Mesoscale movement and recursion behaviors of Namibian black rhinos.

Background:Understanding rhino movement behavior, especially their recursive movements, holds significant promise for enhancing rhino conservation efforts, and protecting their habitats and the biodiversity they support. Here we investigate the daily, biweekly, and seasonal recursion behavior of rhinos, to aid conservation applications and increase our foundational knowledge about these important ecosystem engineers. Methods:Using relocation data from 59 rhinos across northern Namibia and 8 years of sampling efforts, we investigated patterns in 24-h displacement at dawn, dusk, midday, and midnight to examine movement behaviors at an intermediate scale and across daily behavioral modes of foraging and resting. To understand recursion patterns across animals' short and long-term ranges, we built T-LoCoH time use grids to estimate recursive movement by each individual. Comparing these grids to contemporaneous MODIS imagery, we investigated productivity's influence on short-term space use and recursion. Finally, we investigated patterns of recursion within a year's home range, measuring the time to return to the most intensively used patches. Results:Twenty four-hour displacements at dawn were frequently smaller than 24-h displacements at dusk or at midday and midnight resting periods. Recursion analyses demonstrated that short-term recursion was most common in areas of median rather than maximum NDVI values. Investigated across a full year, recursion analysis showed rhinos most frequently returned to areas within 8-21 days, though visits were also seen separated by months likely suggesting seasonality in range use. Conclusions:Our results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Recursion across larger time scales is also evident, and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna

Extensible tools for movement ecology with applications for the study and conservation of Namibian ungulates

Movement ecology is a young sub-discipline in ecology in which researchers apply high resolution location and activity data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses con-tribute to various other subfields within ecology—inter alia behavioral, disease, landscape, resource, and wildlife—and may also facilitate novel exploration in fields ranging from conservation planning to public health.Using a decade of GPS relocation data from zebra (Equus quagga), black rhino (Diceros bicornis), and African elephant (Loxodonta africana) captured and collared in Etosha National Park from 2008-2018, this dissertation reviews developing methods within movement ecology, extends and applies these methods to a threatened and understudied species, and presents a new software package distilling a growing movement ecology tool set for researchers and managers unfamiliar with the domain specific analyses and/or the command line interface of modern statistical analysis (e.g. R).Despite the growing availability of animal movement data and the potential for broad application in geographic analysis beyond animal ecology, the analytical methods of movement ecology have yet to be fully incorporated in a broader understanding of geographic analysis. Chapter 2, a review written for the Geographical Information Sciences (GIS) community, provides an overview of the most common movement metrics and methods of analysis em-ployed by animal ecologists and emphasizes the potential for movement analyses to promote transdisciplinary research: comparing advances in the young field of movement ecology to parallel developments within the broader field of geographic information sciences.Two limitations remain common within the growing field of movement analysis. First, within movement ecology, many, even most, analyses require clean, complete, and regular time series of relocations, limiting the available research on species that are hard to track and/or often return gappy, irregular data; including some of the world’s most endangered animals, e.g. black rhinos. In chapter 3, extending and applying recursion analyses to irregular spatio-temporal data from this understudied and critically endangered species, I investigated daily, biweekly and annual recursion behaviors of rhinos, to aid conservation applications and increase our fundamental knowledge about these important ecosystem engineers. Results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Initial results indicate that recursion at the daily and biweekly scales maybe driven by hydration and productivity cycles respectively. Recursion across larger timescales is also evident and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna.A second, and equally challenging, limitation to the growing movement ecology tool kit is accessibility. The growth in analysis techniques, and the concomitant growth of open-source software for analysis, pose a stumbling block to general acceptance in interdisciplinary and management settings, where researchers may be unfamiliar with the expansive set of tools or the command line interface of modern analysis packages. In chapter 4, to reduce this friction and enhance the accessibility of exploratory data analysis tools for animal movement data, I built stmove, an R package designed to make report building and exploratory data analysis simple for users who may not be familiar with the extent of available analytical tools. Furthermore, stmove sets forth a framework of best practice analyses, which offers a common starting point for the interpretation of terrestrial movement data, promoting comparability of results across movement ecology studies.The datasets, analyses, and tools presented in this dissertation seek to enhance communication, application, and accessibility of a growing movement ecology toolkit while providing a special glimpse into a diverse ecological community and the individual and population movement behavior through within Etosha National Park over the last decade. We demonstrate new tools built for exploratory data analysis in movement ecology using this data and explore how insights from movement ecology can help inform successful conservation efforts in the region and beyond

Extensible Tools for Movement Ecology with Applications for the Study and Conservation of Namibian Ungulates

Movement ecology is a young sub-discipline in ecology in which researchers apply high resolution location and activity data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses con-tribute to various other subfields within ecology—inter alia behavioral, disease, landscape, resource, and wildlife—and may also facilitate novel exploration in fields ranging from conservation planning to public health. Using a decade of GPS relocation data from zebra (Equus quagga), black rhino (Diceros bicornis), and African elephant (Loxodonta africana) captured and collared in Etosha National Park from 2008–2018, this dissertation reviews developing methods within movement ecology, extends and applies these methods to a threatened and understudied species, and presents a new software package distilling a growing movement ecology tool set for researchers and managers unfamiliar with the domain specific analyses and/or the command line interface of modern statistical analysis (e.g. R). Despite the growing availability of animal movement data and the potential for broad application in geographic analysis beyond animal ecology, the analytical methods of movement ecology have yet to be fully incorporated in a broader understanding of geographic analysis. Chapter 2, a review written for the Geographical Information Sciences (GIS) community, provides an overview of the most common movement metrics and methods of analysis em-ployed by animal ecologists and emphasizes the potential for movement analyses to promote transdisciplinary research: comparing advances in the young field of movement ecology to parallel developments within the broader field of geographic information sciences. Two limitations remain common within the growing field of movement analysis. First, within movement ecology, many, even most, analyses require clean, complete, and regular time series of relocations, limiting the available research on species that are hard to track and/or often return gappy, irregular data; including some of the world’s most endangered animals, e.g. black rhinos. In chapter 3, extending and applying recursion analyses to irregular spatio-temporal data from this understudied and critically endangered species, I investigated daily, biweekly and annual recursion behaviors of rhinos, to aid conservation applications and increase our fundamental knowledge about these important ecosystem engineers. Results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Initial results indicate that recursion at the daily and biweekly scales maybe driven by hydration and productivity cycles respectively. Recursion across larger timescales is also evident and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna. A second, and equally challenging, limitation to the growing movement ecology tool kit is accessibility. The growth in analysis techniques, and the concomitant growth of open-source software for analysis, pose a stumbling block to general acceptance in interdisciplinary and management settings, where researchers may be unfamiliar with the expansive set of tools or the command line interface of modern analysis packages. In chapter 4, to reduce this friction and enhance the accessibility of exploratory data analysis tools for animal movement data, I built stmove, an R package designed to make report building and exploratory data analysis simple for users who may not be familiar with the extent of available analytical tools. Furthermore, stmove sets forth a framework of best practice analyses, which offers a common starting point for the interpretation of terrestrial movement data, promoting comparability of results across movement ecology studies. The datasets, analyses, and tools presented in this dissertation seek to enhance communication, application, and accessibility of a growing movement ecology toolkit while providing a special glimpse into a diverse ecological community and the individual and population movement behavior through within Etosha National Park over the last decade. We demonstrate new tools built for exploratory data analysis in movement ecology using this data and explore how insights from movement ecology can help inform successful conservation efforts in the region and beyond

Sympatric speciation in structureless environments.

BackgroundDarwin and the architects of the Modern Synthesis found sympatric speciation difficult to explain and suggested it is unlikely to occur. Increasingly, evidence over the past few decades suggest that sympatric speciation can occur under ecological conditions that require at most intraspecific competition for a structured resource. Here we used an individual-based population model with variable foraging strategies to study the evolution of mating behavior among foraging strategy types. Initially, individuals were placed at random on a structureless resource landscape, with subsequent spatial variation induced through foraging activity itself. The fitness of individuals was determined by their biomass at the end of each generational cycle. The model incorporates three diallelic, codominant foraging strategy genes, and one mate-choice or m-trait (i.e. incipient magic trait) gene, where the latter is inactive when random mating is assumed.ResultsUnder non-random mating, the m-trait gene promotes increasing levels of either disassortative or assortative mating when the frequency of m respectively increases or decreases from 0.5. Our evolutionary simulations demonstrate that, under initial random mating conditions, an activated m-trait gene evolves to promote assortative mating because the system, in trying to fit a multipeak adaptive landscape, causes heterozygous individuals to be less fit than homozygous individuals.ConclusionOur results extend our theoretical understanding that sympatric speciation can evolve under nicheless or gradientless resource conditions: i.e. the underlying resource is monomorphic and initially spatially homogeneous. Further the simplicity and generality of our model suggests that sympatric speciation may be more likely than previously thought to occur in mobile, sexually-reproducing organisms

Sympatric speciation in structureless environments Theories and models

Background: Darwin and the architects of the Modern Synthesis found sympatric speciation difficult to explain and suggested it is unlikely to occur. Increasingly, evidence over the past few decades suggest that sympatric speciation can occur under ecological conditions that require at most intraspecific competition for a structured resource. Here we used an individual-based population model with variable foraging strategies to study the evolution of mating behavior among foraging strategy types. Initially, individuals were placed at random on a structureless resource landscape, with subsequent spatial variation induced through foraging activity itself. The fitness of individuals was determined by their biomass at the end of each generational cycle. The model incorporates three diallelic, codominant foraging strategy genes, and one mate-choice or m-trait (i.e. incipient magic trait) gene, where the latter is inactive when random mating is assumed. Results: Under non-random mating, the m-trait gene promotes increasing levels of either disassortative or assortative mating when the frequency of m respectively increases or decreases from 0.5. Our evolutionary simulations demonstrate that, under initial random mating conditions, an activated m-trait gene evolves to promote assortative mating because the system, in trying to fit a multipeak adaptive landscape, causes heterozygous individuals to be less fit than homozygous individuals. Conclusion: Our results extend our theoretical understanding that sympatric speciation can evolve under nicheless or gradientless resource conditions: i.e. the underlying resource is monomorphic and initially spatially homogeneous. Further the simplicity and generality of our model suggests that sympatric speciation may be more likely than previously thought to occur in mobile, sexually-reproducing organisms.</p

Mesoscale movement and recursion behaviors of Namibian black rhinos.

BackgroundUnderstanding rhino movement behavior, especially their recursive movements, holds significant promise for enhancing rhino conservation efforts, and protecting their habitats and the biodiversity they support. Here we investigate the daily, biweekly, and seasonal recursion behavior of rhinos, to aid conservation applications and increase our foundational knowledge about these important ecosystem engineers.MethodsUsing relocation data from 59 rhinos across northern Namibia and 8 years of sampling efforts, we investigated patterns in 24-h displacement at dawn, dusk, midday, and midnight to examine movement behaviors at an intermediate scale and across daily behavioral modes of foraging and resting. To understand recursion patterns across animals' short and long-term ranges, we built T-LoCoH time use grids to estimate recursive movement by each individual. Comparing these grids to contemporaneous MODIS imagery, we investigated productivity's influence on short-term space use and recursion. Finally, we investigated patterns of recursion within a year's home range, measuring the time to return to the most intensively used patches.ResultsTwenty four-hour displacements at dawn were frequently smaller than 24-h displacements at dusk or at midday and midnight resting periods. Recursion analyses demonstrated that short-term recursion was most common in areas of median rather than maximum NDVI values. Investigated across a full year, recursion analysis showed rhinos most frequently returned to areas within 8-21 days, though visits were also seen separated by months likely suggesting seasonality in range use.ConclusionsOur results indicate that rhinos may frequently stay within the same area of their home ranges for days at a time, and possibly return to the same general area days in a row especially during morning foraging bouts. Recursion across larger time scales is also evident, and likely a contributing mechanism for maintaining open landscapes and browsing lawns of the savanna

Ecological metrics and methods for GPS movement data

<p>The growing field of movement ecology uses high resolution movement data to analyze animal behavior across multiple scales: from individual foraging decisions to population-level space-use patterns. These analyses contribute to various subfields of ecology – <i>inter alia</i> behavioral, disease, landscape, resource, and wildlife – and facilitate novel exploration in fields ranging from conservation planning to public health. Despite the growing availability and general accessibility of animal movement data, much potential remains for the analytical methods of movement ecology to be incorporated in all types of geographic analyses. This review provides for the Geographical Information Sciences (GIS) community an overview of the most common movement metrics and methods of analysis employed by animal ecologists. Through illustrative applications, we emphasize the potential for movement analyses to promote transdisciplinary GIS/wildlife-ecology research.</p