisingly few empirical studies have simultaneously modeled habitat suitability and occupancy status of organisms over large landscapes for management purposes. Joint modeling of these components is particularly important in the context of management of wild populations, as it provides a more coherent framework to investigate the population dynamics of organisms in space and time for the application of management decision tools. We applied such an approach to the study of water hole use by African elephants in Hwange National Park, Zimbabwe. Here we show how such methodology may be implemented and derive estimates of annual transition probabilities among three dry-season states for water holes: (1) unsuitable state (dry water holes with no elephants); (2) suitable state (water hole with water) with low abundance of elephants; and (3) suitable state with high abundance of elephants. We found that annual rainfall and the number of neighboring water holes influenced the transition probabilities among these three states. Because of an increase in elephant densities in the park during the study period, we also found that transition probabilities from low abundance to high abundance states increased over time. The application of the joint habitat-occupancy models provides a coherent framework to examine how habitat suitability and factors that affect habitat suitability influence the distribution and abundance of organisms. We discuss how these simple models can further be used to apply structured decision-making tools in order to derive decisions that are optimal relative to specified management objectives. The modeling framework presented in this paper should be applicable to a wide range of existing data sets and should help to address important ecological, conservation, and management problems that deal with occupancy, relative abundance, and habitat suitability.

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    • "Among these species, as expected elephants moved the greatest distances. These results agreed with similar studies in Africa and the Americas that have found species often move and inhabit areas outside reserves and this movement changes seasonally (Naughton-Treves et al. 2003; Thirgood et al. 2004; Rannestad et al. 2006; Scholte et al. 2007; Sinclair et al. 2007; Martin et al. 2010). This approach and mapping of species distributions is vital to focusing where species protection efforts need to be specifically targeted and determining which habitat areas need to be monitored to ensure species can move freely. "
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    ABSTRACT: Wildlife reserves are becoming increasingly isolated from the surrounding human-dominated landscapes particularly in Asia. It is imperative to understand how species are distributed spatially and temporally in and outside reserves, and what factors influence their occurrence. This study surveyed 7500 km(2) landscape surrounding five reserves in the Western Ghats to examine patterns of occurrence of five herbivores: elephant, gaur, sambar, chital, and pig. Species distributions are modeled spatio-temporally using an occupancy approach. Trained field teams conducted 3860 interview-based occupancy surveys in a 10-km buffer surrounding these five reserves in 2012. I found gaur and wild pig to be the least and most wide-ranging species, respectively. Elephant and chital exhibit seasonal differences in spatial distribution unlike the other three species. As predicted, distance to reserve, the reserve itself, and forest cover were associated with higher occupancy of all species, and higher densities of people negatively influenced occurrence of all species. Park management, species protection, and conflict mitigation efforts in this landscape need to incorporate temporal and spatial understanding of species distributions. All species are known crop raiders and conflict prone locations with resources (such as water and forage) have to be monitored and managed carefully. Wildlife reserves and adjacent areas are critical for long-term persistence and habitat use for all five herbivores and must be monitored to ensure wildlife can move freely. Such a large-scale approach to map and monitor species distributions can be adapted to other landscapes to identify and monitor critical habitats shared by people and wildlife.
    Environmental Management 08/2015; DOI:10.1007/s00267-015-0595-9 · 1.72 Impact Factor
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    • "Interestingly, several authors have applied the model to estimate habitat and occupancy dynamics by redefining the true states as unsuitable habitat (and thus unoccupied), suitable habitat occupied by no or only few individuals of the target species or suitable habitat occupied by some or many individuals of the target species. Such an approach was applied to study the use of water holes by African elephants (Loxodonta africana ) in Hwange National Park, Zimbabwe (Martin et al. 2010), and the occurrence of larvae of a suite of plains fishes in the Arikaree River, eastern Colorado, USA (Falke et al. 2012). The aim of these studies was to examine how habitat suitability and factors that affect habitat suitability (e.g. "
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    ABSTRACT: The past decade has seen an explosion in the development and application of models aimed at estimating species occurrence and occupancy dynamics while accounting for possible non-detection or species misidentification.We discuss some recent occupancy estimation methods and the biological systems that motivated their development. Collectively, these models offer tremendous flexibility, but simultaneously place added demands on the investigator.Unlike many mark–recapture scenarios, investigators utilizing occupancy models have the ability, and responsibility, to define their sample units (i.e. sites), replicate sampling occasions, time period over which species occurrence is assumed to be static and even the criteria that constitute ‘detection’ of a target species. Subsequent biological inference and interpretation of model parameters depend on these definitions and the ability to meet model assumptions.We demonstrate the relevance of these definitions by highlighting applications from a single biological system (an amphibian–pathogen system) and discuss situations where the use of occupancy models has been criticized. Finally, we use these applications to suggest future research and model development.
    Methods in Ecology and Evolution 09/2013; 5(12). DOI:10.1111/2041-210X.12100 · 6.55 Impact Factor
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    • "While occupancy models typically assume that data have two states (i.e., presence and absence), the models have recently been extended to include multiple states (Nichols et al. 2007). Such multistate occupancy models have increased relevance to situations where conservation and habitat management are of interest , because they allow the investigator to consider multiple biologically relevant states (Martin et al. 2010). Multistate occupancy is commonly thought of as being applicable to situations in which temporal changes in animal aggregations or migration patterns are evident (e.g., movements during a breeding season), such that at different times detectability and occupancy would change based on a species' life history (MacKenzie et al. 2009; Martin et al. 2009). "
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    ABSTRACT: We used multiseason, multistate patch occupancy models to investigate habitat use of a regionally rare minnow (bridle shiner, Notropis bifrenatus) within a difficult-to-sample, swampy stream system by defining occupancy states as coarse abundance categories (i.e., none, some, many). Habitat patches were repeatedly subsampled during three sampling periods spanning June to August 2011 using a nonstandard purse-and-lift method with a seine net, as poorly defined shorelines, unconsolidated substrate, and emergent vegetation limited beaching and restricted possible sampling locations. Detection probabilities increased from June to August, likely due to increasing catch per effort as age 0 became vulnerable to the gear, supported by the probability of detection being greater when the species was at high abundance, given occupancy. The probability of a habitat patch being occupied increased with the percent of macrophyte cover and decreased with increasing distance from another occupied patch. Decreasing mean depth showed a weak relationship to high abundance, given a patch was occupied. In summary, the multistate occupancy analytical approach was highly informative for developing quantitative habitat relationships and was seen as an effective framework for evaluating habitat use of aquatic organisms that inhabit environments inherently difficult to sample for which imperfect detection and sampling efficiency are of concern.
    Canadian Journal of Fisheries and Aquatic Sciences 07/2013; 70(10):1429-1437. DOI:10.1139/cjfas-2013-0011 · 2.29 Impact Factor
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