Geology topics

Wayne M. Getz

Publications and source records attributed to Wayne M. Getz.

11 recordsLinked to original sources

USGS2023

Variation in herbivore space use: Comparing two savanna ecosystems with different anthrax outbreak patterns in southern Africa

Background The distribution of resources can affect animal range sizes, which in turn may alter infectious disease dynamics in heterogenous environments. The risk of pathogen exposure or the spatial extent of outbreaks may vary with host range size. This study examined the range sizes of herbivorous anthrax host species in two ecosystems and relationships between spatial movement behavior and patterns of disease outbreaks for a multi-host environmentally transmitted pathogen. Methods We examined range sizes for seven host species and the spatial extent of anthrax outbreaks in Etosha National Park, Namibia and Kruger National Park, South Africa, where the main host species and outbreak sizes differ. We evaluated host range sizes using the local convex hull method at different temporal scales, within-individual temporal range overlap, and relationships between ranging behavior and species contributions to anthrax cases in each park. We estimated the spatial extent of annual anthrax mortalities and evaluated whether the extent was correlated with case numbers of a given host species. Results Range size differences among species were not linearly related to anthrax case numbers. In Kruger the main host species had small range sizes and high range overlap, which may heighten exposure when outbreaks occur within their ranges. However, different patterns were observed in Etosha, where the main host species had large range sizes and relatively little overlap. The spatial extent of anthrax mortalities was similar between parks but less variable in Etosha than Kruger. In Kruger outbreaks varied from small local clusters to large areas and the spatial extent correlated with case numbers and species affected. Secondary host species contributed relatively few cases to outbreaks; however, for these species with large range sizes, case numbers positively correlated with outbreak extent. Conclusions Our results provide new information on the spatiotemporal structuring of ranging movements of anthrax host species in two ecosystems. The results linking anthrax dynamics to host space use are correlative, yet suggest that, though partial and proximate, host range size and overlap may be contributing factors in outbreak characteristics for environmentally transmitted pathogens.

Etosha National Park, Kruger National Park↗

USGS2023

Challenges and solutions for automated avian recognition in aerial imagery

Remote aerial sensing provides a non-invasive, large geographical-scale technology for avian monitoring, but the manual processing of images limits its development and applications. Artificial Intelligence (AI) methods can be used to mitigate this manual image processing requirement. The implementation of AI methods, however, has several challenges: (1) imbalanced (i.e., long-tailed) data distribution, (2) annotation uncertainty in categorization, and (3) dataset discrepancies across different study sites. Here we use aerial imagery data of waterbirds around Cape Cod and Lake Michigan in the United States to examine how these challenges limit avian recognition performance. We review existing solutions and demonstrate as use cases how methods like Label Distribution Aware Marginal Loss with Deferred Re-Weighting, hierarchical classification, and FixMatch address the three challenges. We also present a new approach to tackle the annotation uncertainty challenge using a Soft-fine Pseudo-Label methodology. Finally, we aim with this paper to increase awareness in the ecological remote sensing community of these challenges and bridge the gap between ecological applications and state-of-the-art computer science, thereby opening new doors to future research.

Remote Sensing in Ecology and Conservation↗

USGS2022

A framework for integrating inferred movement behavior into disease risk models

Movement behavior is an important contributor to habitat selection and its incorporation in disease risk models has been somewhat neglected. The habitat preferences of host individuals affect their probability of exposure to pathogens. If preference behavior can be incorporated in ecological niche models (ENMs) when data on pathogen distributions are available, then variation in such behavior may dramatically impact exposure risk. Here we use data from the anthrax endemic system of Etosha National Park, Namibia, to demonstrate how integrating inferred movement behavior alters the construction of disease risk maps. We used a Maximum Entropy (MaxEnt) model that associated soil, bioclimatic, and vegetation variables with the best available pathogen presence data collected at anthrax carcass sites to map areas of most likely Bacillus anthracis (the causative bacterium of anthrax) persistence. We then used a hidden Markov model (HMM) to distinguish foraging and non-foraging behavioral states along the movement tracks of nine zebra ( Equus quagga ) during the 2009 and 2010 anthrax seasons. The resulting tracks, decomposed on the basis of the inferred behavioral state, formed the basis of step-selection functions (SSFs) that used the MaxEnt output as a potential predictor variable. Our analyses revealed different risks of exposure during different zebra behavioral states, which were obscured when the full movement tracks were analyzed without consideration of the underlying behavioral states of individuals. Pathogen (or vector) distribution models may be misleading with regard to the actual risk faced by host animal populations when specific behavioral states are not explicitly accounted for in selection analyses. To more accurately evaluate exposure risk, especially in the case of environmentally transmitted pathogens, selection functions could be built for each identified behavioral state and then used to assess the comparative exposure risk across relevant states. The scale of data collection and analysis, however, introduces complexities and limitations for consideration when interpreting results.

Etosha National Park↗

USGS2022

Africa’s drylands in a changing world: Challenges for wildlife conservation under climate and land-use changes in the Greater Etosha Landscape

Proclaimed in 1907, Etosha National Park in northern Namibia is an iconic dryland system with a rich history of wildlife conservation and research. A recent research symposium on wildlife conservation in the Greater Etosha Landscape (GEL) highlighted increased concern of how intensification of global change will affect wildlife conservation based on participant responses to a questionnaire. The GEL includes Etosha and surrounding areas, the latter divided by a veterinary fence into large, private farms to the south and communal areas of residential and farming land to the north. Here, we leverage our knowledge of this ecosystem to provide insight into the broader challenges facing wildlife conservation in this vulnerable dryland environment. We first look backward, summarizing the history of wildlife conservation and research trends in the GEL based on a literature review, providing a broad-scale understanding of the socioecological processes that drive dryland system dynamics. We then look forward, focusing on eight key areas of challenge and opportunity for this ecosystem: climate change, water availability and quality, vegetation and fire management, adaptability of wildlife populations, disease risk, human-wildlife conflict, wildlife crime, and human dimensions of wildlife conservation. Using this model system, we summarize key lessons and identify critical threats highlighting future research needs to support wildlife management. Research in the GEL has followed a trajectory seen elsewhere reflecting an increase in complexity and integration across biological scales over time. Yet, despite these trends, a gap exists between the scope of recent research efforts and the needs of wildlife conservation to adapt to climate and land-use changes. Given the complex nature of climate change, in addition to locally existing system stressors, a framework of forward-thinking adaptive management to address these challenges, supported by integrative and multidisciplinary research could be beneficial. One critical area for growth is to better integrate research and wildlife management across land-use types. Such efforts have the potential to support wildlife conservation efforts and human development goals, while building resilience against the impacts of climate change. While our conclusions reflect the specifics of the GEL ecosystem, they have direct relevance for other African dryland systems impacted by global change.

Africa, Greater Etosha Landscape↗

USGS2021

Disease or drought: Environmental fluctuations release zebra from a potential pathogen-triggered ecological trap

When a transmission hotspot for an environmentally persistent pathogen establishes in otherwise high-quality habitat, the disease may exert a strong impact on a host population. However, fluctuating environmental conditions lead to heterogeneity in habitat quality and animal habitat preference, which may interrupt the overlap between selected and risky habitats. We evaluated spatio-temporal patterns in anthrax mortalities in a plains zebra ( Equus quagga ) population in Etosha National Park, Namibia, incorporating remote-sensing and host telemetry data. A higher proportion of anthrax mortalities of herbivores was detected in open habitats than in other habitat types. Resource selection functions showed that the zebra population shifted habitat selection in response to changes in rainfall and vegetation productivity. Average to high rainfall years supported larger anthrax outbreaks, with animals congregating in preferred open habitats, while a severe drought forced animals into otherwise less preferred habitats, leading to few anthrax mortalities. Thus, the timing of anthrax outbreaks was congruent with preference for open plains habitats and a corresponding increase in pathogen exposure. Given shifts in habitat preference, the overlap in high-quality habitat and high-risk habitat is intermittent, reducing the adverse consequences for the population.

Etosha National Park↗

USGS2017

Making ecological models adequate

Critical evaluation of the adequacy of ecological models is urgently needed to enhance their utility in developing theory and enabling environmental managers and policymakers to make informed decisions. Poorly supported management can have detrimental, costly or irreversible impacts on the environment and society. Here, we examine common issues in ecological modelling and suggest criteria for improving modelling frameworks. An appropriate level of process description is crucial to constructing the best possible model, given the available data and understanding of ecological structures. Model details unsupported by data typically lead to over parameterisation and poor model performance. Conversely, a lack of mechanistic details may limit a model's ability to predict ecological systems’ responses to management. Ecological studies that employ models should follow a set of model adequacy assessment protocols that include: asking a series of critical questions regarding state and control variable selection, the determinacy of data, and the sensitivity and validity of analyses. We also need to improve model elaboration, refinement and coarse graining procedures to better understand the relevancy and adequacy of our models and the role they play in advancing theory, improving hind and forecasting, and enabling problem solving and management.

Ecology Letters↗

USGS2014

Parasite-mediated selection drives an immunogenetic tradeoff in plains zebra (Equus quagga)

Pathogen evasion of the host immune system is a key force driving extreme polymorphism in genes of the major histocompatibility complex (MHC). Although this gene family is well characterized in structure and function, there is still much debate surrounding the mechanisms by which MHC diversity is selectively maintained. Many studies have investigated relationships between MHC variation and specific pathogens, and have found mixed support for and against the hypotheses of heterozygote advantage, frequency-dependent or fluctuating selection. Few, however, have focused on the selective effects of multiple parasite types on host immunogenetic patterns. Here, we examined relationships between variation in the equine MHC gene, ELA-DRA, and both gastrointestinal (GI) and ectoparasitism in plains zebras (Equus quagga). Specific alleles present at opposing population frequencies had antagonistic effects, with rare alleles associated with increased GI parasitism and common alleles with increased tick burdens. These results support a frequency-dependent mechanism, but are also consistent with fluctuating selection. Maladaptive GI parasite ‘susceptibility alleles’ were reduced in frequency, suggesting that these parasites may play a greater selective role at this locus. Heterozygote advantage, in terms of allele mutational divergence, also predicted decreased GI parasite burden in genotypes with a common allele. We conclude that an immunogenetic trade-off affects resistance/susceptibility to parasites in this system. Because GI and ectoparasites do not directly interact within hosts, our results uniquely show that antagonistic parasite interactions can be indirectly modulated through the host immune system. This study highlights the importance of investigating the role of multiple parasites in shaping patterns of host immunogenetic variation.

Proceedings of the Royal Society B: Biological Sci↗

USGS2007

LoCoH: Non-parameteric kernel methods for constructing home ranges and utilization distributions

Parametric kernel methods currently dominate the literature regarding the construction of animal home ranges (HRs) and utilization distributions (UDs). These methods frequently fail to capture the kinds of hard boundaries common to many natural systems. Recently a local convex hull (LoCoH) nonparametric kernel method, which generalizes the minimum convex polygon (MCP) method, was shown to be more appropriate than parametric kernel methods for constructing HRs and UDs, because of its ability to identify hard boundaries (e.g., rivers, cliff edges) and convergence to the true distribution as sample size increases. Here we extend the LoCoH in two ways: ‘‘fixed sphere-of-influence,’’ or r -LoCoH (kernels constructed from all points within a fixed radius r of each reference point), and an ‘‘adaptive sphere-of-influence,’’ or a -LoCoH (kernels constructed from all points within a radius a such that the distances of all points within the radius to the reference point sum to a value less than or equal to a ), and compare them to the original ‘‘fixed-number-of-points,’’ or k -LoCoH (all kernels constructed from k -1 nearest neighbors of root points). We also compare these nonparametric LoCoH to parametric kernel methods using manufactured data and data collected from GPS collars on African buffalo in the Kruger National Park, South Africa. Our results demonstrate that LoCoH methods are superior to parametric kernel methods in estimating areas used by animals, excluding unused areas (holes) and, generally, in constructing UDs and HRs arising from the movement of animals influenced by hard boundaries and irregular structures (e.g., rocky outcrops). We also demonstrate that a -LoCoH is generally superior to k - and r -LoCoH (with software for all three methods available at http://locoh.cnr.berkeley.edu).

PLoS ONE↗

USGS2006

Utility of R0 as a predictor of disease invasion in structured populations

Early theoretical work on disease invasion typically assumed large and well-mixed host populations. Many human and wildlife systems, however, have small groups with limited movement among groups. In these situations, the basic reproductive number, R 0 , is likely to be a poor predictor of a disease pandemic because it typically does not account for group structure and movement of individuals among groups. We extend recent work by combining the movement of hosts, transmission within groups, recovery from infection and the recruitment of new susceptibles into a stochastic model of disease in a host metapopulation. We focus on how recruitment of susceptibles affects disease invasion and how population structure can affect the frequency of superspreading events (SSEs). We show that the frequency of SSEs may decrease with the reduced movement and the group sizes due to the limited number of susceptible individuals available. Classification tree analysis of the model results illustrates the hierarchical nature of disease invasion in host metapopulations. First, the pathogen must effectively transmit within a group ( R 0 >1), and then the pathogen must persist within a group long enough to allow for movement among the groups. Therefore, the factors affecting disease persistence—such as infectious period, group size and recruitment of new susceptibles—are as important as the local transmission rates in predicting the spread of pathogens across a metapopulation.

Journal of the Royal Society Interface↗

USGS2006

Assessing vaccination as a control strategy in an ongoing epidemic: Bovine tuberculosis in African buffalo

Bovine tuberculosis (BTB) is an exotic disease invading the buffalo population ( Syncerus caffer ) of the Kruger National Park (KNP), South Africa. We used a sex and age-structured epidemiological model to assess the effectiveness of a vaccination program and define important research directions. The model allows for dispersal between a focal herd and background population and was parameterized with a combination of published data and analyses of over 130 radio-collared buffalo in the central region of the KNP. Radio-tracking data indicated that all sex and age categories move between mixed herds, and males over 8 years old had higher mortality and dispersal rates than any other sex or age category. In part due to the high dispersal rates of buffalo, sensitivity analyses indicate that disease prevalence in the background population accounts for the most variability in the BTB prevalence and quasi-eradication within the focal herd. Vaccination rate and the transmission coefficient were the second and third most important parameters of the sensitivity analyses. Further analyses of the model without dispersal suggest that the amount of vaccination necessary for quasi-eradication (i.e. prevalence < 5%) depends upon the duration that a vaccine grants protection. Vaccination programs are more efficient (i.e. fewer wasted doses) when they focus on younger individuals. However, even with a lifelong vaccine and a closed population, the model suggests that >70% of the calf population would have to be vaccinated every year to reduce the prevalence to less than 1%. If the half-life of the vaccine is less than 5 years, even vaccinating every calf for 50 years may not eradicate BTB. Thus, although vaccination provides a means of controlling BTB prevalence it should be combined with other control measures if eradication is the objective.

Kruger National Park↗

USGS2004

Integrating association data and disease dynamics: an illustration using African Buffalo in Kruger National Park

Recognition is a prerequisite for non-random association amongst individuals. We explore how non-random association patterns (i.e. who spends time with whom) affect disease dynamics. We estimated the amount of time individuals spent together per month using radio-tracking data from African buffalo and incorporated these data into a dynamic social network model. The dynamic nature of the network has a strong influence on simulated disease dynamics particularly for diseases with shorter infectious periods. Cluster analyses of the association data demonstrated that buffalo herds were not as well defined as previously thought. Associations were more tightly clustered in 2002 than 2003, perhaps due to drier conditions in 2003. As a result, diseases may spread faster during drought conditions due to increased population mixing. Association data are often collected but this is the first use of empirical data in a network disease model in a wildlife population.

Kruger National Park↗