When the going gets tough: behavioural type-dependent space use in the sleepy lizard changes as the season dries

Understanding space use remains a major challenge for animal ecology, with implications for species interactions, disease spread, and conservation. Behavioural type (BT) may shape the space use of individuals within animal populations. Bolder or more aggressive individuals tend to be more exploratory and disperse further. Yet, to date we have limited knowledge on how space use other than dispersal depends on BT. To address this question we studied BT-dependent space-use patterns of sleepy lizards ( Tiliqua rugosa ) in southern Australia. We combined high-resolution global positioning system (GPS) tracking of 72 free-ranging lizards with repeated behavioural assays, and with a survey of the spatial distributions of their food and refuge resources. Bayesian generalized linear mixed models (GLMM) showed that lizards responded to the spatial distribution of resources at the neighbourhood scale and to the intensity of space use by other conspecifics (showing apparent conspecific avoidance). BT (especially aggressiveness) affected space use by lizards and their response to ecological and social factors, in a seasonally dependent manner. Many of these effects and interactions were stronger later in the season when food became scarce and environmental conditions got tougher. For example, refuge and food availability became more important later in the season and unaggressive lizards were more responsive to these predictors. These findings highlight a commonly overlooked source of heterogeneity in animal space use and improve our mechanistic understanding of processes leading to behaviourally driven disease dynamics and social structure.

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sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽

10.12688/f1000research.15824.3 ◽

2020 ◽

Vol 7 ◽

pp. 1220

Author(s):

Kamil Erguler

Keyword(s):

Population Dynamics ◽

Discrete Time ◽

Uniform Design ◽

Disease Spread ◽

Dependent Manner ◽

Dynamics Model ◽

Fixed Rate ◽

Animal Populations ◽

Population Dynamics Model ◽

Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-dependent epidemiological processes.

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sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽

10.12688/f1000research.15824.1 ◽

2018 ◽

Vol 7 ◽

pp. 1220 ◽

Cited By ~ 1

Author(s):

Kamil Erguler

Keyword(s):

Population Dynamics ◽

Discrete Time ◽

Uniform Design ◽

Disease Spread ◽

Dependent Manner ◽

Dynamics Model ◽

Fixed Rate ◽

Animal Populations ◽

Population Dynamics Model ◽

Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed-rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-delayed epidemiological processes.

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Seasonality impacts collective movements in a wild group-living bird

Movement Ecology ◽

10.1186/s40462-021-00271-9 ◽

2021 ◽

Vol 9 (1) ◽

Author(s):

Danai Papageorgiou ◽

David Rozen-Rechels ◽

Brendah Nyaguthii ◽

Damien R. Farine

Keyword(s):

Scale Up ◽

Group Living ◽

Population Level ◽

Fold Increase ◽

Gps Tracking ◽

Animal Populations ◽

Distribution Of Resources ◽

Collective Movements ◽

Group Members ◽

Induced Changes

Abstract Background A challenge faced by animals living in groups with stable long-term membership is to effectively coordinate their actions and maintain cohesion. However, as seasonal conditions alter the distribution of resources across a landscape, they can change the priority of group members and require groups to adapt and respond collectively across changing contexts. Little is known about how stable group-living animals collectively modify their movement behaviour in response to environment changes, such as those induced by seasonality. Further, it remains unclear how environment-induced changes in group-level movement behaviours might scale up to affect population-level properties, such as a population’s footprint. Methods Here we studied the collective movement of each distinct social group in a population of vulturine guineafowl (Acryllium vulturinum), a largely terrestrial and non-territorial bird. We used high-resolution GPS tracking of group members over 22 months, combined with continuous time movement models, to capture how and where groups moved under varying conditions, driven by seasonality and drought. Results Groups used larger areas, travelled longer distances, and moved to new places more often during drier seasons, causing a three-fold increase in the area used at the population level when conditions turned to drought. By contrast, groups used smaller areas with more regular movements during wetter seasons. Conclusions The consistent changes in collective outcomes we observed in response to different environments raise questions about the role of collective behaviour in facilitating, or impeding, the capacity for individuals to respond to novel environmental conditions. As droughts will be occurring more often under climate change, some group living animals may have to respond to them by expressing dramatic shifts in their regular movement patterns. These shifts can have consequences on their ranging behaviours that can scale up to alter the footprints of animal populations.

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sPop: Age-structured discrete-time population dynamics model in C, Python, and R

F1000Research ◽

10.12688/f1000research.15824.2 ◽

2018 ◽

Vol 7 ◽

pp. 1220

Author(s):

Kamil Erguler

Keyword(s):

Population Dynamics ◽

Discrete Time ◽

Uniform Design ◽

Disease Spread ◽

Dependent Manner ◽

Dynamics Model ◽

Fixed Rate ◽

Animal Populations ◽

Population Dynamics Model ◽

Age Structured

This article describes the sPop packages implementing the deterministic and stochastic versions of an age-structured discrete-time population dynamics model. The packages enable mechanistic modelling of a population by monitoring the age and development stage of each individual. Survival and development are included as the main effectors and they progress at a user-defined pace: follow a fixed-rate, delay for a given time, or progress at an age-dependent manner. The model is implemented in C, Python, and R with a uniform design to ease usage and facilitate adoption. Early versions of the model were previously employed for investigating climate-driven population dynamics of the tiger mosquito and the chikungunya disease spread by this vector. The sPop packages presented in this article enable the use of the model in a range of applications extending from vector-borne diseases towards any age-structured population including plant and animal populations, microbial dynamics, host-pathogen interactions, infectious diseases, and other time-dependent epidemiological processes.

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Spatial and temporal dynamics of space use by free‐ranging domestic dogs Canis familiaris in rural Africa

Ecological Applications ◽

10.1002/eap.2328 ◽

2021 ◽

Author(s):

Jared K. Wilson‐Aggarwal ◽

Cecily E.D. Goodwin ◽

Tchonfienet Moundai ◽

Metinou K. Sidouin ◽

George J.F. Swan ◽

...

Keyword(s):

Temporal Dynamics ◽

Canis Familiaris ◽

Space Use ◽

Domestic Dogs ◽

Spatial And Temporal Dynamics ◽

Rural Africa ◽

Free Ranging

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Human-induced changes in habitat preference by capybaras (Hydrochoerus hydrochaeris) and their potential effect on zoonotic disease transmission

10.1101/2020.02.05.935445 ◽

2020 ◽

Author(s):

Thiago C. Dias ◽

Jared A. Stabach ◽

Qiongyu Huang ◽

Marcelo B. Labruna ◽

Peter Leimgruber ◽

...

Keyword(s):

Habitat Selection ◽

Disease Transmission ◽

Resource Selection ◽

Spotted Fever ◽

Space Use ◽

Zoonotic Disease ◽

Disease Spread ◽

Selection Strategies ◽

Hydrochoerus Hydrochaeris ◽

Natural Landscapes

AbstractHuman activities are changing landscape structure and function globally, affecting wildlife space use, and ultimately increasing human-wildlife conflicts and zoonotic disease spread. Capybara (Hydrochoerus hydrochaeris) is a conflict species that has been implicated in the spread and amplification of the most lethal tick-borne disease in the world, the Brazilian spotted fever (BSF). Even though essential to understand the link between capybaras, ticks and the BSF, many knowledge gaps still exist regarding the effects of human disturbance in capybara space use. Here, we analyzed diurnal and nocturnal habitat selection strategies of capybaras across natural and human-modified landscapes using resource selection functions (RSF). Selection for forested habitats was high across human- modified landscapes, mainly during day- periods. Across natural landscapes, capybaras avoided forests during both day- and night periods. Water was consistently selected across both landscapes, during day- and nighttime. This variable was also the most important in predicting capybara habitat selection across natural landscapes. Capybaras showed slightly higher preferences for areas near grasses/shrubs across natural landscapes, and this variable was the most important in predicting capybara habitat selection across human-modified landscapes. Our results demonstrate human-driven variation in habitat selection strategies by capybaras. This behavioral adjustment across human-modified landscapes may be related to BSF epidemiology.

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Survival analyses

10.1093/oso/9780198838609.003.0013 ◽

2021 ◽

pp. 229-244

Author(s):

Sarah Cubaynes ◽

Simon Galas ◽

Myriam Richaud ◽

Ana Sanz Aguilar ◽

Roger Pradel ◽

...

Keyword(s):

Survival Data ◽

Complex Life Cycle ◽

Mortality Data ◽

Human Populations ◽

Imperfect Detection ◽

Survival Analyses ◽

Kaplan Meier ◽

Animal Populations ◽

Free Ranging ◽

The Impact

Survival analyses are a key tool for demographers, ecologists, and evolutionary biologists. This chapter presents the most common methods and illustrates their use for species across the Tree of Life. It discusses the challenges associated with various types of survival data, how to model species with a complex life cycle, and includes the impact of environmental factors and individual heterogeneity. It covers the analysis of ‘known-fate’ data collected in lab conditions, using the Kaplan–Meier estimator and Cox’s proportional hazard regression analysis. Alternatively, survival data collected on free-ranging populations usually involve individuals missing at certain monitoring occasions and unknown time at death. The chapter provides an overview of capture–mark–recapture (CMR) models, from single-state to multi-state and multi-event models, and their use in animal and plant demography to estimate demographic parameters while correcting for imperfect detection of individuals. It discusses various inference frameworks available to implement CMR models using a frequentist or Bayesian approach. Only humans are an exception among free-ranging populations, with the existence of several consequent databases with perfect knowledge of age and cause of death for all individuals. The chapter presents an overview of the most common models used to describe mortality patterns over age and time using human mortality data. Throughout, focus is placed on eight case studies, which involve lab organisms, free-ranging animal populations, plant populations, and human populations. Each example includes data and codes, together with step-by-step guidance to run the survival analysis.

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Environmental heterogeneity decreases reproductive success via effects on foraging behaviour

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2019.0795 ◽

2019 ◽

Vol 286 (1904) ◽

pp. 20190795 ◽

Cited By ~ 2

Author(s):

Alice M. Trevail ◽

Jonathan A. Green ◽

Jonathan Sharples ◽

Jeff A. Polton ◽

Peter I. Miller ◽

...

Keyword(s):

Reproductive Success ◽

Environmental Heterogeneity ◽

Optimal Foraging Theory ◽

Gps Tracking ◽

Heterogeneous Environments ◽

Rissa Tridactyla ◽

Distribution Of Resources ◽

Resource Patches ◽

Patch Density ◽

The Cost

Environmental heterogeneity shapes the uneven distribution of resources available to foragers, and is ubiquitous in nature. Optimal foraging theory predicts that an animal's ability to exploit resource patches is key to foraging success. However, the potential fitness costs and benefits of foraging in a heterogeneous environment are difficult to measure empirically. Heterogeneity may provide higher-quality foraging opportunities, or alternatively could increase the cost of resource acquisition because of reduced patch density or increased competition. Here, we study the influence of physical environmental heterogeneity on behaviour and reproductive success of black-legged kittiwakes, Rissa tridactyla . From GPS tracking data at 15 colonies throughout their British and Irish range, we found that environments that were physically more heterogeneous were associated with longer trip duration, more time spent foraging while away from the colony, increased overlap of foraging areas between individuals and lower breeding success. These results suggest that there is greater competition between individuals for finite resources in more heterogeneous environments, which comes at a cost to reproduction. Resource hotspots are often considered beneficial, as individuals can learn to exploit them if sufficiently predictable. However, we demonstrate here that such fitness gains can be countered by greater competition in more heterogeneous environments.

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Temporal variation in temperature determines disease spread and maintenance in Paramecium microcosm populations

Proceedings of The Royal Society B Biological Sciences ◽

10.1098/rspb.2011.0287 ◽

2011 ◽

Vol 278 (1723) ◽

pp. 3412-3420 ◽

Cited By ~ 24

Author(s):

Alison B. Duncan ◽

Simon Fellous ◽

Oliver Kaltz

Keyword(s):

Temporal Variation ◽

High Temperatures ◽

Species Interactions ◽

Life Histories ◽

Variable Temperature ◽

Parasite Prevalence ◽

Disease Spread ◽

Negative Effects ◽

Environmental Variance ◽

Variable Environment

The environment is rarely constant and organisms are exposed to temporal and spatial variations that impact their life histories and inter-species interactions. It is important to understand how such variations affect epidemiological dynamics in host–parasite systems. We explored effects of temporal variation in temperature on experimental microcosm populations of the ciliate Paramecium caudatum and its bacterial parasite Holospora undulata . Infected and uninfected populations of two P. caudatum genotypes were created and four constant temperature treatments (26°C, 28°C, 30°C and 32°C) compared with four variable treatments with the same mean temperatures. Variable temperature treatments were achieved by alternating populations between permissive (23°C) and restrictive (35°C) conditions daily over 30 days. Variable conditions and high temperatures caused greater declines in Paramecium populations, greater fluctuations in population size and higher incidence of extinction. The additional effect of parasite infection was additive and enhanced the negative effects of the variable environment and higher temperatures by up to 50 per cent. The variable environment and high temperatures also caused a decrease in parasite prevalence (up to 40%) and an increase in extinction (absence of detection) (up to 30%). The host genotypes responded similarly to the different environmental stresses and their effect on parasite traits were generally in the same direction. This work provides, to our knowledge, the first experimental demonstration that epidemiological dynamics are influenced by environmental variation. We also emphasize the need to consider environmental variance, as well as means, when trying to understand, or predict population dynamics or range.

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