Biology subjects

Calabrese, J.

Publications and source records attributed to Calabrese, J..

12 recordsLinked to original sources

bioRxiv2026

Realistic basin shape variation modulates local riverine biodiversity via altered connectivity

Understanding the drivers of biodiversity in the worlds rivers, which are known to be hyperdiverse relative to their coverage area, has been an enduring goal in ecology. While regression-based empirical studies have identified a suite of environmental factors that are correlated with riverine fish biodiversity, these insights are often system-specific and inconsistent across regions. In contrast, a more limited body of studies have suggested that network connectivity of rivers affects fish biodiversity by limiting dispersal, and basin shape may modulate these relationships. The few theoretical papers that have explored basin morphology effects have tended to use extreme network shapes and inconsistent methods, thus limiting general insights. Here, we build on these results to demonstrate that river basin morphology, as measured by log aspect ratio, can alter both network connectivity and biodiversity in simulated, all-else-equal scenarios. First, we quantify variation in log aspect ratio across the worlds 100 largest rivers and use this empirical range of shape variation to guide synthetic experiments. In particular, we use Optimal Channel Networks (OCNs) constrained to basins with log aspect ratios within realistic range to study how shape alters connectivity profiles when node number and basin area are held constant. By coupling OCNs with dendritic neutral models, we demonstrate that variation in aspect ratio and concomitant changes in connectivity lead to substantial changes in simulated biodiversity. Finally, we use Earth Movers Distance to establish that basin-shape-induced changes in node-level connectivity distributions are predictive of transformations in node-level distributions of and {beta} diversity. Overall, elongated basins such as the Mekong River feature lower species richness (-diversity), higher turnover ({beta}-diversity), and less variable distributions of both quantities relative to a square reference basin. Furthermore, approximately one third of the worlds largest rivers are elongated enough to potentially feature statistically-detectable, shape-mediated variation in connectivity and biodiversity.

ecology↗

bioRxiv2025

Too few, too many, or just right? Optimizing sample sizes for population-level inferences in animal tracking projects

O_LISuccessful animal tracking projects depend on well-informed sampling strategies and robust methods to yield biologically meaningful inferences. Considering financial and logistical constraints, the reliability of research outputs is shaped by key decisions regarding study duration (how long should each individual be tracked?), sampling frequency (how often should new locations be collected?), and how many individuals should be tracked. To maximize their conservation value, studies must consider estimator precision and avoid biased inferences of key parameters related to movement behavior and space use, as this can lead to wasted resources and misguide management actions. C_LIO_LITo address these challenges, we propose a workflow for determining the optimal sample sizes for population-level home range area and speed estimates, explicitly addressing the trade-offs between sampling duration (T), sampling interval (reciprocal of frequency; {Delta}t), and population sample size (m). While a priori study design is considered best practice, this workflow can be applied at multiple stages, including concurrent with data collection, or as a post hoc evaluation. C_LIO_LIBy selecting robust methods that are sampling-insensitive, and by quantifying and propagating uncertainty through downstream analyses, we can determine whether our sample sizes (both at the individual- and population-level) are sufficient to yield robust population-level inferences. Furthermore, researchers can integrate additional logistical constraints such as fix success rate, location error, and potential device malfunctions, while also accounting for individual variation. We illustrate potential applications of this workflow through empirically-guided simulations. C_LIO_LITo facilitate its use and implementation, we incorporated this workflow into the user-friendly movedesign R Shiny application. This application enables researchers to easily test different sampling strategies, and as of version 0.3.3, integrates population-level analytical targets. This workflow has the potential to improve the rigor and reliability of animal tracking projects conducted under logistical and financial constraints, and thereby support more effective scientific research, wildlife management, and conservation efforts. It can also support grant or permit submissions by generating evidence-based recommendations for the number of biologgers needed or sampling effort required to achieve research objectives. C_LI

ecology↗

bioRxiv2025

The range-resident logistic model: a new framework to formalize the population-dynamics consequences of range residency

Individual movement is critical in shaping population dynamics. However, existing frameworks linking these two processes often rely on unrealistic assumptions or numerical simulations. To address this gap, we introduce the range-resident logistic model, an easy-to-simulate and mathematically tractable extension of the spatial logistic model that incorporates empirically supported range-resident movement. Our framework unifies non-spatial and (sessile) spatial formulations of the logistic model as limiting cases. Between these regimes, the long-term population size depends nonlinearly on home-range size and spatial distribution. Neglecting range residency can hence lead to under- or overestimating population carrying capacity. To better understand these results, we also introduce a novel crowding index that depends on movement parameters and can be estimated from tracking data. This index captures the influence of spatial structure on population size, and serves as a robust predictor of abundance. The range-resident logistic model is thus a unifying framework bridging movement and population ecology.

ecology↗

bioRxiv2024

Home range spillover in habitats with impassable boundaries: Causes, biases, and corrections using autocorrelated kernel density estimation

O_LIAn animals home range plays a fundamental role in determining its resource use and overlap with conspecifics, competitors and predators, and is therefore a common focus of movement ecology studies. Autocorrelated kernel density estimation addresses many of the shortcomings of traditional home range estimators when animal tracking data is autocorrelated, but other challenges in home range estimation remain. C_LIO_LIOne such issue is known as spillover bias, in which home range estimates do not respect impassable movement boundaries (e.g., shorelines, fences), and occurs in all forms of kernel density estimation. While several approaches to addressing spillover bias are used when estimating home ranges, these approaches introduce bias throughout the remaining home range area, depending on the amount of spillover removed, or are otherwise inaccessible to most ecologists. Here, we introduce local corrections to home range kernels to mitigate spillover bias in (autocorrelated) kernel density estimation in the continuous time movement model (ctmm) package, and demonstrate their performance using simulations with known home range extents and distributions, and a real world case study. C_LIO_LISimulation results showed that local corrections minimised bias in bounded home range area estimates, and resulted in more accurate distributions when compared to commonly used post-hoc corrections, particularly at small-intermediate sample sizes. C_LIO_LIComparison of the impacts of local vs post-hoc corrections to bounded home ranges estimated from lake trout (Salvelinus namaycush) demonstrated that local corrections constrained bias within the remaining home range area, resulting in proportionally smaller home range areas compared to when post-hoc corrections are used. C_LI

ecology↗

bioRxiv2024

Simultaneous Identification of Changepoints and Model Parameters in Switching Dynamical Systems

Many complex natural systems undergo shifts in dynamics at particular points in time. Examples include phase transitions in gene expression during the cell cycle, introduced species affecting predator-prey interactions, and disease outbreaks responding to intervention measures. Such changepoints partition timeseries into different dynamical regimes characterized by distinct parameter sets, and inference on both the changepoints and regime-specific dynamical parameters is of primary interest. Conventional approaches to analyzing switching dynamical systems first estimate changepoints, and then estimate dynamical parameters assuming the changepoints are fixed and known. Such two-stage approaches are ad-hoc, can introduce biases in the analysis, and do not fully account for uncertainty. Here, we introduce a rigorous, simulation-based inference framework that simultaneously estimates changepoints and model parameters from noisy data while admitting full uncertainty. We use simulation studies of oscillatory predator-prey dynamics and stochastic gene expression to demonstrate that our method yields accurate estimates of changepoints and model parameters together with appropriate uncertainty bounds. We then apply our approach to a real-world case study of COVID-19 intervention effects, and show that our inferred changepoints aligned closely with the actual dates of intervention implementation. Taken together, these results suggest that our framework will have broad utility in diverse scientific domains.

ecology↗

bioRxiv2023

Intraspecific encounters can induce home-range shifts

Direct encounters, in which two or more individuals are physically close to one another, are a topic of increasing interest as more and better movement data become available. Recent progress, including the development of statistical tools for estimating robust measures of changes in animals space use over time, facilitates opportunities to link direct encounters between individuals with the long-term consequences of those encounters. Working with movement data for coyotes (Canis latrans) and grizzly bears (Ursus arctos horribilis), we investigate whether close intraspecific encounters were associated with spatial shifts in the animals range distributions, as might be expected if one or both of the individuals involved in an encounter were seeking to reduce or avoid conflict over space. We analyze the movement data of a pair of coyotes in detail, identifying how a shift in home range location resulting from altered movement behavior was apparently a consequence of a close intraspecific encounter. With grizzly bear movement data, we approach the problem from the perspective of a set of encounter pairs within a population. We find support for the hypotheses that 1) close intraspecific encounters between bears are, on average, associated with subsequent shifts in range distributions and 2) encounters defined at finer spatial scales are followed by greater changes in space use. Our results suggest that animals can undertake long-term, large-scale spatial shifts in response to close intraspecific encounters that have the potential for conflict. These results lend support for existing theory on the evolution of territories and space use (e.g., Maynard-Smiths bourgeois strategy regarding low-conflict coexistence). Overall, we find that analyses of movement data in a pairwise context can 1) identify distances at which individuals proximity to one another may alter behavior and 2) facilitate testing of population-level hypotheses concerning the potential for direct encounters to alter individuals space use. Open Research StatementMovement data for the coyotes and grizzly bears are posted on Movebank.org as datasets 1614661371 and 1044288582, respectively. Statistical tools for estimating, manipulating, and comparing home ranges from movement data are implemented in the open-source R package ctmm. R scripts used to carry out specific analyses for this study are openly available on GitHub at https://github.com/anagkrish/encounter_homerangeshift.

ecology↗

bioRxiv2022

Development of Enterovirus anti-viral agents that target the viral 2C protein

The enterovirus (EV) genus includes a number of important human and animal pathogens. EV-A71, EV-D68, poliovirus (PV), and coxsackievirus (CV) outbreaks have affected millions worldwide causing a range of upper respiratory, skin, neuromuscular diseases, including acute flaccid myelitis, and hand-foot-and-mouth disease. There are no FDA-approved anti-viral therapeutics for these enteroviruses. In this study, we describe novel broad spectrum anti-viral compounds targeting the conserved non-structural viral protein 2C that have low micro-molar to nanomolar IC50 values. The selection of resistant mutants resulted in amino acid substitutions in the viral capsid protein, implying a role for 2C in capsid assembly, as has been seen in PV. The assembly and encapsidation stages of the viral life cycle are not fully understood and the inhibitors reported here could be useful probes in understanding these processes.

pharmacology and toxicology↗

bioRxiv2021

Movement ecology of vulnerable lowland tapirs across a gradient of human disturbance

Animal movement is a key ecological process that is tightly coupled to local environmental conditions. While agriculture, urbanisation, and transportation infrastructure are critical to human socio-economic improvement, these have spurred substantial changes in animal movement across the globe with potential impacts on fitness and survival. Notably, however, human disturbance can have differential effects across species, and responses to human activities are thus largely taxa and context specific. As human disturbance is only expected to worsen over the next decade it is critical to better understand how species respond to human disturbance in order to develop effective, case-specific conservation strategies. Here, we use an extensive telemetry dataset collected over 22 years to fill a critical knowledge gap in the movement ecology of lowland tapirs (Tapirus terrestris) across a gradient of human disturbance within three biomes in southern Brazil: the Pantanal, Cerrado, and Atlantic Forest. From these data we found that the mean home range size across all monitored tapirs was 8.31 km2 (95% CI: 6.53 - 10.42), with no evidence that home range sizes differed between sexes nor age groups. Interestingly, although the Atlantic Forest, Cerrado, and Pantanal vary substantially in habitat composition, levels of human disturbance, and tapir population densities, we found that lowland tapir movement behaviour and space use were consistent across all three biomes. Human disturbance also had no detectable effect on lowland tapir movement. Lowland tapirs living in the most altered habitats we monitored exhibited movement behaviour that was comparable to that of tapirs living in a near pristine environment. Contrary to our expectations, we observed very little individual variability in lowland tapir space use and movement, and human impacts on the landscape also had no measurable effect on their movement. Lowland tapir movement behaviour thus appears to exhibit very little phenotypic plasticity. Crucially, the lack of any detectable response to anthropogenic disturbance suggests that human modified habitats risk being ecological traps for tapirs and this information should be factored into conservation actions and species management aimed towards protecting lowland tapir populations.

ecology↗

bioRxiv2021

Modelling the probability of detecting mass mortality events

While reports of mass mortality events (MMEs) are increasing in the literature, comparing the incidence of MMEs through time, among locations, or taxa is problematic without accounting for detection probabilities. MMEs involving small, cryptic species can be difficult to detect even during the event, and degradation and scavenging of carcasses can make the window for detection very short. As such, the number or occurrence rate of MMEs may often be severely underestimated, especially with infrequent observations. We develop a simple modeling framework to quantify the probability of detecting an MME as a function of the observation frequency relative to the rate at which MMEs become undetectable. This framework facilitates the design of surveillance programs and may be extended to correct estimates of the incidence of MMEs from actual surveillance data for more appropriate analyses of trends through time and among taxa.

ecology↗

bioRxiv2020

Estimating encounter location distributions from animal tracking data

O_LIEcologists have long been interested in linking individual behavior with higher-level processes. For motile species, this upscaling is governed by how well any given movement strategy maximizes encounters with positive factors, and minimizes encounters with negative factors. Despite the importance of encounter events for a broad range of ecological processes, encounter theory has not kept pace with developments in animal tracking or movement modeling. Furthermore, existing work has focused primarily on the relationship between animal movement and encounter rates while no theoretical framework exists for directly relating individual movement with the spatial locations of encounter events in the environment. C_LIO_LIHere, we bridge this gap by introducing a new theoretical concept describing the long-term encounter location probabilities for movement within home ranges, termed the conditional distribution of encounters (CDE). We then derive this distribution, as well as confidence intervals, implement its statistical estimator into open source software, and demonstrate the broad ecological relevance of this novel concept. C_LIO_LIWe first use simulated data to show how our estimator provides asymptotically consistent estimates. We then demonstrate the general utility of this method for three simulation-based scenarios that occur routinely in biological systems: i) a population of individuals with home ranges that overlap with neighbors; ii) a pair of individuals with a hard territorial border between their home ranges; and iii) a predator with a large home range that encompassed the home ranges of multiple prey individuals. Using GPS data from white-faced capuchins (Cebus capucinus) tracked on Barro Colorado Island, Panama, and sleepy lizards (Tiliqua rugosa) tracked in Bundey, South Australia, we then show how the CDE can be used to estimate the locations of territorial borders, identify key resources, quantify the location-specific potential for competition, and/or identify any changes in behaviour that directly result from location-specific encounter probability. C_LIO_LIThis novel target distribution enables researchers to better understand the dynamics of populations of interacting individuals. Notably, the general estimation framework developed in this work builds straightforwardly off of home range estimation and requires no specialised data collection protocols. This method is now openly available via the ctmm R package. C_LI

ecology↗

bioRxiv2020

Structures of three actinobacteriophage capsids: Roles of symmetry and accessory proteins

Mycobacterium tuberculosis and abscessus are major human pathogens that are part of the Actinobacteria phylum. Increasing multiple drug resistance in these bacteria has led to a renewed interest in using viruses that infect these bacteria for therapy. In order to understand these viruses, a course-based undergraduate research experience (CURE) program run by SEA-PHAGES at the University of Pittsburgh and HHMI has isolated, sequenced, and annotated over 3000 actinobacteriophages (viruses that infect Actinobacteria). Little work has been done to investigate the structural diversity of these phage, all of which are thought to use a common protein fold, the HK97-fold, in their major capsid protein. Here we describe the structure of three actinobacteriophage capsids isolated by students that infect Mycobacterium smegmatis. The capsid structures were resolved to approximately 6 angstroms, which allowed confirmation that each phage uses the HK97-fold to form their capsid. One phage, Rosebush, has a novel variation of the HK97-fold. Four novel accessory proteins, that form the capsid head along with the major capsid protein, were identified that show limited or no homology to known proteins. The genes that encode the proteins were identified using SDS-PAGE and mass spectrometry. Bioinformatic analysis of the accessory proteins suggest they are used in many actinobacteriophage capsids.

microbiology↗

bioRxiv2019

The challenges of estimating the distribution of flight heights from telemetry or altimetry data

BackgroundGlobal positioning systems (GPS) and altimeters are increasingly used to monitor vertical space use by aerial species, a key aspect of their niche that we need to know to understand their ecology and conservation needs, and to manage our own use of the airspace. However, there are various sources of error in flight height data (\"height\" above ground, as opposed to \"altitude\" above a reference like the sea level): vertical error from the devices themselves, error in the ground elevation below the tracked animals, and error in the horizontal position of the animals and thus the predicted ground elevation below them.\n\nMethodsWe used controlled field trials, simulations, and the reanalysis of raptor case studies with state-space models to illustrate the effect of improper error management.\n\nResultsErrors of a magnitude of 20 meters appear in benign conditions (expected to be larger in more challenging context). These errors distort the shape of the distribution of flight heights, inflate the variance in flight height, bias behavioural state assignments, correlations with environmental covariates, and airspace management recommendations. Improper data filters such as removing all negative recorded flight height records introduce several biases in the remaining dataset, and preclude the opportunity to leverage unambiguous errors to help with model fitting. Analyses that ignore the variance around the mean flight height, e.g., those based on linear models of flight height, and those that ignore the variance inflation caused by telemetry errors, lead to incorrect inferences.\n\nConclusionThe state-space modelling framework, now in widespread use by ecologists and increasingly often automatically implemented within on-board GPS data processing algorithms, makes it possible to fit flight models directly to raw flight height records, with minimal data pre-selection, and to analyse the full distribution of flight heights, not just the mean. In addition to basic research about aerial niches, behaviour quantification, and environmental interactions, we highlight the applied relevance of our recommendations for airspace management and the conservation of aerial wildlife.

ecology↗