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Strasburg M, Christensen S. Evaluating the Interaction of Emerging Diseases on White-Tailed Deer Populations Using an Agent-Based Modeling Approach. Pathogens 2024; 13:545. [PMID: 39057772 PMCID: PMC11279658 DOI: 10.3390/pathogens13070545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2024] [Revised: 06/04/2024] [Accepted: 06/21/2024] [Indexed: 07/28/2024] Open
Abstract
Disease co-occurrence in wildlife populations is common yet understudied. In the case of disease-caused mortality, the mortality attributed to one disease has the potential to buffer populations against subsequent alternative disease outbreaks by reducing populations and thus contacts needed to sustain disease transmission. However, substantial disease-driven population declines may also prevent populations from recovering, leading to localized extinctions. Hemorrhagic disease (HD), a vector-transmitted, viral disease in white-tailed deer (WTD), similar to chronic wasting disease (CWD), a prion disease, has increased in frequency and distribution in the United States. However, unlike CWD, which progresses slowly, HD can cause mortality only days after infection. Hemorrhagic disease outbreaks can result in substantial localized mortality events in WTD near vector habitats such as wetlands and may reduce local deer densities and consequent CWD transmission. The objective of our study was to evaluate the potential for HD outbreaks to buffer CWD risk where the diseases co-occur. Using an agent-based modeling approach, we found that frequent, intense HD outbreaks have the potential to mitigate CWD risk, especially if those outbreaks occur shortly after CWD introduction. However, HD outbreaks that do not result in substantial WTD mortality are unlikely to impact CWD or WTD population dynamics. Severe HD outbreaks may reduce CWD cases and could present an opportunity for managers to boost CWD control initiatives in a post-HD outbreak year.
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Affiliation(s)
| | - Sonja Christensen
- Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 48824, USA;
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2
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Bush A, Simpson KH, Hanley N. Systematic nature positive markets. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2024; 38:e14216. [PMID: 37937469 DOI: 10.1111/cobi.14216] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 09/14/2023] [Accepted: 10/25/2023] [Indexed: 11/09/2023]
Abstract
Environmental markets are a rapidly emerging tool to mobilize private funding to incentivize landholders to undertake more sustainable land management. How units of biodiversity in these markets are measured and subsequently traded creates key challenges ecologically and economically because it determines whether environmental markets can deliver net gains in biodiversity and efficiently lower the costs of conservation. We developed and tested a metric for such markets based on the well-established principle of irreplaceability from systematic conservation planning. Irreplaceability as a metric avoids the limitations of like-for-like trading and allows one to capture the multidimensional nature of ecosystems (e.g., habitats, species, ecosystem functioning) and simultaneously achieve cost-effective, land-manager-led investments in conservation. Using an integrated ecological modeling approach, we tested whether using irreplaceability as a metric is more ecologically and economically beneficial than the simpler biodiversity offset metrics typically used in net gain and no-net-loss policies. Using irreplaceability ensured no net loss, or even net gain, of biodiversity depending on the targets chosen. Other metrics did not provide the same assurances and, depending on the flexibility with which biodiversity targets can be achieved, and how they overlap with development pressure, were less efficient. Irreplaceability reduced the costs of offsetting to developers and the costs of ecological restoration to society. Integrating economic data and systematic conservation planning approaches would therefore assure land managers they were being fairly rewarded for the opportunity costs of conservation and transparently incentivize the most ecologically and economically efficient investments in nature recovery.
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Affiliation(s)
- Alex Bush
- Lancaster Environment Centre, Lancaster University, Lancaster, UK
| | | | - Nick Hanley
- School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, UK
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3
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Kürschner T, Scherer C, Radchuk V, Blaum N, Kramer‐Schadt S. Resource asynchrony and landscape homogenization as drivers of virulence evolution: The case of a directly transmitted disease in a social host. Ecol Evol 2024; 14:e11065. [PMID: 38380064 PMCID: PMC10877554 DOI: 10.1002/ece3.11065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Revised: 02/05/2024] [Accepted: 02/07/2024] [Indexed: 02/22/2024] Open
Abstract
Throughout the last decades, the emergence of zoonotic diseases and the frequency of disease outbreaks have increased substantially, fuelled by habitat encroachment and vectors overlapping with more hosts due to global change. The virulence of pathogens is one key trait for successful invasion. In order to understand how global change drivers such as habitat homogenization and climate change drive pathogen virulence evolution, we adapted an established individual-based model of host-pathogen dynamics. Our model simulates a population of social hosts affected by a directly transmitted evolving pathogen in a dynamic landscape. Pathogen virulence evolution results in multiple strains in the model that differ in their transmission capability and lethality. We represent the effects of global change by simulating environmental changes both in time (resource asynchrony) and space (homogenization). We found an increase in pathogenic virulence and a shift in strain dominance with increasing landscape homogenization. Our model further indicated that lower virulence is dominant in fragmented landscapes, although pulses of highly virulent strains emerged under resource asynchrony. While all landscape scenarios favoured co-occurrence of low- and high-virulent strains, the high-virulence strains capitalized on the possibility for transmission when host density increased and were likely to become dominant. With asynchrony likely to occur more often due to global change, our model showed that a subsequent evolution towards lower virulence could lead to some diseases becoming endemic in their host populations.
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Affiliation(s)
- Tobias Kürschner
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
| | - Cédric Scherer
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
| | - Viktoriia Radchuk
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
| | - Niels Blaum
- Plant Ecology and Nature ConservationUniversity of PotsdamPotsdamGermany
| | - Stephanie Kramer‐Schadt
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
- Institute of EcologyTechnische Universität BerlinBerlinGermany
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4
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Savary P, Foltête JC, Moal H, Vuidel G, Garnier S. Inferring landscape resistance to gene flow when genetic drift is spatially heterogeneous. Mol Ecol Resour 2023; 23:1574-1588. [PMID: 37332161 DOI: 10.1111/1755-0998.13821] [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: 04/07/2022] [Revised: 05/12/2023] [Accepted: 05/24/2023] [Indexed: 06/20/2023]
Abstract
In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the 'true' cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the 'true' costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the 'true' scenario (cost distance Mantel correlations), but this 'true' scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the 'true' scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.
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Affiliation(s)
- Paul Savary
- ARP-Astrance, Paris, France
- UMR 6049 Thé MA, Université de Franche-Comté, CNRS, Besançon Cedex, France
- UMR 6282 Biogéosciences, Université Bourgogne Franche-Comté, CNRS, Dijon, France
| | | | | | - Gilles Vuidel
- UMR 6049 Thé MA, Université de Franche-Comté, CNRS, Besançon Cedex, France
| | - Stéphane Garnier
- UMR 6282 Biogéosciences, Université Bourgogne Franche-Comté, CNRS, Dijon, France
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5
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Benhamou S, Courbin N. Accounting for central place foraging constraints in habitat selection studies. Ecology 2023; 104:e4134. [PMID: 37386731 DOI: 10.1002/ecy.4134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Revised: 04/25/2023] [Accepted: 06/13/2023] [Indexed: 07/01/2023]
Abstract
Habitat selection studies contrast actual space use with the expected use under the null hypothesis of no selection (hereafter neutral use). Neutral use is most often equated to the relative frequencies with which environmental features occur. This generates a considerable bias when studying habitat selection by foragers that perform numerous trips back and forth to a central place (CP). Indeed, the increased space use close to the CP with respect to distant places reflects a mechanical effect, rather than a true selection for the closest habitats. Yet, correctly estimating habitat selection by CP foragers is of paramount importance for a better understanding of their ecology and to properly plan conservation actions. We show that including the distance to the CP as a covariate in unconditional Resource Selection Functions, as applied in several studies, is ineffective to correct for the bias. This bias can be eliminated only by contrasting the actual use to an appropriate neutral use that considers the CP forager behavior. We also show that the need to specify an appropriate neutral use overall distribution can be bypassed by relying on a conditional approach, where the neutral use is assessed locally regardless of the distance to the CP.
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Affiliation(s)
- Simon Benhamou
- Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, Montpellier, France
| | - Nicolas Courbin
- Centre d'Ecologie Fonctionnelle et Evolutive, CNRS, Montpellier, France
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6
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Kiziridis DA, Mastrogianni A, Pleniou M, Tsiftsis S, Xystrakis F, Tsiripidis I. Improving the predictive performance of CLUE-S by extending demand to land transitions: The trans-CLUE-S model. Ecol Modell 2023. [DOI: 10.1016/j.ecolmodel.2023.110307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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7
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Vanhove M, Launey S. Estimating resistance surfaces using gradient forest and allelic frequencies. Mol Ecol Resour 2023. [PMID: 36847356 DOI: 10.1111/1755-0998.13778] [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: 05/24/2022] [Revised: 02/06/2023] [Accepted: 02/22/2023] [Indexed: 03/01/2023]
Abstract
Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity methods that use link-based methods traditionally rely on relating pairwise genetic distance between individuals or demes to their landscape distance (e.g., geographic distance, cost distance). In this study, we present an alternative to conventional statistical approaches to refine cost surfaces by adapting the gradient forest approach to produce a resistance surface. Used in community ecology, gradient forest is an extension of random forest, and has been implemented in genomic studies to model species genetic offset under future climatic scenarios. By design, this adapted method, resGF, has the ability to handle multiple environmental predicators and is not subjected to traditional assumptions of linear models such as independence, normality and linearity. Using genetic simulations, resistance Gradient Forest (resGF) performance was compared to other published methods (maximum likelihood population effects model, random forest-based least-cost transect analysis and species distribution model). In univariate scenarios, resGF was able to distinguish the true surface contributing to genetic diversity among competing surfaces better than the compared methods. In multivariate scenarios, the gradient forest approach performed similarly to the other random forest-based approach using least-cost transect analysis but outperformed MLPE-based methods. Additionally, two worked examples are provided using two previously published data sets. This machine learning algorithm has the potential to improve our understanding of landscape connectivity and inform long-term biodiversity conservation strategies.
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Affiliation(s)
- Mathieu Vanhove
- DECOD (Ecosystem Dynamics and Sustainability), INRAE, Institut Agro, IFREMER, Rennes, France
| | - Sophie Launey
- DECOD (Ecosystem Dynamics and Sustainability), INRAE, Institut Agro, IFREMER, Rennes, France
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8
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Lee F, Simon KS, Perry GLW. Network topology mediates freshwater fish metacommunity response to loss of connectivity. Ecosphere 2022. [DOI: 10.1002/ecs2.4286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Affiliation(s)
- Finnbar Lee
- School of Environment The University of Auckland Auckland New Zealand
| | - Kevin S. Simon
- School of Environment The University of Auckland Auckland New Zealand
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9
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Dupont G, Linden DW, Sutherland C. Improved inferences about landscape connectivity from spatial capture-recapture by integration of a movement model. Ecology 2022; 103:e3544. [PMID: 34626121 DOI: 10.1002/ecy.3544] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/04/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022]
Abstract
Understanding how broad-scale patterns in animal populations emerge from individual-level processes is an enduring challenge in ecology that requires investigation at multiple scales and perspectives. Complementary to this need for diverse approaches is the recent focus on integrated modeling in statistical ecology. Population-level processes represent the core of spatial capture-recapture (SCR), with many methodological extensions that have been motivated by standing ecological theory and data-integration opportunities. The extent to which these recent advances offer inferential improvements can be limited by the data requirements for quantifying individual-level processes. This is especially true for SCR models that use non-Euclidean distance to relax the restrictive assumption that individual space use is stationary and symmetrical to make inferences about landscape connectivity. To meet the challenges of scale and data quality, we propose integrating an explicit movement model with non-Euclidean SCR for joint estimation of a shared cost parameter between individual and population processes. Here, we define a movement kernel for step selection that uses "ecological distance" instead of Euclidean distance to quantify availability for each movement step in terms of landscape cost. We compare performance of our integrated model to that of existing SCR models using realistic animal movement simulations and data collected on black bears. We demonstrate that an integrated approach offers improvements both in terms of bias and precision in estimating the shared cost parameter over models fit to spatial encounters alone. Simulations suggest these gains were only realized when step lengths were small relative to home range size, and estimates of density were insensitive to whether or not an integrated approach was used. By combining the fine spatiotemporal scale of individual movement processes with the estimation of population density in SCR, integrated approaches such as the one we develop here have the potential to unify the fields of movement, population, and landscape ecology and improve our understanding of landscape connectivity.
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Affiliation(s)
- Gates Dupont
- Department of Environmental Conservation, University of Massachusetts, 160 Holdsworth Way, Amherst, Massachusetts, 01003, USA.,Organismic and Evolutionary Biology Graduate Program, University of Massachusetts, 204C French Hall, 230 Stockbridge Road, Amherst, Massachusetts, 01003, USA
| | - Daniel W Linden
- Greater Atlantic Regional Fisheries Office, NOAA National Marine Fisheries Service, 55 Great Republic Drive, Gloucester, Massachusetts, 01930, USA
| | - Chris Sutherland
- Department of Environmental Conservation, University of Massachusetts, 160 Holdsworth Way, Amherst, Massachusetts, 01003, USA.,Centre for Research into Ecological and Environmental Modelling, University of St Andrews, Fife, KY16 9LZ, St. Andrews, United Kingdom
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10
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Theng M, Milleret C, Bracis C, Cassey P, Delean S. Confronting spatial capture-recapture models with realistic animal movement simulations. Ecology 2022; 103:e3676. [PMID: 35253209 DOI: 10.1002/ecy.3676] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 08/26/2021] [Accepted: 09/14/2021] [Indexed: 12/13/2022]
Abstract
Spatial capture-recapture (SCR) models have emerged as a robust method to estimate the population density of mobile animals. However, model evaluation has generally been based on data simulated from simplified representations of animal space use. Here, we generated data from animal movement simulated from a mechanistic individual-based model, in which movement emerges from the individual's response to a changing environment (i.e., from the bottom-up), driven by key ecological processes (e.g., resource memory and territoriality). We drew individual detection data from simulated movement trajectories and fitted detection data sets to a basic, resource selection and transience SCR model, as well as their variants accounting for resource-driven heterogeneity in density and detectability. Across all SCR models, abundance estimates were robust to multiple, but low-degree violations of the specified movement processes (e.g., resource selection). SCR models also successfully captured the positive effect of resource quality on density. However, covariate models failed to capture the finer scale effect of resource quality on detectability and space use, which may be a consequence of the low temporal resolution of SCR data sets and/or model misspecification. We show that home-range size is challenging to infer from the scale parameter alone, compounded by reliance on conventional measures of "true" home-range size that are highly sensitive to sampling regime. Additionally, we found the transience model challenging to fit, probably due to data sparsity and violation of the assumption of normally distributed inter-occasion movement of activity centers, suggesting that further development of the model is required for general applicability. Our results showed that further integration of complex movement into SCR models may not be necessary for population estimates of abundance when the level of individual heterogeneity induced by the underlying movement process is low, but appears warranted in terms of accurately revealing finer scale patterns of ecological and movement processes. Further investigation into whether this holds true in populations with other types of realistic movement characteristics is merited. Our study provides a framework to generate realistic SCR data sets to develop and evaluate more complex movement processes in SCR models.
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Affiliation(s)
- Meryl Theng
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Cyril Milleret
- Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences, Ås, Norway
| | - Chloe Bracis
- TIMC / MAGE, Université Grenoble Alpes, Grenoble, France
| | - Phillip Cassey
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
| | - Steven Delean
- School of Biological Sciences, University of Adelaide, Adelaide, South Australia, Australia
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11
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McClure KM, Bastille‐Rousseau G, Davis AJ, Stengel CA, Nelson KM, Chipman RB, Wittemyer G, Abdo Z, Gilbert AT, Pepin KM. Accounting for animal movement improves vaccination strategies against wildlife disease in heterogeneous landscapes. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2022; 32:e2568. [PMID: 35138667 PMCID: PMC9285612 DOI: 10.1002/eap.2568] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 08/28/2021] [Accepted: 10/15/2021] [Indexed: 06/14/2023]
Abstract
Oral baiting is used to deliver vaccines to wildlife to prevent, control, and eliminate infectious diseases. A central challenge is how to spatially distribute baits to maximize encounters by target animal populations, particularly in urban and suburban areas where wildlife such as raccoons (Procyon lotor) are abundant and baits are delivered along roads. Methods from movement ecology that quantify movement and habitat selection could help to optimize baiting strategies by more effectively targeting wildlife populations across space. We developed a spatially explicit, individual-based model of raccoon movement and oral rabies vaccine seroconversion to examine whether and when baiting strategies that match raccoon movement patterns perform better than currently used baiting strategies in an oral rabies vaccination zone in greater Burlington, Vermont, USA. Habitat selection patterns estimated from locally radio-collared raccoons were used to parameterize movement simulations. We then used our simulations to estimate raccoon population rabies seroprevalence under currently used baiting strategies (actual baiting) relative to habitat selection-based baiting strategies (habitat baiting). We conducted simulations on the Burlington landscape and artificial landscapes that varied in heterogeneity relative to Burlington in the proportion and patch size of preferred habitats. We found that the benefits of habitat baiting strongly depended on the magnitude and variability of raccoon habitat selection and the degree of landscape heterogeneity within the baiting area. Habitat baiting improved seroprevalence over actual baiting for raccoons characterized as habitat specialists but not for raccoons that displayed weak habitat selection similar to radiocollared individuals, except when baits were delivered off roads where preferred habitat coverage and complexity was more pronounced. In contrast, in artificial landscapes with either more strongly juxtaposed favored habitats and/or higher proportions of favored habitats, habitat baiting performed better than actual baiting, even when raccoons displayed weak habitat preferences and where baiting was constrained to roads. Our results suggest that habitat selection-based baiting could increase raccoon population seroprevalence in urban-suburban areas, where practical, given the heterogeneity and availability of preferred habitat types in those areas. Our novel simulation approach provides a flexible framework to test alternative baiting strategies in multiclass landscapes to optimize bait-distribution strategies.
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Affiliation(s)
- Katherine M. McClure
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureFort CollinsColoradoUSA
- Department of Microbiology, Immunology, and PathologyColorado State UniversityFort CollinsColoradoUSA
- Present address:
Hawai‘i Cooperative Studies UnitUniversity of Hawai‘i at HiloHiloHawai‘iUSA
| | - Guillaume Bastille‐Rousseau
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureFort CollinsColoradoUSA
- Cooperative Wildlife Research LaboratorySouthern Illinois UniversityCarbondaleIllinoisUSA
| | - Amy J. Davis
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureFort CollinsColoradoUSA
| | - Carolyn A. Stengel
- Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureConcordNew HampshireUSA
| | - Kathleen M. Nelson
- National Rabies Management Program, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureConcordNew HampshireUSA
| | - Richard B. Chipman
- National Rabies Management Program, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureConcordNew HampshireUSA
| | - George Wittemyer
- Fish, Wildlife, and Conservation BiologyColorado State UniversityFort CollinsColoradoUSA
| | - Zaid Abdo
- Department of Microbiology, Immunology, and PathologyColorado State UniversityFort CollinsColoradoUSA
| | - Amy T. Gilbert
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureFort CollinsColoradoUSA
| | - Kim M. Pepin
- National Wildlife Research Center, Wildlife Services, Animal and Plant Health Inspection ServiceUnited States Department of AgricultureFort CollinsColoradoUSA
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12
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Landscape Characteristics Affecting Small Mammal Occurrence in Heterogeneous Olive Grove Agro-Ecosystems. CONSERVATION 2022. [DOI: 10.3390/conservation2010005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Understanding how small mammals (SM) are associated with environmental characteristics in olive groves is important to identify potential threats to agriculture and assess the overall conservation value and functioning of agro-ecosystems. Here, we provide first insights on this topic applied to traditional olive groves in northeast (NE) Portugal by assessing the landscape attributes that determine SM occurrence, focusing on one species of conservation concern (Microtus cabrerae Thomas 1906) and one species often perceived as a potential pest of olives (Microtus lusitanicus Gerbe 1879). Based on SM genetic non-invasive sampling in 51 olive groves and surrounding habitats, we identified seven rodent species and one insectivore. Occupancy modelling indicated that SM were generally less detected within olive groves than in surrounding habitats. The vulnerable M. cabrerae reached a mean occupancy (95% CI) of 0.77 (0.61–0.87), while M. lusitanicus stood at 0.37 (0.24–0.52). M. cabrerae was more likely to occur in land mosaics with high density of agricultural field edges, while M. lusitanicus was more associated with high density of pastureland patches. Overall, our study suggests that the complex structure and spatial heterogeneity of traditionally managed olive grove agro-ecosystems may favor the occurrence of species-rich SM communities, possibly including well-established populations of species of conservation importance, while keeping potential pest species at relatively low occupancy rates.
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13
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Zamberletti P, Papaïx J, Gabriel E, Opitz T. Markov random field models for vector-based representations of landscapes. Ann Appl Stat 2021. [DOI: 10.1214/21-aoas1447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Affiliation(s)
| | - Julien Papaïx
- Biostatistique et Processus Spatiaux (BioSP) , INRAE
| | - Edith Gabriel
- Biostatistique et Processus Spatiaux (BioSP) , INRAE
| | - Thomas Opitz
- Biostatistique et Processus Spatiaux (BioSP) , INRAE
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14
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Thompson PR, Derocher AE, Edwards MA, Lewis MA. Detecting seasonal episodic‐like spatio‐temporal memory patterns using animal movement modelling. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13743] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Affiliation(s)
- Peter R. Thompson
- Department of Biological Sciences University of Alberta Edmonton AB Canada
| | - Andrew E. Derocher
- Department of Biological Sciences University of Alberta Edmonton AB Canada
| | - Mark A. Edwards
- Mammalogy Department Royal Alberta Museum Edmonton AB Canada
- Department of Renewable Resources University of Alberta Edmonton AB Canada
| | - Mark A. Lewis
- Department of Biological Sciences University of Alberta Edmonton AB Canada
- Department of Mathematical and Statistical Sciences University of Alberta Edmonton AB Canada
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15
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Gallagher CA, Chimienti M, Grimm V, Nabe-Nielsen J. Energy-mediated responses to changing prey size and distribution in marine top predator movements and population dynamics. J Anim Ecol 2021; 91:241-254. [PMID: 34739086 DOI: 10.1111/1365-2656.13627] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 10/27/2021] [Indexed: 11/26/2022]
Abstract
Climate change is modifying the structure of marine ecosystems, including that of fish communities. Alterations in abiotic and biotic conditions can decrease fish size and change community spatial arrangement, ultimately impacting predator species which rely on these communities. To conserve predators and understand the drivers of observed changes in their population dynamics, we must advance our understanding of how shifting environmental conditions can impact populations by limiting food available to individuals. To investigate the impacts of changing fish size and spatial aggregation on a top predator population, we applied an existing agent-based model parameterized for harbour porpoises Phocoena phocoena which represents animal energetics and movements in high detail. We used this framework to quantify the impacts of shifting prey size and spatial aggregation on porpoise movement, space use, energetics and population dynamics. Simulated individuals were more likely to switch from area-restricted search to transit behaviour with increasing prey size, particularly when starving, due to elevated resource competition. In simulations with highly aggregated prey, higher prey encounter rates counteracted resource competition, resulting in no impacts of prey spatial aggregation on movement behaviour. Reduced energy intake with decreasing prey size and aggregation level caused population decline, with a 15% decrease in fish length resulting in total population collapse Increasing prey consumption rates by 42.8 ± 4.5% could offset population declines; however, this increase was 21.3 ± 12.7% higher than needed to account for changes in total energy availability alone. This suggests that animals in realistic seascapes require additional energy to locate smaller prey which should be considered when assessing the impacts of decreased energy availability. Changes in prey size and aggregation influenced movements and population dynamics of simulated harbour porpoises, revealing that climate-induced changes in prey structure, not only prey abundance, may threaten predator populations. We demonstrate how a population model with realistic animal movements and process-based energetics can be used to investigate population consequences of shifting food availability, such as those mediated by climate change, and provide a mechanistic explanation for how changes in prey structure can impact energetics, behaviour and ultimately viability of predator populations.
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Affiliation(s)
- Cara A Gallagher
- Department of Ecoscience, Aarhus University, Roskilde, Denmark.,Plant Ecology and Nature Conservation, University of Potsdam, Potsdam, Germany
| | - Marianna Chimienti
- Department of Ecoscience, Aarhus University, Roskilde, Denmark.,Centre d'Etudes Biologiques de Chizé, Villiers-en-Bois, France
| | - Volker Grimm
- Plant Ecology and Nature Conservation, University of Potsdam, Potsdam, Germany.,Department of Ecological Modelling, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
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16
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Cretois B, Simmonds EG, Linnell JDC, van Moorter B, Rolandsen CM, Solberg EJ, Strand O, Gundersen V, Roer O, Rød JK. Identifying and correcting spatial bias in opportunistic citizen science data for wild ungulates in Norway. Ecol Evol 2021; 11:15191-15204. [PMID: 34765170 PMCID: PMC8571602 DOI: 10.1002/ece3.8200] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 09/16/2021] [Accepted: 09/21/2021] [Indexed: 11/27/2022] Open
Abstract
Many publications make use of opportunistic data, such as citizen science observation data, to infer large-scale properties of species' distributions. However, the few publications that use opportunistic citizen science data to study animal ecology at a habitat level do so without accounting for spatial biases in opportunistic records or using methods that are difficult to generalize. In this study, we explore the biases that exist in opportunistic observations and suggest an approach to correct for them. We first examined the extent of the biases in opportunistic citizen science observations of three wild ungulate species in Norway by comparing them to data from GPS telemetry. We then quantified the extent of the biases by specifying a model of the biases. From the bias model, we sampled available locations within the species' home range. Along with opportunistic observations, we used the corrected availability locations to estimate a resource selection function (RSF). We tested this method with simulations and empirical datasets for the three species. We compared the results of our correction method to RSFs obtained using opportunistic observations without correction and to RSFs using GPS-telemetry data. Finally, we compared habitat suitability maps obtained using each of these models. Opportunistic observations are more affected by human access and visibility than locations derived from GPS telemetry. This has consequences for drawing inferences about species' ecology. Models naïvely using opportunistic observations in habitat-use studies can result in spurious inferences. However, sampling availability locations based on the spatial biases in opportunistic data improves the estimation of the species' RSFs and predicted habitat suitability maps in some cases. This study highlights the challenges and opportunities of using opportunistic observations in habitat-use studies. While our method is not foolproof it is a first step toward unlocking the potential of opportunistic citizen science data for habitat-use studies.
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Affiliation(s)
- Benjamin Cretois
- Department of GeographyNorwegian University of Science and TechnologyTrondheimNorway
- Norwegian Institute for Nature ResearchTrondheimNorway
| | - Emily G. Simmonds
- Department of Mathematical SciencesNorwegian University of Science and TechnologyTrondheimNorway
| | - John D. C. Linnell
- Norwegian Institute for Nature ResearchTrondheimNorway
- Department of Forestry and Wildlife ManagementInland Norway University of Applied SciencesKoppandNorway
| | | | | | | | - Olav Strand
- Norwegian Institute for Nature ResearchTrondheimNorway
| | | | - Ole Roer
- Faun Naturforvaltning ASFyresdalNorway
| | - Jan Ketil Rød
- Department of GeographyNorwegian University of Science and TechnologyTrondheimNorway
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17
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Wagner B, Baker PJ, Nitschke CR. The influence of spatial patterns in foraging habitat on the abundance and home range size of a vulnerable arboreal marsupial in southeast Australia. CONSERVATION SCIENCE AND PRACTICE 2021. [DOI: 10.1111/csp2.566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022] Open
Affiliation(s)
- Benjamin Wagner
- School of Ecosystem and Forest Sciences The University of Melbourne Richmond Victoria Australia
| | - Patrick J. Baker
- School of Ecosystem and Forest Sciences The University of Melbourne Richmond Victoria Australia
| | - Craig R. Nitschke
- School of Ecosystem and Forest Sciences The University of Melbourne Richmond Victoria Australia
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18
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Anvari F, Marchiori D. Priming exploration across domains: does search in a spatial environment influence search in a cognitive environment? ROYAL SOCIETY OPEN SCIENCE 2021; 8:201944. [PMID: 34457320 PMCID: PMC8371357 DOI: 10.1098/rsos.201944] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 07/31/2021] [Indexed: 06/13/2023]
Abstract
Is there a general tendency to explore that connects search behaviour across different domains? Although the experimental evidence collected so far suggests an affirmative answer, this fundamental question about human behaviour remains open. A feasible way to test the domain-generality hypothesis is that of testing the so-called priming hypothesis: priming explorative behaviour in one domain should subsequently influence explorative behaviour in another domain. However, only a limited number of studies have experimentally tested this priming hypothesis, and the evidence is mixed. We tested the priming hypothesis in a registered report. We manipulated explorative behaviour in a spatial search task by randomly allocating people to search environments with resources that were either clustered together or dispersedly distributed. We hypothesized that, in a subsequent anagram task, participants who searched in clustered spatial environments would search for words in a more clustered way than participants who searched in the dispersed spatial environments. The pre-registered hypothesis was not supported. An equivalence test showed that the difference between conditions was smaller than the smallest effect size of interest (d = 0.36). Out of several exploratory analyses, we found only one inferential result in favour of priming. We discuss implications of these findings for the theory and propose future tests of the hypothesis.
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Affiliation(s)
- Farid Anvari
- Strategic Organization Design Group, Department of Marketing and Management, University of Southern Denmark, Odense 5230, Denmark
| | - Davide Marchiori
- Strategic Organization Design Group, Department of Marketing and Management, University of Southern Denmark, Odense 5230, Denmark
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19
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Kürschner T, Scherer C, Radchuk V, Blaum N, Kramer‐Schadt S. Movement can mediate temporal mismatches between resource availability and biological events in host-pathogen interactions. Ecol Evol 2021; 11:5728-5741. [PMID: 34026043 PMCID: PMC8131764 DOI: 10.1002/ece3.7478] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Revised: 02/23/2021] [Accepted: 03/09/2021] [Indexed: 12/28/2022] Open
Abstract
Global change is shifting the timing of biological events, leading to temporal mismatches between biological events and resource availability. These temporal mismatches can threaten species' populations. Importantly, temporal mismatches not only exert strong pressures on the population dynamics of the focal species, but can also lead to substantial changes in pairwise species interactions such as host-pathogen systems. We adapted an established individual-based model of host-pathogen dynamics. The model describes a viral agent in a social host, while accounting for the host's explicit movement decisions. We aimed to investigate how temporal mismatches between seasonal resource availability and host life-history events affect host-pathogen coexistence, that is, disease persistence. Seasonal resource fluctuations only increased coexistence probability when in synchrony with the hosts' biological events. However, a temporal mismatch reduced host-pathogen coexistence, but only marginally. In tandem with an increasing temporal mismatch, our model showed a shift in the spatial distribution of infected hosts. It shifted from an even distribution under synchronous conditions toward the formation of disease hotspots, when host life history and resource availability mismatched completely. The spatial restriction of infected hosts to small hotspots in the landscape initially suggested a lower coexistence probability due to the critical loss of susceptible host individuals within those hotspots. However, the surrounding landscape facilitated demographic rescue through habitat-dependent movement. Our work demonstrates that the negative effects of temporal mismatches between host resource availability and host life history on host-pathogen coexistence can be reduced through the formation of temporary disease hotspots and host movement decisions, with implications for disease management under disturbances and global change.
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Affiliation(s)
- Tobias Kürschner
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
| | - Cédric Scherer
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
| | - Viktoriia Radchuk
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
| | - Niels Blaum
- Plant Ecology and Nature ConservationUniversity of PotsdamPotsdamGermany
| | - Stephanie Kramer‐Schadt
- Department of Ecological DynamicsLeibniz Institute for Zoo and Wildlife ResearchBerlinGermany
- Department of EcologyTechnische Universität BerlinBerlinGermany
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20
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Vickers SH, Franco AMA, Gilroy JJ. Sensitivity of migratory connectivity estimates to spatial sampling design. MOVEMENT ECOLOGY 2021; 9:16. [PMID: 33810815 PMCID: PMC8019184 DOI: 10.1186/s40462-021-00254-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 03/16/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND The use of statistical methods to quantify the strength of migratory connectivity is commonplace. However, little attention has been given to their sensitivity to spatial sampling designs and scales of inference. METHODS We examine sources of bias and imprecision in the most widely used methodology, Mantel correlations, under a range of plausible sampling regimes using simulated migratory populations. RESULTS As Mantel correlations depend fundamentally on the spatial scale and configuration of sampling, unbiased inferences about population-scale connectivity can only be made under certain sampling regimes. Within a contiguous population, samples drawn from smaller spatial subsets of the range generate lower connectivity metrics than samples drawn from the range as a whole, even when the underlying migratory ecology of the population is constant across the population. Random sampling of individuals from contiguous subsets of species ranges can therefore underestimate population-scale connectivity. Where multiple discrete sampling sites are used, by contrast, overestimation of connectivity can arise due to samples being biased towards larger between-individual pairwise distances in the seasonal range where sampling occurs (typically breeding). Severity of all biases was greater for populations with lower levels of true connectivity. When plausible sampling regimes were applied to realistic simulated populations, accuracy of connectivity measures was maximised by increasing the number of discrete sampling sites and ensuring an even spread of sites across the full range. CONCLUSIONS These results suggest strong potential for bias and imprecision when making quantitative inferences about migratory connectivity using Mantel statistics. Researchers wishing to apply these methods should limit inference to the spatial extent of their sampling, maximise their number of sampling sites, and avoid drawing strong conclusions based on small sample sizes.
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Affiliation(s)
- Stephen H Vickers
- School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.
| | - Aldina M A Franco
- School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
| | - James J Gilroy
- School of Environmental Sciences, University of East Anglia, Norwich, NR4 7TJ, UK
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21
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Dupont G, Royle JA, Nawaz MA, Sutherland C. Optimal sampling design for spatial capture-recapture. Ecology 2021; 102:e03262. [PMID: 33244753 DOI: 10.1002/ecy.3262] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Revised: 09/10/2020] [Accepted: 10/09/2020] [Indexed: 11/06/2022]
Abstract
Spatial capture-recapture (SCR) has emerged as the industry standard for estimating population density by leveraging information from spatial locations of repeat encounters of individuals. The precision of density estimates depends fundamentally on the number and spatial configuration of traps. Despite this knowledge, existing sampling design recommendations are heuristic and their performance remains untested for most practical applications. To address this issue, we propose a genetic algorithm that minimizes any sensible, criteria-based objective function to produce near-optimal sampling designs. To motivate the idea of optimality, we compare the performance of designs optimized using three model-based criteria related to the probability of capture. We use simulation to show that these designs outperform those based on existing recommendations in terms of bias, precision, and accuracy in the estimation of population size. Our approach, available as a function in the R package oSCR, allows conservation practitioners and researchers to generate customized and improved sampling designs for wildlife monitoring.
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Affiliation(s)
- Gates Dupont
- Department of Environmental Conservation, University of Massachusetts, 160 Holdsworth Way, Amherst, Massachusetts, 01003, USA.,Organismic and Evolutionary Biology Graduate Program, University of Massachusetts, 204C French Hall, 230 Stockbridge Road, Amherst, Massachusetts, USA
| | - J Andrew Royle
- U.S. Geological Survey, Patuxent Wildlife Research Center, Laurel, Maryland, 20708, USA
| | - Muhammad Ali Nawaz
- Department of Animal Sciences, Quaid-i-Azam University, Islamabad, 44000, Pakistan.,Snow Leopard Trust, 4649 Sunnyside Avenue North, Suite 325, Seattle, Washington, 98103, USA.,Department of Biological and Environmental Sciences, College of Arts and Sciences, University of Qatar, Doha, Qatar
| | - Chris Sutherland
- Department of Environmental Conservation, University of Massachusetts, 160 Holdsworth Way, Amherst, Massachusetts, 01003, USA.,Centre for Research into Ecological and Environmental Modelling, University of St Andrews, Fife, KY16 9LZ, St. Andrews, UK
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22
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Savary P, Foltête JC, Moal H, Vuidel G, Garnier S. Analysing landscape effects on dispersal networks and gene flow with genetic graphs. Mol Ecol Resour 2021; 21:1167-1185. [PMID: 33460526 DOI: 10.1111/1755-0998.13333] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 01/08/2021] [Accepted: 01/12/2021] [Indexed: 12/16/2022]
Abstract
Graph-theoretic approaches have relevant applications in landscape genetic analyses. When species form populations in discrete habitat patches, genetic graphs can be used (a) to identify direct dispersal paths followed by propagules or (b) to quantify landscape effects on multi-generational gene flow. However, the influence of their construction parameters remains to be explored. Using a simulation approach, we constructed genetic graphs using several pruning methods (geographical distance thresholds, topological constraints, statistical inference) and genetic distances to weight graph links (FST , DPS , Euclidean genetic distances). We then compared the capacity of these different graphs to (a) identify the precise topology of the dispersal network and (b) to infer landscape resistance to gene flow from the relationship between cost-distances and genetic distances. Although not always clear-cut, our results showed that methods based on geographical distance thresholds seem to better identify dispersal networks in most cases. More interestingly, our study demonstrates that a sub-selection of pairwise distances through graph pruning (thereby reducing the number of data points) can counter-intuitively lead to improved inferences of landscape effects on dispersal. Finally, we showed that genetic distances such as the DPS or Euclidean genetic distances should be preferred over the FST for landscape effect inference as they respond faster to landscape changes.
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Affiliation(s)
- Paul Savary
- ARP-Astrance, 9 Avenue Percier, Paris, 75008, France.,ThéMA, UMR 6049 CNRS, Université Bourgogne-Franche-Comté, 32 Rue Mégevand, Besançon Cedex, 25030, France.,Biogéosciences, UMR 6282 CNRS, Université Bourgogne-Franche-Comté, 6 Boulevard Gabriel, Dijon, 21000, France
| | - Jean-Christophe Foltête
- ThéMA, UMR 6049 CNRS, Université Bourgogne-Franche-Comté, 32 Rue Mégevand, Besançon Cedex, 25030, France
| | - Hervé Moal
- ARP-Astrance, 9 Avenue Percier, Paris, 75008, France
| | - Gilles Vuidel
- ThéMA, UMR 6049 CNRS, Université Bourgogne-Franche-Comté, 32 Rue Mégevand, Besançon Cedex, 25030, France
| | - Stéphane Garnier
- Biogéosciences, UMR 6282 CNRS, Université Bourgogne-Franche-Comté, 6 Boulevard Gabriel, Dijon, 21000, France
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23
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Thermal Summer Diurnal Hot-Spot Analysis: The Role of Local Urban Features Layers. REMOTE SENSING 2021. [DOI: 10.3390/rs13030538] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
This study was focused on the metropolitan area of Florence in Tuscany (Italy) with the aim of mapping and evaluating thermal summer diurnal hot- and cool-spots in relation to the features of greening, urban surfaces, and city morphology. The work was driven by Landsat 8 land surface temperature (LST) data related to 2015–2019 summer daytime periods. Hot-spot analysis was performed adopting Getis-Ord Gi* spatial statistics applied on mean summer LST datasets to obtain location and boundaries of hot- and cool-spot areas. Each hot- and cool-spot was classified by using three significance threshold levels: 90% (LEVEL-1), 95% (LEVEL-2), and 99% (LEVEL-3). A set of open data urban elements directly or indirectly related to LST at local scale were calculated for each hot- and cool-spot area: (1) Normalized Difference Vegetation Index (NDVI), (2) tree cover (TC), (3) water bodies (WB), (4) impervious areas (IA), (5) mean spatial albedo (ALB), (6) surface areas (SA), (7) Shape index (SI), (8) Sky View Factor (SVF), (9) theoretical solar radiation (RJ), and (10) mean population density (PD). A General Dominance Analysis (GDA) framework was adopted to investigate the relative importance of urban factors affecting thermal hot- and cool-spot areas. The results showed that 11.5% of the studied area is affected by cool-spots and 6.5% by hot-spots. The average LST variation between hot- and cold-spot areas was about 10 °C and it was 15 °C among the extreme hot- and cool-spot levels (LEVEL-3). Hot-spot detection was magnified by the role of vegetation (NDVI and TC) combined with the significant contribution of other urban elements. In particular, TC, NDVI and ALB were identified as the most significant predictors (p-values < 0.001) of the most extreme cool-spot level (LEVEL-3). NDVI, PD, ALB, and SVF were selected as the most significant predictors (p-values < 0.05 for PD and SVF; p-values < 0.001 for NDVI and ALB) of the hot-spot LEVEL-3. In this study, a reproducible methodology was developed applicable to any urban context by using available open data sources.
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24
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Gilbert NA, Clare JDJ, Stenglein JL, Zuckerberg B. Abundance estimation of unmarked animals based on camera-trap data. CONSERVATION BIOLOGY : THE JOURNAL OF THE SOCIETY FOR CONSERVATION BIOLOGY 2021; 35:88-100. [PMID: 32297655 DOI: 10.1111/cobi.13517] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 04/02/2020] [Accepted: 04/10/2020] [Indexed: 06/11/2023]
Abstract
The rapid improvement of camera traps in recent decades has revolutionized biodiversity monitoring. Despite clear applications in conservation science, camera traps have seldom been used to model the abundance of unmarked animal populations. We sought to summarize the challenges facing abundance estimation of unmarked animals, compile an overview of existing analytical frameworks, and provide guidance for practitioners seeking a suitable method. When a camera records multiple detections of an unmarked animal, one cannot determine whether the images represent multiple mobile individuals or a single individual repeatedly entering the camera viewshed. Furthermore, animal movement obfuscates a clear definition of the sampling area and, as a result, the area to which an abundance estimate corresponds. Recognizing these challenges, we identified 6 analytical approaches and reviewed 927 camera-trap studies published from 2014 to 2019 to assess the use and prevalence of each method. Only about 5% of the studies used any of the abundance-estimation methods we identified. Most of these studies estimated local abundance or covariate relationships rather than predicting abundance or density over broader areas. Next, for each analytical approach, we compiled the data requirements, assumptions, advantages, and disadvantages to help practitioners navigate the landscape of abundance estimation methods. When seeking an appropriate method, practitioners should evaluate the life history of the focal taxa, carefully define the area of the sampling frame, and consider what types of data collection are possible. The challenge of estimating abundance of unmarked animal populations persists; although multiple methods exist, no one method is optimal for camera-trap data under all circumstances. As analytical frameworks continue to evolve and abundance estimation of unmarked animals becomes increasingly common, camera traps will become even more important for informing conservation decision-making.
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Affiliation(s)
- Neil A Gilbert
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, U.S.A
| | - John D J Clare
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, U.S.A
| | - Jennifer L Stenglein
- Wisconsin Department of Natural Resources, 2901 Progress Drive, Madison, WI, 53716, U.S.A
| | - Benjamin Zuckerberg
- Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, U.S.A
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25
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Peterman WE, Pope NS. The use and misuse of regression models in landscape genetic analyses. Mol Ecol 2020; 30:37-47. [PMID: 33128830 DOI: 10.1111/mec.15716] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2020] [Revised: 08/21/2020] [Accepted: 10/22/2020] [Indexed: 12/27/2022]
Abstract
The field of landscape genetics has been rapidly evolving, adopting and adapting analytical frameworks to address research questions. Current studies are increasingly using regression-based frameworks to infer the individual contributions of landscape and habitat variables on genetic differentiation. This paper outlines appropriate and inappropriate uses of multiple regression for these purposes, and demonstrates through simulation the limitations of different analytical frameworks for making correct inference. Of particular concern are recent studies seeking to explain genetic differences by fitting regression models with effective distance variables calculated independently on separate landscape resistance surfaces. When moving across the landscape, organisms cannot respond independently and uniquely to habitat and landscape features. Analyses seeking to understand how landscape features affect gene flow should model a single conductance or resistance surface as a parameterized function of relevant spatial covariates, and estimate the values of these parameters by linking a single set of resistance distances to observed genetic dissimilarity via a loss function. While this loss function may involve a regression-like step, the associated nuisance parameters are not interpretable in terms of organismal movement and should not be conflated with what is actually of interest: the mapping between spatial covariates and conductance/resistance. The growth and evolution of landscape genetics as a field has been rapid and exciting. It is the goal of this paper to highlight past missteps and demonstrate limitations of current approaches to ensure that future use of regression models will appropriately consider the process being modeled, which will provide clarity to model interpretation.
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Affiliation(s)
- William E Peterman
- School of Environment and Natural Resources, The Ohio State University, Columbus, OH, USA
| | - Nathaniel S Pope
- Department of Entomology, The Pennsylvania State University, University Park, PA, USA
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26
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Affiliation(s)
- Matthias Fritsch
- Ecosystem Modelling Faculty of Forest Sciences and Forest Ecology University of Göttingen Göttingen Germany
| | - Heike Lischke
- Dynamic Macroecology Land Change ScienceSwiss Federal Institute for Forest, Snow and Landscape Research WSL Birmensdorf Switzerland
| | - Katrin M. Meyer
- Ecosystem Modelling Faculty of Forest Sciences and Forest Ecology University of Göttingen Göttingen Germany
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27
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Scherer C, Radchuk V, Franz M, Thulke H, Lange M, Grimm V, Kramer‐Schadt S. Moving infections: individual movement decisions drive disease persistence in spatially structured landscapes. OIKOS 2020. [DOI: 10.1111/oik.07002] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- Cédric Scherer
- Leibniz Inst. for Zoo and Wildlife Research (IZW) Alfred‐Kowalke‐Str. 17 DE‐10315 Berlin Germany
| | - Viktoriia Radchuk
- Leibniz Inst. for Zoo and Wildlife Research (IZW) Alfred‐Kowalke‐Str. 17 DE‐10315 Berlin Germany
| | - Mathias Franz
- Leibniz Inst. for Zoo and Wildlife Research (IZW) Alfred‐Kowalke‐Str. 17 DE‐10315 Berlin Germany
| | | | - Martin Lange
- Helmholtz Centre for Environmental Research–UFZ Leipzig Germany
| | - Volker Grimm
- Helmholtz Centre for Environmental Research–UFZ Leipzig Germany
| | - Stephanie Kramer‐Schadt
- Leibniz Inst. for Zoo and Wildlife Research (IZW) Alfred‐Kowalke‐Str. 17 DE‐10315 Berlin Germany
- Dept of Ecology, Technische Univ. Berlin Berlin Germany
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28
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Silva I, Crane M, Marshall BM, Strine CT. Reptiles on the wrong track? Moving beyond traditional estimators with dynamic Brownian Bridge Movement Models. MOVEMENT ECOLOGY 2020; 8:43. [PMID: 33133609 PMCID: PMC7592577 DOI: 10.1186/s40462-020-00229-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Accepted: 10/12/2020] [Indexed: 05/23/2023]
Abstract
BACKGROUND Animal movement expressed through home ranges or space-use can offer insights into spatial and habitat requirements. However, different classes of estimation methods are currently instinctively applied to answer home range, space-use or movement-based research questions regardless of their widely varying outputs, directly impacting conclusions. Recent technological advances in animal tracking (GPS and satellite tags), have enabled new methods to quantify animal space-use and movement pathways, but so far have primarily targeted mammal and avian species. METHODS Most reptile spatial ecology studies only make use of two older home range estimation methods: Minimum Convex Polygons (MCP) and Kernel Density Estimators (KDE), particularly with the Least Squares Cross Validation (LSCV) and reference (h ref ) bandwidth selection algorithms. These methods are frequently applied to answer space-use and movement-based questions. Reptile movement patterns are unique (e.g., low movement frequency, long stop-over periods), prompting investigation into whether newer movement-based methods -such as dynamic Brownian Bridge Movement Models (dBBMMs)- apply to Very High Frequency (VHF) radio-telemetry tracking data. We simulated movement data for three archetypical reptile species: a highly mobile active hunter, an ambush predator with long-distance moves and long-term sheltering periods, and an ambush predator with short-distance moves and short-term sheltering periods. We compared traditionally used estimators, MCP and KDE, with dBBMMs, across eight feasible VHF field sampling regimes for reptiles, varying from one data point every four daylight hours, to once per month. RESULTS Although originally designed for GPS tracking studies, dBBMMs outperformed MCPs and KDE h ref across all tracking regimes in accurately revealing movement pathways, with only KDE LSCV performing comparably at some higher frequency sampling regimes. However, the LSCV algorithm failed to converge with these high-frequency regimes due to high site fidelity, and was unstable across sampling regimes, making its use problematic for species exhibiting long-term sheltering behaviours. We found that dBBMMs minimized the effect of individual variation, maintained low error rates balanced between omission (false negative) and commission (false positive), and performed comparatively well even under low frequency sampling regimes (e.g., once a month). CONCLUSIONS We recommend dBBMMs as a valuable alternative to MCP and KDE methods for reptile VHF telemetry data, for research questions associated with space-use and movement behaviours within the study period: they work under contemporary tracking protocols and provide more stable estimates. We demonstrate for the first time that dBBMMs can be applied confidently to low-resolution tracking data, while improving comparisons across regimes, individuals, and species. SUPPLEMENTARY INFORMATION Supplementary information accompanies this paper at 10.1186/s40462-020-00229-3.
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Affiliation(s)
- Inês Silva
- Conservation Ecology Program, School of Bioresources and Technology, King Mongkut’s University of Technology Thonburi, Bangkhunthien, Bangkok, Thailand
| | - Matt Crane
- Conservation Ecology Program, School of Bioresources and Technology, King Mongkut’s University of Technology Thonburi, Bangkhunthien, Bangkok, Thailand
| | - Benjamin Michael Marshall
- School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, Thailand
| | - Colin Thomas Strine
- School of Biology, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, Thailand
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29
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Betts MG, Wolf C, Pfeifer M, Banks-Leite C, Arroyo-Rodríguez V, Ribeiro DB, Barlow J, Eigenbrod F, Faria D, Fletcher RJ, Hadley AS, Hawes JE, Holt RD, Klingbeil B, Kormann U, Lens L, Levi T, Medina-Rangel GF, Melles SL, Mezger D, Morante-Filho JC, Orme CDL, Peres CA, Phalan BT, Pidgeon A, Possingham H, Ripple WJ, Slade EM, Somarriba E, Tobias JA, Tylianakis JM, Urbina-Cardona JN, Valente JJ, Watling JI, Wells K, Wearn OR, Wood E, Young R, Ewers RM. Extinction filters mediate the global effects of habitat fragmentation on animals. Science 2019; 366:1236-1239. [DOI: 10.1126/science.aax9387] [Citation(s) in RCA: 98] [Impact Index Per Article: 19.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Accepted: 10/23/2019] [Indexed: 12/16/2022]
Abstract
Habitat loss is the primary driver of biodiversity decline worldwide, but the effects of fragmentation (the spatial arrangement of remaining habitat) are debated. We tested the hypothesis that forest fragmentation sensitivity—affected by avoidance of habitat edges—should be driven by historical exposure to, and therefore species’ evolutionary responses to disturbance. Using a database containing 73 datasets collected worldwide (encompassing 4489 animal species), we found that the proportion of fragmentation-sensitive species was nearly three times as high in regions with low rates of historical disturbance compared with regions with high rates of disturbance (i.e., fires, glaciation, hurricanes, and deforestation). These disturbances coincide with a latitudinal gradient in which sensitivity increases sixfold at low versus high latitudes. We conclude that conservation efforts to limit edges created by fragmentation will be most important in the world’s tropical forests.
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Affiliation(s)
- Matthew G. Betts
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
| | - Christopher Wolf
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
| | - Marion Pfeifer
- School of Natural and Environmental Sciences, Newcastle University, Newcastle Upon Tyne NE1 7RU, UK
| | | | - Víctor Arroyo-Rodríguez
- Instituto de Investigaciones en Ecosistemas y Sustentabilidad, Universidad Nacional Autónoma de México (UNAM), Campus Morelia, Antigua Carretera Patzcuaro no. 8701, Ex-Hacienda de San José de la Huerta, 58190 Morelia, Michoacán, Mexico
| | - Danilo Bandini Ribeiro
- Instituo de Biociências, Universidade Federal de Mato Grosso do Sul, Caixa Postal 549, 79070-900 Campo Grande, Brazil
| | - Jos Barlow
- Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
- Setor Ecologia, Departamento de Biologia, Universidade Federal de Lavras, 37200-000, Lavras, MG, Brazil
| | - Felix Eigenbrod
- Geography and Environmental Sciences, University of Southampton, Southampton SO17 1BJ, UK
| | - Deborah Faria
- Applied Conservation Ecology Lab, Programa de Pós-graduação em Ecologia e Conservação, da Biodiversidade, Universidade Estadual de Santa Cruz, Rodovia Ilhéus-Itabuna, km 16, Salobrinho, 45662-000 Ilhéus, Bahia, Brazil
| | - Robert J. Fletcher
- Department of Wildlife Ecology and Conservation, University of Florida, Gainesville, FL 32611, USA
| | - Adam S. Hadley
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
| | - Joseph E. Hawes
- Applied Ecology Research Group, School of Life Sciences, Anglia Ruskin University, Cambridge CB1 1PT, UK
| | - Robert D. Holt
- Department of Biology, University of Florida, Gainesville, FL 32611, USA
| | - Brian Klingbeil
- School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849, USA
| | - Urs Kormann
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
- Swiss Ornithological Institute, Sempach, Switzerland
- Division of Forest Sciences, School of Agricultural, Forest and Food Sciences HAFL, Bern University of Applied Sciences, Zollikofen, Switzerland
| | - Luc Lens
- Ghent University, Department of Biology, K.L. Ledeganckstraat 35, B-9000 Gent, Belgium
| | - Taal Levi
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
| | - Guido F. Medina-Rangel
- Groupo de Biodiversidad y Conservación, Reptiles, Instituto de Ciencias Naturales, Universidad Nacional de Colombia, Ciudad Universitaria, Edificio 425, Bogotá, Distrito Capital, Colombia
| | - Stephanie L. Melles
- Department of Chemistry and Biology, Ryerson University, 350 Victoria Street, Toronto, ON M5B 2K3, Canada
| | - Dirk Mezger
- Department of Science and Education, Field Museum of Natural History, Chicago, IL 60605, USA
| | - José Carlos Morante-Filho
- Applied Conservation Ecology Lab, Programa de Pós-graduação em Ecologia e Conservação, da Biodiversidade, Universidade Estadual de Santa Cruz, Rodovia Ilhéus-Itabuna, km 16, Salobrinho, 45662-000 Ilhéus, Bahia, Brazil
- Departamento de Ciências Biológicas, Universidade Estadual de Feira de Santana, Avenida Transnordestina, s/n - Novo Horizonte, 44036-900 Feira de Santana, Bahia, Brazil
| | - C. David L. Orme
- Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK
| | - Carlos A. Peres
- Centre for Ecology, Evolution and Conservation, School of Environmental Sciences, University of East Anglia, Norwich NR4 7TJ, UK
| | - Benjamin T. Phalan
- Instituto de Biologia, Universidade Federal da Bahia, Salvador, 40170-115 Bahia, Brazil
| | - Anna Pidgeon
- Department of Forest and Wildlife Ecology, University of Wisconsin–Madison, 1630 Linden Drive, Madison, WI 53706, USA
| | - Hugh Possingham
- School of Biological Sciences, University of Queensland, St Lucia, Queensland, Australia
- The Nature Conservancy, Arlington, VA 22203, USA
| | - William J. Ripple
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
| | - Eleanor M. Slade
- Asian School of the Environment, Nanyang Technological University, 62 Nanyang Dr., 637459 Singapore
| | - Eduardo Somarriba
- Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, Costa Rica
| | - Joseph A. Tobias
- Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK
| | - Jason M. Tylianakis
- School of Biological Sciences, University of Canterbury, Private bag 4800, Christchurch 8140, New Zealand
| | - J. Nicolás Urbina-Cardona
- Department of Ecology and Territory, School of Rural and Environmental Studies, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Jonathon J. Valente
- Forest Biodiversity Research Network, Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA
- Smithsonian Conservation Biology Institute, Migratory Bird Center, National Zoological Park, Washington, DC 20013, USA
| | - James I. Watling
- Department of Biology, John Carroll University, University Heights, OH 44118, USA
| | - Konstans Wells
- Department of Biosciences, Swansea University, Swansea SA2 8PP, Wales, UK
| | - Oliver R. Wearn
- Institute of Zoology, Zoological Society of London, Regent’s Park, London NW1 4RY, UK
| | - Eric Wood
- Department of Biological Sciences, California State University Los Angeles, 5151 State University Drive, Los Angeles, CA 90032, USA
| | - Richard Young
- Durrell Wildlife Conservation Trust, Les Augres Manor, Trinity, Jersey JE3 5BP, UK
| | - Robert M. Ewers
- Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK
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Lourenço A, Gonçalves J, Carvalho F, Wang IJ, Velo‐Antón G. Comparative landscape genetics reveals the evolution of viviparity reduces genetic connectivity in fire salamanders. Mol Ecol 2019; 28:4573-4591. [DOI: 10.1111/mec.15249] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2019] [Revised: 08/22/2019] [Accepted: 09/16/2019] [Indexed: 01/07/2023]
Affiliation(s)
- André Lourenço
- Departamento de Biologia Faculdade de Ciências Universidade do Porto Porto Portugal
- CIBIO/InBIO Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto Instituto de Ciências Agrárias de Vairão Vairão Portugal
| | - João Gonçalves
- CIBIO/InBIO Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto Instituto de Ciências Agrárias de Vairão Vairão Portugal
| | - Filipe Carvalho
- CIBIO/InBIO Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto Instituto de Ciências Agrárias de Vairão Vairão Portugal
- Department of Zoology and Entomology School of Biological and Environmental Sciences University of Fort Hare Alice South Africa
| | - Ian J. Wang
- Department of Environmental Science, Policy, and Management University of California Berkeley CA USA
| | - Guillermo Velo‐Antón
- CIBIO/InBIO Centro de Investigação em Biodiversidade e Recursos Genéticos da Universidade do Porto Instituto de Ciências Agrárias de Vairão Vairão Portugal
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Langhammer M, Thober J, Lange M, Frank K, Grimm V. Agricultural landscape generators for simulation models: A review of existing solutions and an outline of future directions. Ecol Modell 2019. [DOI: 10.1016/j.ecolmodel.2018.12.010] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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