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Latest recommendations
Id | Title * ▲ | Authors * | Abstract * | Picture * | Thematic fields * | Recommender | Reviewers | Submission date | |
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06 May 2022
![]() Effects of climate warming on the pine processionary moth at the southern edge of its range: a retrospective analysis on egg survival in TunisiaAsma Bourougaaoui, Christelle Robinet, Mohamed Lahbib Ben Jamâa, Mathieu Laparie https://doi.org/10.1101/2021.08.17.456665Even the current climate change winners could end up being losersRecommended by Elodie Vercken based on reviews by Matt Hill, Philippe Louapre, José Hodar and Corentin IltisClimate change is accelerating (IPCC 2022), and so applies ever stronger selective pressures on biodiversity (Segan et al. 2016). Possible responses include range shifts or adaptations to new climatic conditions (Bellard et al. 2012), but there is still much uncertainty about the extent of most species' adaptive capacities and the impact of extreme climatic events. Battisti A, Stastny M, Netherer S, Robinet C, Schopf A, Roques A, Larsson S (2005) Expansion of Geographic Range in the Pine Processionary Moth Caused by Increased Winter Temperatures. Ecological Applications, 15, 2084–2096. https://doi.org/10.1890/04-1903 Bellard C, Bertelsmeier C, Leadley P, Thuiller W, Courchamp F (2012) Impacts of climate change on the future of biodiversity. Ecology Letters, 15, 365–377. https://doi.org/10.1111/j.1461-0248.2011.01736.x Bourougaaoui A, Ben Jamâa ML, Robinet C (2021) Has North Africa turned too warm for a Mediterranean forest pest because of climate change? Climatic Change, 165, 46. https://doi.org/10.1007/s10584-021-03077-1 Bourougaaoui A, Robinet C, Jamaa MLB, Laparie M (2022) Effects of climate warming on the pine processionary moth at the southern edge of its range: a retrospective analysis on egg survival in Tunisia. bioRxiv, 2021.08.17.456665, ver. 5 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2021.08.17.456665 IPCC. 2022. Climate Change 2022: Impacts, Adaptation, and Vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [H.-O. Pörtner, D.C. Roberts, M. Tignor, E.S. Poloczanska, K. Mintenbeck, A. Alegría, M. Craig, S. Langsdorf, S. Löschke, V. Möller, A. Okem, B. Rama (eds.)]. Cambridge University Press. In Press. Segan DB, Murray KA, Watson JEM (2016) A global assessment of current and future biodiversity vulnerability to habitat loss–climate change interactions. Global Ecology and Conservation, 5, 12–21. https://doi.org/10.1016/j.gecco.2015.11.002 Verner D (2013) Tunisia in a Changing Climate : Assessment and Actions for Increased Resilience and Development. World Bank, Washington, DC. https://doi.org/10.1596/978-0-8213-9857-9 | Effects of climate warming on the pine processionary moth at the southern edge of its range: a retrospective analysis on egg survival in Tunisia | Asma Bourougaaoui, Christelle Robinet, Mohamed Lahbib Ben Jamâa, Mathieu Laparie | <p style="text-align: justify;">In recent years, ectotherm species have largely been impacted by extreme climate events, essentially heatwaves. In Tunisia, the pine processionary moth (PPM), <em>Thaumetopoea pityocampa</em>, is a highly damaging p... | ![]() | Climate change, Dispersal & Migration, Life history, Phenotypic plasticity, Species distributions, Terrestrial ecology, Thermal ecology, Zoology | Elodie Vercken | 2021-08-19 11:03:13 | View | |
24 May 2024
![]() Effects of water nutrient concentrations on stream macroinvertebrate community stoichiometry: a large-scale studyMiriam Beck, Elise Billoir, Philippe Usseglio-Polatera, Albin Meyer, Edwige Gautreau, Michael Danger https://doi.org/10.1101/2024.02.01.574823The influence of water phosphorus and nitrogen loads on stream macroinvertebrate community stoichiometryRecommended by Huihuang ChenThe manuscript by Beck et al. (2024) investigates the effects of water phosphorus and nitrogen loads on stream macroinvertebrate community stoichiometry across France. Utilizing data from over 1300 standardized sampling events, this research finds that community stoichiometry is significantly influenced by water phosphorus concentration, with the strongest effects at low nitrogen levels. The results demonstrate that the assumptions of Ecological Stoichiometry Theory apply at the community level for at least two dominant taxa and across a broad spatial scale, with probable implications for nutrient cycling and ecosystem functionality. This manuscript contributes to ecological theory, particularly by extending Ecological Stoichiometry Theory to include community-level interactions, clarifying the impact of nutrient concentrations on community structure and function, and informing nutrient management and conservation strategies. In summary, this study not only addresses a gap in community-level stoichiometric research but also delivers crucial empirical support for advancing ecological science and promoting environmental stewardship. References Beck M, Billoir E, Usseglio-Polatera P, Meyer A, Gautreau E and Danger M (2024) Effects of water nutrient concentrations on stream macroinvertebrate community stoichiometry: a large-scale study. bioRxiv, 2024.02.01.574823, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2024.02.01.574823 | Effects of water nutrient concentrations on stream macroinvertebrate community stoichiometry: a large-scale study | Miriam Beck, Elise Billoir, Philippe Usseglio-Polatera, Albin Meyer, Edwige Gautreau, Michael Danger | <p>Basal resources generally mirror environmental nutrient concentrations in the elemental composition of their tissue, meaning that nutrient alterations can directly reach consumer level. An increased nutrient content (e.g. phosphorus) in primary... | ![]() | Community ecology, Ecological stoichiometry | Huihuang Chen | Thomas Guillemaud, Jun Zuo, Anonymous | 2024-02-02 10:14:01 | View |
03 Jan 2024
![]() Efficient sampling designs to assess biodiversity spatial autocorrelation : should we go fractal?Fabien Laroche https://doi.org/10.1101/2022.07.29.501974Spatial patterns and autocorrelation challenges in ecological conservationRecommended by Eric Goberville“Pattern, like beauty, is to some extent in the eye of the beholder” (Grant 1977 in Wiens, 1989) Ecologists are immersed in unraveling the complex spatial patterns that govern species diversity, driven by both practical and theoretical imperatives (Rahbek, 2005; Wang et al., 2019). This dual focus necessitates a practical imperative for strategic biodiversity conservation, requiring a nuanced understanding of locations with peak species richness and dynamic shifts in species assemblages (Chase et al., 2020). Simultaneously, there is a theoretical interest in using diversity patterns as empirical testing grounds for theories explaining factors influencing diversity disparities and the associated increase in species turnover correlated with inter-site distance (Condit et al., 2002).
McGill (2010), in his paper "Matters of Scale", highlights the scale-dependent nature of ecology, aligning with the recognition that spatial autocorrelation is inherent in biogeographical data and often correlated with sample size (Rahbek, 2005). Spatial autocorrelation, often underestimated in ecological studies (Dormann, 2007), occurs when proximate locations exhibit similarities in ecological attributes (Tobler, 1970; Getis, 2010), introducing a latent bias that compromises the robustness of ecological findings (Dormann, 2007; Dormann et al., 2007). This phenomenon serves as both an asset, providing valuable information for inferring processes from patterns (Palma et al. 1999), and a challenge, imposing limitations on hypothesis testing and prediction (Dormann et al., 2007 and references therein). Various factors contribute to spatial autocorrelation, with three primary contributors (Dormann et al., 2007; Legendre, 1993; Legendre and Fortin, 1989; Legendre and Legendre, 2012): (i) distance-related effects in biological processes, (ii) misrepresentation of non-linear relationships between the environment and species as linear and (iii) the oversight of a crucial spatially structured environmental determinant in the statistical model, leading to spatial structuring in the response (Dormann et al., 2007).
Recognising the pivotal role of spatial heterogeneity in ecological theories (Wang et al., 2019), it becomes imperative to discern and address the limitations introduced by spatial autocorrelation (Legendre, 1993). McGill (2011) emphasises that the ultimate goal of biodiversity pattern studies should be to develop a quantitative predictive theory useful for conservation. The spatial dimension's importance in study planning, determining the system's scale, appropriate quadrat size, and spacing between sampling stations, is paramount (Fortin, 1999a,b). Responses to these considerations are intricately linked with study objectives and insights from pre-sampling campaigns, underscoring the need for a nuanced and rigorous approach (Delmelle, 2021).
Understanding statistical techniques and nested sampling designs is crucial to answering fundamental ecological questions (Dormann et al., 2007; McDonald, 2012). In addressing spatial autocorrelation challenges, ecologists must recognize the limitations of many standard statistical methods in ecological studies (Dale and Fortin, 2002; Legendre and Fortin, 1989; Steel et al., 2013). In the initial phases of description or hypothesis generation, ecologists should proactively acknowledge the spatial structure in their data and conduct tests for spatial autocorrelation (for a comprehensive description, see Legendre and Fortin, 1989): various tools, including correlograms, spectral analysis, the Mantel test, and clustering methods, facilitate the assessment and description of spatial structures. The partial Mantel test enables the study of causal models with space as an explanatory variable. Techniques for mapping ecological variables, such as interpolation, trend surface analysis, and constrained clustering, yield maps providing valuable insights into the spatial dynamics of ecological systems.
This refined consideration of spatial autocorrelation emerges as an imperative in ecological research, fostering a deeper and more precise understanding of the intricate interplay between species diversity, spatial patterns, and the inherent limitations imposed by spatial autocorrelation (Legendre et al., 2002). This not only contributes significantly to the scientific discourse in ecology but also aligns with McGill's vision of developing predictive theories for effective conservation (Bacaro et al., 2016; McGill, 2011).
In this study by Fabien Laroche (2023), titled “Efficient sampling designs to assess biodiversity spatial autocorrelation: should we go fractal?” the primary focus was on addressing the challenges associated with estimating the autocorrelation range of species distribution across spatial scales. The study aimed to explore alternative sampling designs, with a particular focus on the application of fractal designs—self-similar designs with well-identified scales. The overarching goal was to evaluate whether fractal designs could offer a more efficient compromise compared to traditional hybrid designs, which involve mixing random sampling points with a systematic grid.
Virtual ecology provides a way to test whether sampling designs can accurately detect or quantify effects of interest before implementing them in the field. Beyond the question of assessing the power of empirical designs, a virtual ecology analysis contributes to clearly formulating the set of questions associated with a design. However, only a few virtual studies have focused on efficient designs to accurately estimate the autocorrelation range of biodiversity variables. In this study, the statistical framework of optimal design of experiments was employed—a methodology often used in building and comparing designs of temporal or spatiotemporal biodiversity surveys but rarely applied to the specific problem of quantifying spatial autocorrelation.
Key findings from the study shed light on optimal sampling strategies, with a notable dependence on the feasible grid mesh size over the study area in relation to expected autocorrelation range values. The results demonstrated that the efficiency of designs varied based on the specific effect under study. Fractal designs, however, exhibited superior performance, particularly when assessing the effect of a monotonic environmental gradient across space.
In conclusion, the study provides valuable insights into the potential benefits of incorporating fractal designs in biodiversity studies, offering a nuanced and efficient approach to estimate spatial autocorrelation. These findings contribute significantly to the ongoing scientific discourse in ecology, providing practical considerations for improving sampling designs in biodiversity assessments.
References
Bacaro, G., Altobelli, A., Cameletti, M., Ciccarelli, D., Martellos, S., Palmer, M.W., Ricotta, C., Rocchini, D., Scheiner, S.M., Tordoni, E., Chiarucci, A., 2016. Incorporating spatial autocorrelation in rarefaction methods: Implications for ecologists and conservation biologists. Ecological Indicators 69, 233-238. https://doi.org/10.1016/j.ecolind.2016.04.026
Chase, J.M., Jeliazkov, A., Ladouceur, E., Viana, D.S., 2020. Biodiversity conservation through the lens of metacommunity ecology. Annals of the New York Academy of Sciences 1469, 86-104. https://doi.org/10.1111/nyas.14378
Condit, R., Pitman, N., Leigh, E.G., Chave, J., Terborgh, J., Foster, R.B., Núñez, P., Aguilar, S., Valencia, R., Villa, G., Muller-Landau, H.C., Losos, E., Hubbell, S.P., 2002. Beta-Diversity in Tropical Forest Trees. Science 295, 666-669. https://doi.org/10.1126/science.1066854
Dale, M.R.T., Fortin, M.-J., 2002. Spatial autocorrelation and statistical tests in ecology. Écoscience 9, 162-167. https://doi.org/10.1080/11956860.2002.11682702
Delmelle, E.M., 2021. Spatial Sampling, in: Fischer, M.M., Nijkamp, P. (Eds.), Handbook of Regional Science. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 1829-1844.
Dormann, C.F., 2007. Effects of incorporating spatial autocorrelation into the analysis of species distribution data. Global Ecology & Biogeography 16, 129-128. https://doi.org/10.1111/j.1466-8238.2006.00279.x
Dormann, C.F., McPherson, J.M., Araújo, M.B., Bivand, R., Bolliger, J., Carl, G., Davies, R.G., Hirzel, A., Jetz, W., Kissling, W.D., Kühn, I., Ohlemüler, R., Peres-Neto, P.R., Reineking, B., Schröder, B., Schurr, F.M., Wilson, R., 2007. Methods to account for spatial autocorrelation in the analysis of species distributional data: a review. Ecography 33, 609-628. https://doi.org/10.1111/j.2007.0906-7590.05171.x
Fortin, M.-J., 1999a. Effects of quadrat size and data measurement on the detection of boundaries. Journal of Vegetation Science 10, 43-50. https://doi.org/10.2307/3237159
Fortin, M.-J., 1999b. Effects of sampling unit resolution on the estimation of spatial autocorrelation. Écoscience 6, 636-641. https://doi.org/10.1080/11956860.1999.11682547
Getis, A., 2010. Spatial Autocorrelation, in: Fischer, M.M., Getis, A. (Eds.), Handbook of Applied Spatial Analysis: Software Tools, Methods and Applications. Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 255-278.
Laroche, F., 2023. Efficient sampling designs to assess biodiversity spatial autocorrelation: should we go fractal? bioRxiv, 2022.07.29.501974, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.07.29.501974
Legendre, P., 1993. Spatial Autocorrelation: Trouble or New Paradigm? Ecology 74, 1659-1673. https://doi.org/10.2307/1939924
Legendre, P., Dale, M.R.T., Fortin, M.-J., Gurevitch, J., Hohn, M., Myers, D., 2002. The consequences of spatial structure for the design and analysis of ecological field surveys. Ecography 25, 601-615. https://doi.org/10.1034/j.1600-0587.2002.250508.x
Legendre, P., Fortin, M.J., 1989. Spatial pattern and ecological analysis. Vegetatio 80, 107-138. https://doi.org/10.1007/BF00048036
Legendre, P., Legendre, L., 2012. Numerical Ecology, Third Edition ed. Elsevier, The Netherlands.
McDonald, T., 2012. Spatial sampling designs for long-term ecological monitoring, in: Cooper, A.B., Gitzen, R.A., Licht, D.S., Millspaugh, J.J. (Eds.), Design and Analysis of Long-term Ecological Monitoring Studies. Cambridge University Press, Cambridge, pp. 101-125.
McGill, B.J., 2010. Matters of Scale. Science 328, 575-576. https://doi.org/10.1126/science.1188528
McGill, B.J., 2011. Linking biodiversity patterns by autocorrelated random sampling. American Journal of Botany 98, 481-502. https://doi.org/10.3732/ajb.1000509
Rahbek, C., 2005. The role of spatial scale and the perception of large-scale species-richness patterns. Ecology Letters 8, 224-239. https://doi.org/10.1111/j.1461-0248.2004.00701.x
Steel, E.A., Kennedy, M.C., Cunningham, P.G., Stanovick, J.S., 2013. Applied statistics in ecology: common pitfalls and simple solutions. Ecosphere 4, art115. https://doi.org/10.1890/ES13-00160.1
Tobler, W.R., 1970. A Computer Movie Simulating Urban Growth in the Detroit Region. Economic Geography 46, 234-240. https://doi.org/10.2307/143141
Wang, S., Lamy, T., Hallett, L.M., Loreau, M., 2019. Stability and synchrony across ecological hierarchies in heterogeneous metacommunities: linking theory to data. Ecography 42, 1200-1211. https://doi.org/10.1111/ecog.04290
Wiens, J.A., 1989. The ecology of bird communities. Cambridge University Press.
| Efficient sampling designs to assess biodiversity spatial autocorrelation : should we go fractal? | Fabien Laroche | <p>Quantifying the autocorrelation range of species distribution in space is necessary for applied ecological questions, like implementing protected area networks or monitoring programs. However, the power of spatial sampling designs to estimate t... | ![]() | Biodiversity, Landscape ecology, Spatial ecology, Metacommunities & Metapopulations, Statistical ecology | Eric Goberville | 2023-04-21 10:54:29 | View | |
12 Jun 2019
![]() Environmental heterogeneity drives tsetse fly population dynamics and controlCecilia H, Arnoux S, Picault S, Dicko A, Seck MT, Sall B, Bassene M, Vreysen M, Pagabeleguem S, Bance A, Bouyer J, Ezanno P https://doi.org/10.1101/493650Modeling jointly landscape complexity and environmental heterogeneity to envision new strategies for tsetse flies controlRecommended by Benjamin Roche based on reviews by Timothée Vergne and 1 anonymous reviewerToday, understanding spatio-temporal dynamics of pathogens is pivotal to understand their transmission and controlling them. First, understanding this dynamics can reveal the ecology of their transmission [1]. Indeed, such knowledge, based on data that are quite easy to access, can shed light on transmission modes, which could rely on different animal species that can be spatially distributed in a non-uniform way [2]. This is especially true for pathogens with complex life-cycles, despite that investigating such dynamics is very challenging and rely mostly on mathematical models. References [1] Grenfell, B. T., Bjørnstad, O. N., & Kappey, J. (2001). Travelling waves and spatial hierarchies in measles epidemics. Nature, 414(6865), 716-723. doi: 10.1038/414716a | Environmental heterogeneity drives tsetse fly population dynamics and control | Cecilia H, Arnoux S, Picault S, Dicko A, Seck MT, Sall B, Bassene M, Vreysen M, Pagabeleguem S, Bance A, Bouyer J, Ezanno P | <p>A spatially and temporally heterogeneous environment may lead to unexpected population dynamics. Knowledge still is needed on which of the local environment properties favour population maintenance at larger scale. For pathogen vectors, such as... | ![]() | Biological control, Population ecology, Spatial ecology, Metacommunities & Metapopulations | Benjamin Roche | 2018-12-14 12:13:39 | View | |
16 Jun 2020
![]() Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback frameworkTim Coulson https://doi.org/10.1101/509067Stasis and the phenotypic gambitRecommended by Tom Van Dooren based on reviews by Jacob Johansson, Katja Räsänen and 1 anonymous reviewerThe preprint "Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback framework" by Coulson (2020) presents a general framework for evolutionary ecology, useful to interpret patterns of selection and evolutionary responses to environmental transitions. The paper is written in an accessible and intuitive manner. It reviews important concepts which are at the heart of evolutionary ecology. Together, they serve as a worldview which you can carry with you to interpret patterns in data or observations in nature. I very much appreciate it that Coulson (2020) presents his personal intuition laid bare, the framework he uses for his research and how several strong concepts from theoretical ecology fit in there. Overviews as presented in this paper are important to understand how we as researchers put the pieces together. References [1] Coulson, T. (2020) Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback framework. bioRxiv, 509067, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/509067 | Environmental perturbations and transitions between ecological and evolutionary equilibria: an eco-evolutionary feedback framework | Tim Coulson | <p>I provide a general framework for linking ecology and evolution. I start from the fact that individuals require energy, trace molecules, water, and mates to survive and reproduce, and that phenotypic resource accrual traits determine an individ... | ![]() | Eco-evolutionary dynamics, Evolutionary ecology | Tom Van Dooren | 2019-01-03 10:05:16 | View | |
30 Mar 2020
![]() Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South AmericaPablo F. Cuervo, Alejandro Percara, Lucas Monje, Pablo M. Beldomenico, Martín A. Quiroga https://doi.org/10.1101/839589Catching the fly in dystopian timesRecommended by Rodrigo Medel based on reviews by 4 anonymous reviewersHost-parasite interactions are ubiquitous on Earth. They are present in almost every conceivable ecosystem and often result from a long history of antagonist coevolution [1,2]. Recent studies on climate change have revealed, however, that modification of abiotic variables are often accompanied by shifts in the distributional range of parasites to habitats far beyond their original geographical distribution, creating new interactions in novel habitats with unpredictable consequences for host community structure and organization [3,4]. This situation may be especially critical for endangered host species having small population abundance and restricted distribution range. The infestation of bird species with larvae of the muscid fly genus Philornis is a case in point. At least 250 bird species inhabiting mostly Central and South America are infected by Philornis flies [5,6]. Fly larval development occurs in bird faeces, nesting material, or inside nestlings, affecting the development and nestling survival. References [1] Thompson JN (1994) The Coevolutionary Process. University of Chicago Press. | Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America | Pablo F. Cuervo, Alejandro Percara, Lucas Monje, Pablo M. Beldomenico, Martín A. Quiroga | <p>*Philornis* flies are the major cause of myasis in altricial nestlings of neotropical birds. Its impact ranges from subtle to lethal, being of major concern in endangered bird species with geographically-restricted, fragmented and small-sized p... | ![]() | Biogeography, Macroecology, Parasitology, Species distributions | Rodrigo Medel | 2019-11-26 21:31:33 | View | |
14 Nov 2022
![]() Estimating abundance of a recovering transboundary brown bear population with capture-recapture modelsCécile Vanpé, Blaise Piédallu, Pierre-Yves Quenette, Jérôme Sentilles, Guillaume Queney, Santiago Palazón, Ivan Afonso Jordana, Ramón Jato, Miguel Mari Elósegui Irurtia, Jordi Solà de la Torre, Olivier Gimenez https://doi.org/10.1101/2021.12.08.471719A new and efficient approach to estimate, from protocol and opportunistic data, the size and trends of populations: the case of the Pyrenean brown bearRecommended by Nicolas BECH based on reviews by Tim Coulson, Romain Pigeault and ?In this study, the authors report a new method for estimating the abundance of the Pyrenean brown bear population. Precisely, the methodology involved aims to apply Pollock's closed robust design (PCRD) capture-recapture models to estimate population abundance and trends over time. Overall, the results encourage the use of PCRD to study populations' demographic rates, while minimizing biases due to inter-individual heterogeneity in detection probabilities. Estimating the size and trends of animal population over time is essential for informing conservation status and management decision-making (Nichols & Williams 2006). This is particularly the case when the population is small, geographically scattered, and threatened. Although several methods can be used to estimate population abundance, they may be difficult to implement when individuals are rare, elusive, solitary, largely nocturnal, highly mobile, and/or occupy large home ranges in remote and/or rugged habitats. Moreover, in such standard methods,
However, these conditions are rarely met in real populations, such as wild mammals (e.g., Bellemain et al. 2005; Solbert et al. 2006), and therefore the risk of underestimating population size can rapidly increase because the assumption of perfect detection of all individuals in the population is violated. Focusing on the critically endangered Pyrenean brown bear that was close to extinction in the mid-1990s, the study by Vanpe et al. (2022), uses protocol and opportunistic data to describe a statistical modeling exercise to construct mark-recapture histories from 2008 to 2020. Among the data, the authors collected non-invasive samples such as a mixture of hair and scat samples used for genetic identification, as well as photographic trap data of recognized individuals. These data are then analyzed in RMark to provide detection and survival estimates. The final model (i.e. PCRD capture-recapture) is then used to provide Bayesian population estimates. Results show a five-fold increase in population size between 2008 and 2020, from 13 to 66 individuals. Thus, this study represents the first published annual abundance and temporal trend estimates of the Pyrenean brown bear population since 2008. Then, although the results emphasize that the PCRD estimates were broadly close to the MRS counts and had reasonably narrow associated 95% Credibility Intervals, they also highlight that the sampling effort is different according to individuals. Indeed, as expected, the detection of an individual depends on
Overall, the PCRD capture-recapture modelling approach, involved in this study, provides robust estimates of abundance and demographic rates of the Pyrenean brown bear population (with associated uncertainty) while minimizing and considering bias due to inter-individual heterogeneity in detection probabilities. The authors conclude that mark-recapture provides useful population estimates and urge wildlife ecologists and managers to use robust approaches, such as the RDPC capture-recapture model, when studying large mammal populations. This information is essential to inform management decisions and assess the conservation status of populations.
References Bellemain, E.V.A., Swenson, J.E., Tallmon, D., Brunberg, S. and Taberlet, P. (2005). Estimating population size of elusive animals with DNA from hunter-collected feces: four methods for brown bears. Cons. Biol. 19(1), 150-161. https://doi.org/10.1111/j.1523-1739.2005.00549.x Nichols, J.D. and Williams, B.K. (2006). Monitoring for conservation. Trends Ecol. Evol. 21(12), 668-673. https://doi.org/10.1016/j.tree.2006.08.007 Otis, D.L., Burnham, K.P., White, G.C. and Anderson, D.R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs (62), 3-135. Solberg, K.H., Bellemain, E., Drageset, O.M., Taberlet, P. and Swenson, J.E. (2006). An evaluation of field and non-invasive genetic methods to estimate brown bear (Ursus arctos) population size. Biol. Conserv. 128(2), 158-168. https://doi.org/10.1016/j.biocon.2005.09.025 Vanpé C, Piédallu B, Quenette P-Y, Sentilles J, Queney G, Palazón S, Jordana IA, Jato R, Elósegui Irurtia MM, de la Torre JS, and Gimenez O (2022) Estimating abundance of a recovering transboundary brown bear population with capture-recapture models. bioRxiv, 2021.12.08.471719, ver. 4 recommended and peer-reviewed by PCI Ecology. https://doi.org/10.1101/2021.12.08.471719 | Estimating abundance of a recovering transboundary brown bear population with capture-recapture models | Cécile Vanpé, Blaise Piédallu, Pierre-Yves Quenette, Jérôme Sentilles, Guillaume Queney, Santiago Palazón, Ivan Afonso Jordana, Ramón Jato, Miguel Mari Elósegui Irurtia, Jordi Solà de la Torre, Olivier Gimenez | <p>Estimating the size of small populations of large mammals can be achieved via censuses, or complete counts, of recognizable individuals detected over a time period: minimum detected (population) size (MDS). However, as a population grows larger... | ![]() | Conservation biology, Demography, Population ecology | Nicolas BECH | 2022-01-20 10:49:59 | View | |
18 Mar 2019
![]() Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasiteAmalia Rataud, Marlène Dupraz, Céline Toty, Thomas Blanchon, Marion Vittecoq, Rémi Choquet, Karen D. McCoy https://doi.org/10.5281/zenodo.2592114Limited dispersal in a vector on territorial hostsRecommended by Adele Mennerat based on reviews by Shelly Lachish and 1 anonymous reviewerParasitism requires parasites and hosts to meet and is therefore conditioned by their respective dispersal abilities. While dispersal has been studied in a number of wild vertebrates (including in relation to infection risk), we still have poor knowledge of the movements of their parasites. Yet we know that many parasites, and in particular vectors transmitting pathogens from host to host, possess the ability to move actively during at least part of their lives. References | Evaluating functional dispersal and its eco-epidemiological implications in a nest ectoparasite | Amalia Rataud, Marlène Dupraz, Céline Toty, Thomas Blanchon, Marion Vittecoq, Rémi Choquet, Karen D. McCoy | <p>Functional dispersal (between-site movement, with or without subsequent reproduction) is a key trait acting on the ecological and evolutionary trajectories of a species, with potential cascading effects on other members of the local community. ... | ![]() | Dispersal & Migration, Epidemiology, Parasitology, Population ecology | Adele Mennerat | 2018-11-05 11:44:58 | View | |
01 Feb 2020
![]() Touchy matter: the delicate balance between Morgan’s canon and open-minded description of advanced cognitive skills in the animalRecommended by Francois-Xavier Dechaume-MoncharmontIn a recent paper published in PNAS, Fayet et al. [1] reported scarce field observations of two Atlantic puffins (four years apart) apparently scratching their bodies using sticks, which was interpreted by the authors as evidence of tool use in this species. In a short response, Benjamin Farrar [2] raises serious concerns about this interpretation and proposes simpler, more parsimonious, mechanisms explaining the observed behaviour: a textbook case of Morgan's canon. References [1] Fayet, A. L., Hansen, E. S., and Biro, D. (2020). Evidence of tool use in a seabird. Proceedings of the National Academy of Sciences, 117(3), 1277–1279. doi: 10.1073/pnas.1918060117 | Evidence of tool use in a seabird? | Benjamin G. Farrar | Fayet, Hansen and Biro (1) provide two observations of Atlantic puffins, *Fratercula arctica*, performing self-directed actions while holding a stick in their beaks. The authors interpret this as evidence of tool use as they suggest that the stick... | ![]() | Behaviour & Ethology | Francois-Xavier Dechaume-Moncharmont | 2020-01-22 11:55:27 | View | |
24 May 2023
![]() Evolutionary determinants of reproductive seasonality: a theoretical approachLugdiwine Burtschell, Jules Dezeure, Elise Huchard, Bernard Godelle https://doi.org/10.1101/2022.08.22.504761When does seasonal reproduction evolve?Recommended by Tim CoulsonHave you ever wondered why some species breed seasonally while others do not? You might think it is all down to lattitude and the harshness of winters but it turns out it is quite a bit more complicated than that. A consequence of this is that climate change may result in the evolution of the degree of seasonal reproduction, with some species perhaps becoming less seasonal and others more so even in the same habitat. Burtschell et al. (2023) investigated how various factors influence seasonal breeding by building an individual-based model of a baboon population from which they calculated the degree of seasonality for the fittest reproductive strategy. They then altered key aspects of their model to examine how these changes impacted the degree of seasonality in the reproductive strategy. What they found is fascinating. The degree of seasonality in reproductive strategy is expected to increase with increased seasonality in the environment, decreased food availability, increased energy expenditure, and how predictable resource availability is. Interestingly, neither female cycle length nor extrinsic infant mortality influenced the degree of seasonality in reproduction. What this means in reality for seasonal species is more challenging to understand. Some environments appear to be becoming more seasonal yet less predictable, and some species appear to be altering their daily energy budgets in response to changing climate in quite complex ways. As with pretty much everything in biology, Burtschell et al.'s work reveals much nuance and complexity, and that predicting how species might alter their reproductive timing is fraught with challenges. The paper is very well written. With a simpler model it may have proven possible to achieve analytical solutions, but this is a very minor gripe. The reviewers were positive about the paper, and I have little doubt it will be well-cited. REFERENCES Burtschell L, Dezeure J, Huchard E, Godelle B (2023) Evolutionary determinants of reproductive seasonality: a theoretical approach. bioRxiv, 2022.08.22.504761, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.22.504761 | Evolutionary determinants of reproductive seasonality: a theoretical approach | Lugdiwine Burtschell, Jules Dezeure, Elise Huchard, Bernard Godelle | <p style="text-align: justify;">Reproductive seasonality is a major adaptation to seasonal cycles and varies substantially among organisms. This variation, which was long thought to reflect a simple latitudinal gradient, remains poorly understood ... | ![]() | Evolutionary ecology, Life history, Theoretical ecology | Tim Coulson | Nigel Yoccoz | 2022-08-23 21:37:28 | View |
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