Biology subjects

Getz, W. M.

Publications and source records attributed to Getz, W. M..

15 recordsLinked to original sources

bioRxiv2023

The Statistical Building Blocks of Animal Movement Simulations

Animal movement plays a key role in many ecological processes and has a direct influence on an individuals fitness at several scales of analysis (i.e., next-step, subdiel, day-by-day, seasonal). This high-lights the need to dissect movement behavior at different spatio-temporal scales and develop hierarchical movement tools for generating realistic tracks to supplement existing single-temporal-scale simulators. In reality, animal movement paths are a concatenation of fundamental movement elements (FuMEs: e.g., a step or wing flap), but these are not generally extractable from a relocation time-series track (e.g., sequential GPS fixes) from which step-length (SL, aka velocity) and turning-angle (TA) time series can be extracted. For short, fixed-length segments of track, we generate their SL and TA statistics (e.g., means, standard deviations, correlations) to obtain segment-specific vectors that can be cluster into different types. We use the centroids of these clusters to obtain a set of statistical movement elements (StaMEs; e.g. directed fast movement versus random slow movement elements) that we use as a basis for analyzing and simulating movement tracks. Our novel concept is that sequences of StaMEs provide a basis for constructing and fitting step-selection kernels at the scale of fixed-length canonical activity modes: short fixed-length sequences of interpretable activity such as dithering, ambling, directed walking, or running. Beyond this, variable length pure or characteristic mixtures of CAMs can be interpreted as behavioral activity modes (BAMs), such as gathering resources (a sequence of dithering and walking StaMEs) or beelining (a sequence of fast directed-walk StaMEs interspersed with vigilance and navigation stops). Here we formulate a multi-modal, step-selection kernel simulation framework, and construct a 2-mode movement simulator (Numerus ANIMOVER_1), using Numerus RAMP technology. We also illustrate methods for extracting StaMEs from both simulated and real data from two barn owls (Tyto alba) in the Harod Valley, Israel. Overall, our new bottom-up approach to path segmentation allows us to both dissect real movement tracks and generate realistic synthetic ones, thereby providing a general tool for testing hypothesis in movement ecology and simulating animal movement in diverse contexts such as evaluating an individuals response to landscape changes, release of an individual into a novel environment, or identifying when individuals are sick or unusually stressed.

ecology↗

bioRxiv2022

Extending Conway's Game of Life

We introduce an extension to Conways Game of Life (GoL) that allows more than 2 states (dead/alive; 0/1) to be specified. State 0 is reserved for dead or lifeless cells, and states 1 to n - 1 for cells that are "alive." Associated with state{sigma} is the value v{sigma} of cells such that v0 = 0, v1 = 1, and for{sigma} = 2, ..., n - 1 the cell value v{sigma} is free to be assigned any positive integer value. The value Vij of the Moore neighborhood surrounding cells at array locations (i, j) (i = 1, ..., r rows, j = 1, ..., c) is the sum of state values of the 8 cells that touch the cell at location (i, j) (4 north, south, east and west side cells and 4 NE, NW, SE, and SW corner cells; except for boundary cells, which have 5 neighbors on an edge or 3 neighbors on a corner, and noting that torroidal arrays have no boundaries). The game is based on a set of rules involving the values Vij that determine whether cells at locations (i, j) in state{sigma} , stay in this state or progress to state{sigma} + 1,{sigma} = 0, ..., n - 2, or die (remain dead in the case of dead cells). Specifically, for two non-negative constants 0 [≤] p{sigma}L [≤] p{sigma}U, if Vij < p{sigma}L, Vij [isin] [p{sigma}L, p{sigma}U] or Vij > p{sigma}U then a cell in state{sigma} at location (i, j) respectively stays in state{sigma} , progresses to state{sigma} + 1, or dies. In this paper, we illustrate some of the properties of such games of life with three, four and six states, identifying still-life, oscillator, glider and replicator pattern sequences. We also examine the long term behavior of patterns arising from random and regular (stripped diagonals) starting configurations, as well as set-piece motifs. Most importantly, we introduce two freely downloadable, Numerus runtime alterable model platforms (Numerus RAMPs) that can be used to simulate the three and four state GoLs discussed in this paper, and provide a guide on how these RAMPs can be used to explore the behavior of our GoLs.

scientific communication and education↗

bioRxiv2022

Coursing hyenas and stalking lions: the potential for inter- and intraspecific interactions

Resource partitioning promotes coexistence among guild members, and carnivores reduce interference competition through behavioural mechanisms that promote spatio-temporal separation. We analyzed sympatric lion and spotted hyena movements and activity patterns to ascertain the mechanisms facilitating their coexistence within semi-arid and wetland ecosystems. We identified recurrent high-use (revisitation) and extended stay (duration) areas within home ranges, and correlated environmental variables with movement-derived measures of inter- and intraspecific interactions. Spatial overlaps among lions and hyenas occurred at edges of home ranges, around water-points, along pathways between patches of high-use areas, and expanded during the wet season. Lions shared more of their home ranges with spotted hyenas in arid ecosystems, but shared more of their ranges with conspecifics in mesic environments. Despite shared space use, we found evidence for subtle temporal differences in the nocturnal movement and activity patterns between the two predators, suggesting a fine localized-scale avoidance strategy. Revisitation frequency and duration within home ranges were influenced by interspecific interactions, subsequent to land cover categories and diel cycles. Intraspecific interactions were also important for lions and, for hyenas, moon illumination and ungulates attracted to former anthrax carcass sites in Etosha, with distance to water in Chobe/Linyanti. Recursion and duration according to locales of competitor probabilities were similar among female lions and both sexes of hyenas, but different for male lions. Our results suggest that lions and spotted hyenas mediate the potential for interference competition through subtle differences in temporal activity, fine-scale habitat use differentiation, and localized reactive-avoidance behaviours. These findings enhance our understanding of the potential effects of interspecific interactions among large carnivore space-use patterns within an apex predator system, and show adaptability across heterogeneous and homogeneous environments. Future conservation plans should emphasize the importance of inter- and intraspecific competition within large carnivore communities, particularly moderating such effects within increasingly fragmented landscapes.

ecology↗

bioRxiv2022

Noninvasive sampling for comparisons of wildlife microbiomes may be more reliable than sampling trapped animals

In ecological and conservation studies, responsible researchers strive to obtain rich data while minimizing disturbance to wildlife and ecosystems. We assessed if samples collected noninvasively can be used for microbiome research, comparing microbiota of noninvasively collected fecal samples to those collected from trapped common cranes at the same sites over the same periods. We found significant differences in microbial composition (alpha and beta diversity), which were not accounted for by noninvasive samples exposure to soil contaminants, as manually assessed by comparing differentially abundant taxa. They could result from trapped birds exposure to sedatives. We conclude that if all samples are collected in the same manner, comparative analyses are valid, and noninvasive sampling may better represent host microbiota because there are no trapping effects. Experiments with fresh and delayed sample collection can elucidate effects of environmental exposures on microbiota. Further, stressing or sedation may unravel how trapping affects wildlife microbiota.

ecology↗

bioRxiv2021

A relative-motion method for parsing spatio-temporal behaviour of dyads using GPS relocation data

O_LIIn this paper, we introduce a novel method for classifying and computing the frequencies of movement modes of intra and interspecific dyads, focusing in particular on distance-mediated approach, retreat, following and side by side movement modes. C_LIO_LIBesides distance, the method includes factors such as sex, age, time of day, or season that cause frequencies of movement modes to deviate from random. C_LIO_LIWe demonstrate and validate our method using both simulated and empirical data. Our simulated data were obtained from a relative-motion, biased random-walk (RM-BRW) model with attraction and repulsion circumferences. Our empirical data were GPS relocation time series collected from African elephants in Etosha National Park, Namibia. The simulated data were primarily used to validate our method while the empirical data analysis were used to illustrate the types of behavioral assessment that our methodology reveals. C_LIO_LIOur methodology facilitates automated, observer-bias-free analysis of the locomotive interactions of dyads using GPS relocation data, which is becoming increasingly ubiquitous as telemetry and related technologies improve. Our method should open up a whole new vista of behavioral-interaction type analyses to movement and behavioral ecologists. C_LI

ecology↗

bioRxiv2019

A hierarchical framework for segmenting movement paths

Comparative applications of animal movement path analyses are hampered by the lack of a comprehensive framework for linking structures and processes conceived at different spatio-temporal scales. Although many analyses begin by generating step-length (SL) and turning-angle (TA) distributions from relocation time-series data--some of which are linked to ecological, landscape, and environmental covariates--the frequency at which these data are collected may vary from sub-seconds to several hours, or longer. The kinds of questions that may be asked of these data, however, are very much scale-dependent. It thus behooves us to clarify how the scale at which SL and TA data are collected and relate to one another, as well as the kinds of ecological questions that can be asked. Difficulties arise because the information contained in SL and TA time series is not semantically aligned with the physiological, ecological, and sociological factors that influence the structure of movement paths. I address these difficulties by classifying movement types at salient temporal scales using two different kinds of vocabularies. The first is the language derived from behavioral and ecological concepts. The second is the language derived from mathematically formulated stochastic walks. The primary tools for analyzing these walks are fitting time-series and stochastic-process models to SL and TA statistics (means, variances, correlations, individual-state and local environmental covariates), while paying attention to movement patterns that emerge at various spatial scales. The purpose of this paper is to lay out a more coherent, hierarchical, scale-dependent, appropriate-complexity framework for conceptualizing path segments at different spatio-temporal scales and propose a method for extracting a simulation model, referred to as M3, from these data when at a relatively high frequencies (ideally minute-by-minute). Additionally, this framework is designed to bridge biological and mathematical movement ecology concepts; thereby stimulating the development of conceptually-rooted methods that facilitates the formulation of our M3 model for simulating theoretical and analyzing empirical data, which can then be used to test hypothesis regarding mechanisms driving animal movement and make predications of animal movement responses to management and global change.

ecology↗

bioRxiv2019

A quantitative narrative on movement, disease and patch exploitation in nesting agent groups

Animal relocation data has recently become considerably more ubiquitous, finely structured (collection frequencies measured in minutes) and co-variate rich (physiology of individuals, environmental and landscape information, and accelerometer data). To better understand the impacts of ecological interactions, individual movement and disease on global change ecology, including wildlife management and conservation, it is important to have simulators that will provide demographic, movement, and epidemiology null models against which to compare patterns observed in empirical systems. Such models may then be used to develop quantitative narratives that enhance our intuition and understanding of the relationship between population structure and generative processes: in essence, along with empirical and experimental narratives, quantitative narratives are used to advance ecological epistemology. Here we describe a simulator that accounts for the influence of consumer-resource interactions, existence of social groups anchored around a central location, territoriality, group-switching behavior, and disease dynamics on population size. We use this simulator to develop new and reinforce existing quantitative narratives and point out areas for future study. Author summaryThe health and viability of species are of considerable concern to all nature lovers. Population models are central to our efforts to assess the numerical and ecological status of species and threats posed by climate change. Models, however, are crude caricatures of complex ecological systems. So how do we construct reliable assessment models able to capture processes essential to predicating the impacts of global change on population viability without getting tied up in their vast complexities? We broach this question and demonstrate how models focusing at the level of the individual (i.e., agent-based models) are tools for developing robust, narratives to augment narratives arising purely from empirical data sources and experimental outcomes. We do this in the context of nesting social groups, foraging for food, while exhibiting territoriality and group-switching behavior; and, we evaluate the impact of disease on the viability of such populations.

ecology↗

bioRxiv2018

Disease and introgression explain the long-lasting contact zone of Modern Humans and Neanderthals and its eventual destabilization

Neanderthals and modern humans both occupied the Levant for tens of thousands of years prior to modern humans spread into the rest of Eurasia and their replacement of the Neanderthals. That the inter-species boundary remained geographically localized for so long is a puzzle, particularly in light of the rapidity of its subsequent movement. We propose that disease dynamics can explain the localization and persistence of the inter-species boundary; in this view, each species carried pathogens to which it was largely immune and tolerant, but that could spread to the other, vulnerable, species, inducing a significant disease burden. Epidemics and endemic diseases along the interspecies boundary would have mitigated against bands of one species migrating into regions dominated by the other species. Together with decreased population densities and limited inter-group interactions due to disease burden, this mechanism could have resulted in a fixed and narrow contact-zone. We further propose, and support with results from dynamical systems models, that genetic introgression, including transmission of alleles related to the immune system, would have gradually allowed the two species to overcome this barrier to pervasive inter-species interaction, leading to the eventual release of the inter-species boundary from its geographic localization. Asymmetries between the two species in the initial size of their associated \"pathogen package\" could have created feedback loops that influenced the rates at which immunity to and tolerance of the novel pathogens were acquired. These asymmetries could have allowed modern humans to overcome the disease burden earlier than Neanderthals, giving them a significant advantage in their subsequent spread into Eurasia, particularly upon interaction with Neanderthal populations that had previously been far from the original contact zone in the Levant.

evolutionary biology↗

bioRxiv2018

A comparison of visual features used by humans and machines to classify wildlife

In our quest to develop more intelligent machines, knowledge of the visual features used by machines to classify objects shall be helpful. The current state of the art in training machines to classify wildlife species from camera-trap data is to employ convolutional neural networks (CNN) encoded within deep learning algorithms. Here we report on results obtained in training a CNN to classify 20 African wildlife species with an overall accuracy of 87.5% from a dataset containing 111,467 images. We then used a gradient-weighted class-activation-mapping (Grad-CAM) procedure to extract the most salient pixels in the final convolution layer. We show that these pixels highlight features in particular images that are in most, but not all, cases similar to those used to train humans to identify these species. Further, we used mutual information methods to identify the neurons in the final convolution layer that consistently respond most strongly across a set of images of one particular species, and we then interpret the features in the image where the strongest responses occur. We also used hierarchical clustering of feature vectors (i.e., the state of the final fully-connected layer in the CNN) associated with each image to produce a visual similarity dendrogram of identified species. Finally, we evaluated how images that were not part of the training set fell within our dendrogram when these images were one of the 20 species \"known\" to our CNN in contrast to where they fell when these images were \"unknown\" to our CNN.

ecology↗

bioRxiv2018

The global distribution of Bacillus anthracis and associated anthrax risk to humans, livestock, and wildlife

Bacillus anthracis is a spore-forming, Gram-positive bacterium responsible for anthrax, an acute and commonly lethal infection that most significantly affects grazing livestock, wild ungulates and other herbivorous mammals, but also poses a serious threat to human health1, 2. The geographic extent of B. anthracis endemism is still poorly understood, despite multi-decade research on anthrax epizootic and epidemic dynamics around the world3, 4. Several biogeographic studies have focused on modeling environmental suitability for anthrax at local or national scales5-9, but many countries have limited or inadequate surveillance systems, even within known endemic regions. Here we compile an extensive global occurrence dataset for B. anthracis, drawing on confirmed human, livestock, and wildlife anthrax outbreaks. With these records, we use boosted regression trees10, 11 to produce the first map of the global distribution of B. anthracis as a proxy for anthrax risk. Variable contributions to the model support pre-existing hypotheses that environmental suitability for B. anthracis depends most strongly on soil characteristics such as pH that affect spore persistence, and the extent of seasonal fluctuations in vegetation, which plays a key role in transmission for herbivores12, 13. We apply the global model to estimate that 1.83 billion people (95% credible interval: 0.59--4.16 billion) live within regions of anthrax risk, but most of that population faces little occupational exposure to anthrax. More informatively, a global total of 63.8 million rural poor livestock keepers (95% CI: 17.5--168.6 million) and 1.1 billion livestock (95% CI: 0.4--2.3 billion) live within vulnerable regions. Human risk is concentrated in rural areas, and human and livestock vulnerability are both concentrated in rainfed systems throughout arid and temperate land across Eurasia, Africa, and North America. We conclude by mapping where anthrax risk overlaps with vulnerable wild ungulate populations, and therefore could disrupt sensitive conservation efforts for species like bison, pronghorn, and saiga that coincide with anthrax-prone, mixed-agricultural landscapes. Anthrax is a zoonotic disease caused by the Gram-positive bacterium Bacillus anthracis, a generalist soil-transmitted pathogen found on every inhabited continent14, and several islands including Haiti and parts of the Philippines and Indonesia. Worldwide, an estimated 20,000 to 100,000 cases of anthrax occur annually, mostly in poor rural areas15. In clinical presentations of anthrax, case fatality rates are a function of exposure pathway. Respiratory exposure from spore inhalation is important the context of bioterrorism, but is highly uncommon, and accounts for a negligible fraction of the global burden of anthrax cases. Cutaneous exposure to B. anthracis accounts for the majority of human cases worldwide, and typically presents with low mortality; gastrointestinal exposure accounts for the remainder and presents with intermediate to high fatality rates. Cutaneous and gastrointestinal cases of anthrax are most commonly caused by handling and slaughtering infected livestock, or butchering and eating contaminated meat; untreated gastrointestinal cases likely account for most human mortality from anthrax.14-16

epidemiology↗

bioRxiv2018

Using movement data to estimate contact rates in a simulated environmentally-transmitted disease system

Agent-based models have become important tools in ecology, particularly in the study of infectious disease dynamics. Simulations of near-continuous movement paths guided by empirical data offer new avenues of investigation into disease transmission. Here, we simulate the spatiotemporal transmission dynamics of anthrax, the acute disease caused by the bacterium Bacillus anthracis, a pathogen transmitted primarily via environmental reservoirs. We explore how calculations of the probabilities of contact between a host and infectious reservoirs are affected by the scale and method of analysis. At both the landscape and individual scales, empirical movement tracks offer previously unattainable estimates of impacts of movement decisions on contact rate metrics. However, the analytical method selected for the calculation of the probability of contact has notable impacts on the resulting estimates, with convex polygons virtually canceling out variation, and unions of local convex hulls (LoCoH methods) and space-time prisms reflecting reasonable variation, but differing in the magnitude of their estimates. The explicit consideration of behavioral states along movement pathways also impacts evaluations of exposure risk, though its effects differ across methods of analysis. Ultimately, simulations demonstrate that the incorporation of movement data into pathogen transmission analyses helps clarify the role of movement processes underlying the observed dynamics of infectious disease.

ecology↗

bioRxiv2017

Going through the motions: incorporating movement analyses into disease research

Though epidemiology dates back to the 1700s, most mathematical representations of epidemics still use transmission rates averaged at the population scale, especially for wildlife diseases. In simplifying the contact process, we ignore the heterogeneities in host movements that complicate the real world, and overlook their impact on spatiotemporal patterns of disease burden. Movement ecology offers a set of tools that help unpack the transmission process, letting researchers more accurately model how animals within a population interact and spread pathogens. Analytical techniques from this growing field can also help expose the reverse process: how infection impacts movement behaviors, and therefore other ecological processes like feeding, reproduction, and dispersal. Here, we synthesize the contributions of movement ecology in disease research, with a particular focus on studies that have successfully used movement-based methods to quantify individual heterogeneity in exposure and transmission risk. Throughout, we highlight the rapid growth of both disease and movement ecology, and comment on promising but unexplored avenues for research at their overlap. Ultimately, we suggest, including movement empowers ecologists to pose new questions expanding our understanding of host-pathogen dynamics, and improving our predictive capacity for wildlife and even human diseases.

ecology↗

bioRxiv2017

Modeling Epidemics: A Primer and Numerus Software Implementation

Epidemiological models are dominated by SEIR (Susceptible, Exposed, Infected and Removed) dynamical systems formulations and their elaborations. These formulations can be continuous or discrete, deterministic or stochastic, or spatially homogeneous or heterogeneous, the latter often embracing a network formulation. Here we review the continuous and discrete deterministic and discrete stochastic formulations of the SEIR dynamical systems models, and we outline how they can be easily and rapidly constructed using the Numerus Model Builder, a graphically-driven coding platform. We also demonstrate how to extend these models to a metapopulation setting using both the Numerus Model Builder network and geographical mapping tools.

epidemiology↗

bioRxiv2017

The Parasite Extinction Assessment & Red List: an open-source, online biodiversity database for neglected symbionts

Parasite conservation is a rapidly growing field at the intersection of ecology, epidemiology, parasitology, and public health. The overwhelming diversity of parasitic life on earth, and recent work showing that parasites and other symbionts face severe extinction risk, necessitates infrastructure for parasite conservation assessments. Here, we describe the release of the Parasite Extinction Assessment & Red List (PEARL) version 1.0, an open-access database of conservation assessments and distributional data for almost 500 macroparasitic invertebrates. The current approach to vulnerability assessment is based on range shifts and loss from climate change, and will be expanded as additional data (e.g., host-parasite associations and coextinction risk) is consolidated in PEARL. The web architecture is also open-source, scalable, and extensible, making PEARL a template for more eZcient red listing for other high-diversity, data-de1cient groups. Future iterations will also include new functionality, including a user-friendly open data pository and automated assessment and re-listing.

ecology↗

bioRxiv2017

A cross-validation-based approach for delimiting reliable home range estimates

BackgroundWith decreasing costs of GPS telemetry devices, data repositories of animal movement paths are increasing almost exponentially in size. A series of complex statistical tools have been developed in conjunction with this increase in data. Each of these methods offers certain improvements over previously proposed methods, but each has certain assumptions or shortcomings that make its general application difficult. In the case of the recently developed Time Local Convex Hull (T-LoCoH) method, the subjectivity in parameter selection serves as one of the primary impediments to its more widespread use. While there are certain advantages to the flexibility it offers for question-driven research, the lack of an objective approach for parameter selection may prevent some users from exploring the benefits of the method.\n\nResultsHere we present a cross-validation-based approach for selecting parameter values to optimize the T-LoCoH algorithm. We demonstrate the utility of the approach using a case study from the Etosha National Park anthrax system. Utilizing the proposed algorithm, rather than the guidelines in the T-LoCoH documentation, results in significantly different values for derived site fidelity metrics.\n\nConclusionsDue to its basis in principles of cross-validation, the application of this method offers a more objective approach than the relatively subjective guidelines set forth in the T-LoCoH documentation and enables a more accurate basis for the comparison of home ranges among individuals and species, as well as among studies.

ecology↗