Coupling movement and landscape ecology for animal conservation in production landscapes

Doherty, Tim S.; Driscoll, Don A.

doi:10.1098/rspb.2017.2272

Cited by 96 publications

(81 citation statements)

References 80 publications

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“…In our model, we have used two mechanistic movement rules, HDM and CDM, in addition to the phenomenological CRW rule. Movement decisions based on the in response to environmental factors such as resources and shelter or to conspecifics is a typical driver of animal movement and used as a basis for movement analyses and simulation (Smouse et al , Doherty and Driscoll ). In our approach, HDM leads to crowding of animals in high‐quality patches and thus can be seen as a positive density‐dependent movement while we simulate CDM as negative density‐dependent.…”

Section: Discussionmentioning

confidence: 99%

Moving infections: individual movement decisions drive disease persistence in spatially structured landscapes

Scherer

Radchuk

Franz

et al. 2020

Oikos

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Understanding host–pathogen dynamics requires realistic consideration of transmission events that, in the case of directly transmitted pathogens, result from contacts between susceptible and infected individuals. The corresponding contact rates are usually heterogeneous due to variation in individual movement patterns and the underlying landscape structure. However, in epidemiological models, the roles that explicit host movements and landscape structure play in shaping contact rates are often overlooked. We adapted an established agent‐based model of classical swine fever (CSF) in wild boar Sus scrofa to investigate how explicit representation of landscape heterogeneity and host movement between social groups affects invasion and persistence probabilities. We simulated individual movement both phenomenologically as a correlated random walk (CRW) and mechanistically by representing interactions of the moving individuals with the landscape and host population structure. The effect of landscape structure on the probability of invasion success and disease persistence depended remarkably on the way host movement is simulated and the case fatality ratio associated with the pathogen strain. The persistence probabilities were generally low with CRW which ignores feedbacks to external factors. Although the basic reproduction number R0, a measure of the contagiousness of an infectious disease, was kept constant, these probabilities were up to eight times higher under mechanistic movement rules, especially in heterogeneous landscapes. The increased persistence emerged due to important feedbacks of the directed movement on the spatial variation of host density, contact rates and transmission events to distant areas. Our findings underscore the importance of accounting for spatial context and group size structures in eco‐epidemiological models. Our study highlights that the simulation of explicit, mechanistic movement behaviour can reverse predictions of disease persistence in comparison to phenomenological rules such as random walk approaches. This can have severe consequences when predicting the probability of disease persistence and assessing control measures to prevent outbreaks.

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Section: Discussionmentioning

confidence: 99%

Moving infections: individual movement decisions drive disease persistence in spatially structured landscapes

Scherer

Radchuk

Franz

et al. 2020

Oikos

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“…Occupancy can also be influenced by movement (Nathan et al, 2008;Pavlacky et al, 2012) which is affected by size and flying ability (De Bie et al, 2012;Doherty & Driscoll, 2018), and could interact with time since fire. For example, flying species can be most abundant shortly after fire because they are rapid colonisers (Ribera et al, 2001;Moretti et al, 2004;Podgaiski et al, 2018).…”

Section: Discussionmentioning

confidence: 99%

Interactions among body size, trophic level, and dispersal traits predict beetle detectability and occurrence responses to fire

Driscoll

Smith

Blight

et al. 2019

Ecological Entomology

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1. Testing the extent to which traits act alone or in combination with other traits to influence responses to fire informs the trade‐off between increased generalisation using single traits and increased predictive power using interactions. This study investigated the following question: do four traits (body size, trophic group, dispersal ability, and stratum of the ecosystem), alone or in combination, best explain changes in beetle occurrence with time since fire? 2. The data from 4 years and 15 independent fires in southern Australia were analysed using generalised linear mixed models. The study also assessed whether detectability depends on time since fire using multi‐year detection models, because detectability has the potential to confound occurrence patterns. 3. The best model included the three‐way combination of size, flight, and trophic level interacting with time since fire and with year. The relationship between detectability and time since fire was similar to the occurrence relationship in six of the 10 trait–combination groups, with flightless species generally showing reduced detection probability as time since fire increased. Detectability did not confound occurrence responses for four trait groups, with three increasing with time since fire and one decreasing. 4. Generalisation using main effects of traits risks oversimplifying animal responses to fire, because combinations of traits influence the direction and magnitude of the response. Also, taking detectability into account is critical to correctly interpretating occupancy data. Three‐way trait combinations that differ by just one trait, particularly dispersal ability, can result in either negligible effects of disturbance on detectability or strong effects that influence observed occurrence.

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“…For example, a patch‐dependent animal may avoid crossing habitat edges, or its movement pattern may vary in distance or orientation, depending on the quality of the adjacent matrix (Long et al ., ; Rittenhouse & Semlitsch, ; Cooney, Schauber & Hellgren, ). Thus, identifying which species are sensitive to habitat modification has important implications for management, as well as advancing ecological concepts about the matrix (Driscoll et al ., ; Doherty & Driscoll, ).…”

Section: Introductionmentioning

confidence: 99%

“…The persistence and occupation of native habitat specialists within fragments depends on an individual's ability to disperse through modified habitats and between patches as well as cope with rapid changes to their habitat (Sarre, Smith & Meyers, ; Rittenhouse & Semlitsch, ; Connette & Semlitsch, ). Thus, movement patterns of patch‐dependent animals in response to habitat edges, and to the perceived habitat quality of the adjacent matrix, can be important determinants of functional connectivity across landscapes (Baguette & Van Dyck, ; Connette & Semlitsch, ; Doherty & Driscoll, ).…”

Section: Introductionmentioning

confidence: 99%

Movement patterns of an arboreal gecko in fragmented agricultural landscapes reveal matrix avoidance

Hansen

Driscoll

Michael

et al. 2019

Animal Conservation

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Animal movement through agricultural landscapes is critical for population persistence of species within fragmented native vegetation patches. However, perceived habitat quality and the structural changes between differing land uses within such landscapes can reduce an animal's willingness to move. Understanding when animal movement behaviour varies in response to differing habitat types is necessary for identifying barriers to movement between habitat patches. We quantified the homing success and fine-scale movement behaviour of a patch-dependent gecko, Gehyra versicolor, in remnant patches, three different matrix types (crop, pasture and linear plantings), and at varying distances from the edge using fluorescent powder tracking, radio-telemetry and experimental displacement. We found displaced geckos in pasture environments orientated more strongly and moved farther into farmland after being released and, away from their home ranges in remnant patches. In contrast, we found strong homing ability of displaced animals in plantings and crop matrix types, with animals moving towards remnant patches and away from farmland. Importantly, from the 48 individuals radio-tracked, none moved into farmland, including pastures, despite 16 individuals approaching edge habitat. Because radio-tracked geckos did not move into pastures, or any other matrix type, movement further into pasture by displaced animals likely represents limited orientation capacity in pasture rather than preference for pasture. We conclude geckos behaviourally avoided the farmland, irrespective of the presence of complex habitat (e.g. linear plantings). Our findings suggest that, despite efforts to improve farmland quality by planting, farmland is not generally preferred compared to remnant native vegetation. Understanding habitat-specific movement behaviour is crucial to effectively identifying barriers to animal movement and will improve our efforts to conserve regional populations of patch-dependent species.

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Coupling movement and landscape ecology for animal conservation in production landscapes

Cited by 96 publications

References 80 publications

Moving infections: individual movement decisions drive disease persistence in spatially structured landscapes

Moving infections: individual movement decisions drive disease persistence in spatially structured landscapes

Interactions among body size, trophic level, and dispersal traits predict beetle detectability and occurrence responses to fire

Movement patterns of an arboreal gecko in fragmented agricultural landscapes reveal matrix avoidance

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