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McGrane-Corrigan B, Mason O, de Andrade Moral R. Inferring stochastic group interactions within structured populations via coupled autoregression. J Theor Biol 2024; 584:111793. [PMID: 38492917 DOI: 10.1016/j.jtbi.2024.111793] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 03/04/2024] [Accepted: 03/11/2024] [Indexed: 03/18/2024]
Abstract
The internal behaviour of a population is an important feature to take account of when modelling its dynamics. In line with kin selection theory, many social species tend to cluster into distinct groups in order to enhance their overall population fitness. Temporal interactions between populations are often modelled using classical mathematical models, but these sometimes fail to delve deeper into the, often uncertain, relationships within populations. Here, we introduce a stochastic framework that aims to capture the interactions of animal groups and an auxiliary population over time. We demonstrate the model's capabilities, from a Bayesian perspective, through simulation studies and by fitting it to predator-prey count time series data. We then derive an approximation to the group correlation structure within such a population, while also taking account of the effect of the auxiliary population. We finally discuss how this approximation can lead to ecologically realistic interpretations in a predator-prey context. This approximation also serves as verification to whether the population in question satisfies our various assumptions. Our modelling approach will be useful for empiricists for monitoring groups within a conservation framework and also theoreticians wanting to quantify interactions, to study cooperation and other phenomena within social populations.
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Affiliation(s)
- Blake McGrane-Corrigan
- Department of Mathematics and Statistics, Maynooth University, Maynooth, Kildare, Ireland.
| | - Oliver Mason
- Department of Mathematics and Statistics, Maynooth University, Maynooth, Kildare, Ireland
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2
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Stringer EJ, Gruber B, Sarre SD, Wardle GM, Edwards SV, Dickman CR, Greenville AC, Duncan RP. Boom-bust population dynamics drive rapid genetic change. Proc Natl Acad Sci U S A 2024; 121:e2320590121. [PMID: 38621118 PMCID: PMC11067018 DOI: 10.1073/pnas.2320590121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 03/06/2024] [Indexed: 04/17/2024] Open
Abstract
Increasing environmental threats and more extreme environmental perturbations place species at risk of population declines, with associated loss of genetic diversity and evolutionary potential. While theory shows that rapid population declines can cause loss of genetic diversity, populations in some environments, like Australia's arid zone, are repeatedly subject to major population fluctuations yet persist and appear able to maintain genetic diversity. Here, we use repeated population sampling over 13 y and genotype-by-sequencing of 1903 individuals to investigate the genetic consequences of repeated population fluctuations in two small mammals in the Australian arid zone. The sandy inland mouse (Pseudomys hermannsburgensis) experiences marked boom-bust population dynamics in response to the highly variable desert environment. We show that heterozygosity levels declined, and population differentiation (FST) increased, during bust periods when populations became small and isolated, but that heterozygosity was rapidly restored during episodic population booms. In contrast, the lesser hairy-footed dunnart (Sminthopsis youngsoni), a desert marsupial that maintains relatively stable population sizes, showed no linear declines in heterozygosity. These results reveal two contrasting ways in which genetic diversity is maintained in highly variable environments. In one species, diversity is conserved through the maintenance of stable population sizes across time. In the other species, diversity is conserved through rapid genetic mixing during population booms that restores heterozygosity lost during population busts.
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Affiliation(s)
- Emily J. Stringer
- Centre for Conservation Ecology and Genomics, Institute for Applied Ecology, University of Canberra, CanberraACT2617, Australia
| | - Bernd Gruber
- Centre for Conservation Ecology and Genomics, Institute for Applied Ecology, University of Canberra, CanberraACT2617, Australia
| | - Stephen D. Sarre
- Centre for Conservation Ecology and Genomics, Institute for Applied Ecology, University of Canberra, CanberraACT2617, Australia
| | - Glenda M. Wardle
- Desert Ecology Research Group, School of Life and Environmental Sciences, The University of Sydney, SydneyNSW2006, Australia
| | - Scott V. Edwards
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA02138
| | - Christopher R. Dickman
- Desert Ecology Research Group, School of Life and Environmental Sciences, The University of Sydney, SydneyNSW2006, Australia
| | - Aaron C. Greenville
- Desert Ecology Research Group, School of Life and Environmental Sciences, The University of Sydney, SydneyNSW2006, Australia
| | - Richard P. Duncan
- Centre for Conservation Ecology and Genomics, Institute for Applied Ecology, University of Canberra, CanberraACT2617, Australia
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3
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Nistelberger HM, Roycroft E, Macdonald AJ, McArthur S, White LC, Grady PGS, Pierson J, Sims C, Cowen S, Moseby K, Tuft K, Moritz C, Eldridge MDB, Byrne M, Ottewell K. Genetic mixing in conservation translocations increases diversity of a keystone threatened species, Bettongia lesueur. Mol Ecol 2023. [PMID: 37715549 DOI: 10.1111/mec.17119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Revised: 07/11/2023] [Accepted: 08/17/2023] [Indexed: 09/17/2023]
Abstract
Translocation programmes are increasingly being informed by genetic data to monitor and enhance conservation outcomes for both natural and established populations. These data provide a window into contemporary patterns of genetic diversity, structure and relatedness that can guide managers in how to best source animals for their translocation programmes. The inclusion of historical samples, where possible, strengthens monitoring by allowing assessment of changes in genetic diversity over time and by providing a benchmark for future improvements in diversity via management practices. Here, we used reduced representation sequencing (ddRADseq) data to report on the current genetic health of three remnant and seven translocated boodie (Bettongia lesueur) populations, now extinct on the Australian mainland. In addition, we used exon capture data from seven historical mainland specimens and a subset of contemporary samples to compare pre-decline and current diversity. Both data sets showed the significant impact of population founder source (whether multiple or single) on the genetic diversity of translocated populations. Populations founded by animals from multiple sources showed significantly higher genetic diversity than the natural remnant and single-source translocation populations, and we show that by mixing the most divergent populations, exon capture heterozygosity was restored to levels close to that observed in pre-decline mainland samples. Relatedness estimates were surprisingly low across all contemporary populations and there was limited evidence of inbreeding. Our results show that a strategy of genetic mixing has led to successful conservation outcomes for the species in terms of increasing genetic diversity and provides strong rationale for mixing as a management strategy.
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Affiliation(s)
- Heidi M Nistelberger
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Emily Roycroft
- Division of Ecology & Evolution, Research School of Biology, ANU College of Science, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Anna J Macdonald
- Division of Ecology & Evolution, Research School of Biology, ANU College of Science, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Shelley McArthur
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Lauren C White
- Department of Environment, Land, Water and Planning, Arthur Rylah Institute for Environmental Research, Heidelberg, Victoria, Australia
| | - Patrick G S Grady
- Department of Molecular and Cell Biology, University of Connecticut, Storrs, Connecticut, USA
| | - Jennifer Pierson
- Australian Wildlife Conservancy, Subiaco, Western Australia, Australia
| | - Colleen Sims
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Saul Cowen
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Katherine Moseby
- Centre for Ecosystem Science, School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | | | - Craig Moritz
- Division of Ecology & Evolution, Research School of Biology, ANU College of Science, The Australian National University, Canberra, Australian Capital Territory, Australia
| | - Mark D B Eldridge
- Terrestrial Vertebrates, Australian Museum Research Institute, Sydney, New South Wales, Australia
| | - Margaret Byrne
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
| | - Kym Ottewell
- Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, Kensington, Western Australia, Australia
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4
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Geary WL, Tulloch AIT, Ritchie EG, Doherty TS, Nimmo DG, Maxwell MA, Wayne AF. Identifying historical and future global change drivers that place species recovery at risk. GLOBAL CHANGE BIOLOGY 2023; 29:2953-2967. [PMID: 36864646 DOI: 10.1111/gcb.16661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 11/28/2022] [Indexed: 05/03/2023]
Abstract
Ecosystem management in the face of global change requires understanding how co-occurring threats affect species and communities. Such an understanding allows for effective management strategies to be identified and implemented. An important component of this is differentiating between factors that are within (e.g. invasive predators) or outside (e.g. drought, large wildfires) of a local manager's control. In the global biodiversity hotspot of south-western Australia, small- and medium-sized mammal species are severely affected by anthropogenic threats and environmental disturbances, including invasive predators, fire, and declining rainfall. However, the relative importance of different drivers has not been quantified. We used data from a long-term monitoring program to fit Bayesian state-space models that estimated spatial and temporal changes in the relative abundance of four threatened mammal species: the woylie (Bettongia penicillata), chuditch (Dasyurus geoffroii), koomal (Trichosurus vulpecula) and quenda (Isoodon fusciventor). We then use Bayesian structural equation modelling to identify the direct and indirect drivers of population changes, and scenario analysis to forecast population responses to future environmental change. We found that habitat loss or conversion and reduced primary productivity (caused by rainfall declines) had greater effects on species' spatial and temporal population change than the range of fire and invasive predator (the red fox Vulpes vulpes) management actions observed in the study area. Scenario analysis revealed that a greater extent of severe fire and further rainfall declines predicted under climate change, operating in concert are likely to further reduce the abundance of these species, but may be mitigated partially by invasive predator control. Considering both historical and future drivers of population change is necessary to identify the factors that risk species recovery. Given that both anthropogenic pressures and environmental disturbances can undermine conservation efforts, managers must consider how the relative benefit of conservation actions will be shaped by ongoing global change.
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Affiliation(s)
- William L Geary
- School of Life and Environmental Sciences (Burwood Campus), Centre for Integrative Ecology, Deakin University, Geelong, Victoria, Australia
- Biodiversity Division, Department of Environment, Land, Water and Planning, East Melbourne, Victoria, Australia
| | - Ayesha I T Tulloch
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
- School of Biology and Environmental Science, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Euan G Ritchie
- School of Life and Environmental Sciences (Burwood Campus), Centre for Integrative Ecology, Deakin University, Geelong, Victoria, Australia
| | - Tim S Doherty
- School of Life and Environmental Sciences, The University of Sydney, Sydney, New South Wales, Australia
| | - Dale G Nimmo
- Gulbali Institute, School of Agricultural, Environmental and Veterinary Sciences, Charles Sturt University, New South Wales, Albury, Australia
| | - Marika A Maxwell
- Department of Biodiversity, Conservation and Attractions, Manjimup, Western Australia, Australia
| | - Adrian F Wayne
- Department of Biodiversity, Conservation and Attractions, Manjimup, Western Australia, Australia
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5
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Peterson KA, Barnes MD, Jeynes‐Smith C, Cowen S, Gibson L, Sims C, Baker CM, Bode M. Reconstructing lost ecosystems: A risk analysis framework for planning multispecies reintroductions under severe uncertainty. J Appl Ecol 2021. [DOI: 10.1111/1365-2664.13965] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Katie A. Peterson
- School of Mathematical Sciences Queensland University of Technology Brisbane Qld Australia
- ARC Centre of Excellence for Coral Reef Studies James Cook University Townsville Qld Australia
- National Socio‐Environmental Synthesis Center University of Maryland Annapolis MD USA
| | - Megan D. Barnes
- Biodiversity and Conservation Science Western Australian Department of Biodiversity, Conservation and Attractions Perth WA Australia
| | - Cailan Jeynes‐Smith
- School of Mathematical Sciences Queensland University of Technology Brisbane Qld Australia
| | - Saul Cowen
- Biodiversity and Conservation Science Western Australian Department of Biodiversity, Conservation and Attractions Perth WA Australia
- School of Biological Sciences The University of Western Australia Perth WA Australia
| | - Lesley Gibson
- Biodiversity and Conservation Science Western Australian Department of Biodiversity, Conservation and Attractions Perth WA Australia
- School of Biological Sciences The University of Western Australia Perth WA Australia
| | - Colleen Sims
- Biodiversity and Conservation Science Western Australian Department of Biodiversity, Conservation and Attractions Perth WA Australia
| | - Christopher M. Baker
- School of Mathematics and Statistics The University of Melbourne Melbourne Vic. Australia
- Melbourne Centre for Data Science The University of Melbourne Melbourne Vic. Australia
- Centre of Excellence for Biosecurity Risk Analysis The University of Melbourne Melbourne Vic. Australia
| | - Michael Bode
- School of Mathematical Sciences Queensland University of Technology Brisbane Qld Australia
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6
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Becker JA, Hutchinson MC, Potter AB, Park S, Guyton JA, Abernathy K, Americo VF, Conceiçāo A, Kartzinel TR, Kuziel L, Leonard NE, Lorenzi E, Martins NC, Pansu J, Scott WL, Stahl MK, Torrens KR, Stalmans ME, Long RA, Pringle RM. Ecological and behavioral mechanisms of density‐dependent habitat expansion in a recovering African ungulate population. ECOL MONOGR 2021. [DOI: 10.1002/ecm.1476] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Justine A. Becker
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
- Department of Zoology and Physiology, University of Wyoming, Laramie, Wyoming, 82072, USA
| | - Matthew C. Hutchinson
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
| | - Arjun B. Potter
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
| | - Shinkyu Park
- Department of Mechanical and Aerospace Engineering Princeton University Princeton New Jersey 08544 USA
| | - Jennifer A. Guyton
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
| | - Kyler Abernathy
- Exploration Technology Lab National Geographic Society Washington D.C. 20036 USA
| | - Victor F. Americo
- Department of Scientific Services Parque Nacional da Gorongosa Sofala Mozambique
| | - Anagledis Conceiçāo
- Department of Scientific Services Parque Nacional da Gorongosa Sofala Mozambique
| | - Tyler R. Kartzinel
- Department of Ecology and Evolutionary Biology Brown University Providence Rhode Island 02912 USA
- Institute at Brown for Environment and Society Brown University Providence Rhode Island 02912 USA
| | - Luca Kuziel
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
| | - Naomi E. Leonard
- Department of Mechanical and Aerospace Engineering Princeton University Princeton New Jersey 08544 USA
| | - Eli Lorenzi
- Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA
| | - Nuno C. Martins
- Department of Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA
| | - Johan Pansu
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
- Station Biologique de Roscoff UMR 7144 CNRS‐Sorbonne Université Roscoff France
- CSIRO Ocean & Atmosphere Lucas Heights New South Wales Australia
| | - William L. Scott
- Department of Mechanical Engineering Bucknell University Lewisburg Pennsylvania 17837 USA
| | - Maria K. Stahl
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
| | - Kai R. Torrens
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
| | - Marc E. Stalmans
- Department of Scientific Services Parque Nacional da Gorongosa Sofala Mozambique
| | - Ryan A. Long
- Department of Fish and Wildlife Sciences University of Idaho Moscow Idaho 83844 USA
| | - Robert M. Pringle
- Department of Ecology and Evolutionary Biology Princeton University Princeton New Jersey 08544 USA
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