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03 Oct 2023
Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sourcesThibaut Ferraille, Christian Kerbiriou, Charlotte Bigard, Fabien Claireau, John D. Thompson https://doi.org/10.1101/2023.05.09.539999Biodiversity databases are ever more numerous, but can they be used reliably for Species Distribution Modelling?Recommended by Nicolas Schtickzelle based on reviews by 2 anonymous reviewersProposing efficient guidelines for biodiversity conservation often requires the use of forecasting tools. Species Distribution Models (SDM) are more and more used to predict how the distribution of a species will react to environmental change, including any large-scale management actions that could be implemented. Their use is also boosted by the increase of publicly available biodiversity databases[1]. The now famous aphorism by George Box "All models are wrong but some are useful"[2] very well summarizes that the outcome of a model must be adjusted to, and will depend on, the data that are used to parameterize it. The question of the reliability of using biodiversity databases to parameterize biodiversity models such as SDM –but the question would also apply to other kinds of biodiversity models, e.g. Population Viability Analysis models[3]– is key to determine the confidence that can be placed in model predictions. This point is often overlooked by some categories of biodiversity conservation stakeholders, in particular the fact that some data were collected using controlled protocols while others are opportunistic. In this study[4], the authors use a collection of databases covering a range of species as well as of geographic scales in France and using different data collection and validation approaches as a case study to evaluate the impact of data quality when performing Strategic Environmental Assessment (SEA). Among their conclusions, the fact that a large-scale database (what they call the “country” level) is necessary to reliably parameterize SDM. Besides this and other conclusions of their study, which are likely to be in part specific to their case study –unfortunately for its conservation, biodiversity is complex and varies a lot–, the merit of this work lies in the approach used to test the impact of data on model predictions. References 1. Feng, X. et al. A review of the heterogeneous landscape of biodiversity databases: Opportunities and challenges for a synthesized biodiversity knowledge base. Global Ecology and Biogeography 31, 1242–1260 (2022). https://doi.org/10.1111/geb.13497 2. Box, G. E. P. Robustness in the Strategy of Scientific Model Building. in Robustness in Statistics (eds. Launer, R. L. & Wilkinson, G. N.) 201–236 (Academic Press, 1979). https://doi.org/10.1016/B978-0-12-438150-6.50018-2. 3. Beissinger, S. R. & McCullough, D. R. Population Viability Analysis. (The University of Chicago Press, 2002). 4. Ferraille, T., Kerbiriou, C., Bigard, C., Claireau, F. & Thompson, J. D. (2023) Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sources. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.05.09.539999 | Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sources | Thibaut Ferraille, Christian Kerbiriou, Charlotte Bigard, Fabien Claireau, John D. Thompson | <p>Strategic Environmental Assessment (SEA) of land-use planning is a fundamental tool to minimize environmental impacts of artificialization. In this context, Systematic Conservation Planning (SCP) tools based on Species Distribution Models (SDM)... | Biodiversity, Conservation biology, Species distributions, Terrestrial ecology | Nicolas Schtickzelle | 2023-05-11 09:41:05 | View | ||
11 Aug 2023
Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary BiologyEdward Ivimey-Cook, Joel Pick, Kevin Bairos-Novak, Antica Culina, Elliot Gould, Matthew Grainger, Benjamin Marshall, David Moreau, Matthieu Paquet, Raphaël Royauté, Alfredo Sanchez-Tojar, Inês Silva, Saras Windecker https://doi.org/10.32942/X2CG64A handy “How to” review code for ecologists and evolutionary biologistsRecommended by Corina Logan based on reviews by Serena Caplins and 1 anonymous reviewerIvimey Cook et al. (2023) provide a concise and useful “How to” review code for researchers in the fields of ecology and evolutionary biology, where the systematic review of code is not yet standard practice during the peer review of articles. Consequently, this article is full of tips for authors on how to make their code easier to review. This handy article applies not only to ecology and evolutionary biology, but to many fields that are learning how to make code more reproducible and shareable. Taking this step toward transparency is key to improving research rigor (Brito et al. 2020) and is a necessary step in helping make research trustable by the public (Rosman et al. 2022). References Brito, J. J., Li, J., Moore, J. H., Greene, C. S., Nogoy, N. A., Garmire, L. X., & Mangul, S. (2020). Recommendations to enhance rigor and reproducibility in biomedical research. GigaScience, 9(6), giaa056. https://doi.org/10.1093/gigascience/giaa056 Ivimey-Cook, E. R., Pick, J. L., Bairos-Novak, K., Culina, A., Gould, E., Grainger, M., Marshall, B., Moreau, D., Paquet, M., Royauté, R., Sanchez-Tojar, A., Silva, I., Windecker, S. (2023). Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary Biology. EcoEvoRxiv, ver 5 peer-reviewed and recommended by Peer Community In Ecology. https://doi.org/10.32942/X2CG64 Rosman, T., Bosnjak, M., Silber, H., Koßmann, J., & Heycke, T. (2022). Open science and public trust in science: Results from two studies. Public Understanding of Science, 31(8), 1046-1062. https://doi.org/10.1177/09636625221100686 | Implementing Code Review in the Scientific Workflow: Insights from Ecology and Evolutionary Biology | Edward Ivimey-Cook, Joel Pick, Kevin Bairos-Novak, Antica Culina, Elliot Gould, Matthew Grainger, Benjamin Marshall, David Moreau, Matthieu Paquet, Raphaël Royauté, Alfredo Sanchez-Tojar, Inês Silva, Saras Windecker | <p>Code review increases reliability and improves reproducibility of research. As such, code review is an inevitable step in software development and is common in fields such as computer science. However, despite its importance, code review is not... | Meta-analyses, Statistical ecology | Corina Logan | 2023-05-19 15:54:01 | View | ||
11 Mar 2024
Sex differences in the relationship between maternal and neonate cortisol in a free-ranging large mammalAmin, B., Fishman, R., Quinn, M., Matas, D., Palme, R., Koren, L., Ciuti, S. https://doi.org/10.1101/2023.05.04.538920Stress and stress hormones’ transmission from mothers to offspringRecommended by Matthieu Paquet based on reviews by 2 anonymous reviewersIndividuals can respond to environmental changes that they undergo directly (within-generation plasticity) but also through transgenerational plasticity, providing lasting effects that are transmitted to the next generations (Donelson et al. 2012; Munday et al. 2013; Kuijper & Hoyle 2015; Auge et al. 2017, Tariel et al. 2020). These parental effects can affect offspring via various mechanisms, notably via maternal transmission of hormones to the eggs or growing embryos (Mousseau & Fox 1998). While the effects of environmental quality may simply carry-over to the next generation (e.g., females in stressful environments give birth to offspring in poorer condition), parental effects may also be a mechanism that adjusts offspring phenotype in response to environmental variation and predictability, and thereby match offspring's phenotype to future environmental conditions (Gluckman et al. 2005; Marshall & Uller 2007; Dey et al. 2016; Yin et al. 2019), for example by preparing their offspring to an expected stressful environment. When females experience stress during gestation or egg formation, elevations in glucocorticoids (GC) are expected to affect offspring phenotype in many ways, from the offspring's own GC levels, to their growth and survival (Sheriff et al. 2017). This is a well established idea, but how strong is the evidence for this? A meta-analysis on birds found no clear effect of corticosterone manipulation on offspring traits (38 studies on 9 bird species for corticosterone manipulation; Podmokła et al. 2018). Another meta-analysis including 14 vertebrate species found no clear effect of prenatal stress on offspring GC (Thayer et al. 2018). Finally, a meta-analysis on wild vertebrates (23 species) found no clear effect of GC-mediated maternal effects on offspring traits (MacLeod et al. 2021). As often when facing such inconclusive results, context dependence has been suggested as one potential reason for such inconsistencies, for exemple sex specific effects (Groothuis et al. 2019, 2020). However, sex specific measures on offspring are scarce (Podmokła et al. 2018). Moreover, the literature available is still limited to a few, mostly “model” species. With their study, Amin et al. (2024) show the way to improve our understanding on GC transmission from mother to offspring and its effects in several aspects. First they used innovative non-invasive methods (which could broaden the range of species available to study) by quantifying cortisol metabolites from faecal samples collected from pregnant females, as proxy for maternal GC level, and relating it to GC levels from hairs of their neonate offspring. Second they used a free ranging large mammal (taxa from which literature is missing): the fallow deer (Dama dama). Third, they provide sex specific measures of GC levels. And finally but importantly, they are exemplary in their transparency regarding 1) the exploratory nature of their study, 2) their statistical thinking and procedure, and 3) the study limitations (e.g., low sample size and high within individual variation of measurements). I hope this study will motivate more research (on the fallow deer, and on other species) to broaden and strengthen our understanding of sex specific effects of maternal stress and CG levels on offspring phenotype and fitness. References Amin, B., Fishman, R., Quinn, M., Matas, D., Palme, R., Koren, L., & Ciuti, S. (2024). Sex differences in the relationship between maternal and foetal glucocorticoids in a free-ranging large mammal. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.05.04.538920 Auge, G.A., Leverett, L.D., Edwards, B.R. & Donohue, K. (2017). Adjusting phenotypes via within-and across-generational plasticity. New Phytologist, 216, 343–349. https://doi.org/10.1111/nph.14495 Dey, S., Proulx, S.R. & Teotonio, H. (2016). Adaptation to temporally fluctuating environments by the evolution of maternal effects. PLoS biology, 14, e1002388. https://doi.org/10.1371/journal.pbio.1002388 Donelson, J.M., Munday, P.L., McCormick, M.I. & Pitcher, C.R. (2012). Rapid transgenerational acclimation of a tropical reef fish to climate change. Nature Climate Change, 2, 30. https://doi.org/10.1038/nclimate1323 Gluckman, P.D., Hanson, M.A. & Spencer, H.G. (2005). Predictive adaptive responses and human evolution. Trends in ecology & evolution, 20, 527–533. https://doi.org/10.1016/j.tree.2005.08.001 Groothuis, Ton GG, Bin-Yan Hsu, Neeraj Kumar, and Barbara Tschirren. "Revisiting mechanisms and functions of prenatal hormone-mediated maternal effects using avian species as a model." Philosophical Transactions of the Royal Society B 374, no. 1770 (2019): 20180115. https://doi.org/10.1098/rstb.2018.0115 Groothuis, Ton GG, Neeraj Kumar, and Bin-Yan Hsu. "Explaining discrepancies in the study of maternal effects: the role of context and embryo." Current Opinion in Behavioral Sciences 36 (2020): 185-192. https://doi.org/10.1016/j.cobeha.2020.10.006 Kuijper, B. & Hoyle, R.B. (2015). When to rely on maternal effects and when on phenotypic plasticity? Evolution, 69, 950–968. https://doi.org/10.1111/evo.12635 MacLeod, Kirsty J., Geoffrey M. While, and Tobias Uller. "Viviparous mothers impose stronger glucocorticoid‐mediated maternal stress effects on their offspring than oviparous mothers." Ecology and Evolution 11, no. 23 (2021): 17238-17259. Marshall, D.J. & Uller, T. (2007). When is a maternal effect adaptive? Oikos, 116, 1957–1963. https://doi.org/10.1111/j.2007.0030-1299.16203.x Mousseau, T.A. & Fox, C.W. (1998). Maternal effects as adaptations. Oxford University Press. Munday, P.L., Warner, R.R., Monro, K., Pandolfi, J.M. & Marshall, D.J. (2013). Predicting evolutionary responses to climate change in the sea. Ecology Letters, 16, 1488–1500. https://doi.org/10.1111/ele.12185 Podmokła, Edyta, Szymon M. Drobniak, and Joanna Rutkowska. "Chicken or egg? Outcomes of experimental manipulations of maternally transmitted hormones depend on administration method–a meta‐analysis." Biological Reviews 93, no. 3 (2018): 1499-1517. https://doi.org/10.1111/brv.12406 Sheriff, M. J., Bell, A., Boonstra, R., Dantzer, B., Lavergne, S. G., McGhee, K. E., MacLeod, K. J., Winandy, L., Zimmer, C., & Love, O. P. (2017). Integrating ecological and evolutionary context in the study of maternal stress. Integrative and Comparative Biology, 57(3), 437–449. https://doi.org/10.1093/icb/icx105 Tariel, Juliette, Sandrine Plénet, and Émilien Luquet. "Transgenerational plasticity in the context of predator-prey interactions." Frontiers in Ecology and Evolution 8 (2020): 548660. https://doi.org/10.3389/fevo.2020.548660 Thayer, Zaneta M., Meredith A. Wilson, Andrew W. Kim, and Adrian V. Jaeggi. "Impact of prenatal stress on offspring glucocorticoid levels: A phylogenetic meta-analysis across 14 vertebrate species." Scientific Reports 8, no. 1 (2018): 4942. https://doi.org/10.1038/s41598-018-23169-w Yin, J., Zhou, M., Lin, Z., Li, Q.Q. & Zhang, Y.-Y. (2019). Transgenerational effects benefit offspring across diverse environments: a meta-analysis in plants and animals. Ecology letters, 22, 1976–1986. https://doi.org/10.1111/ele.13373 | Sex differences in the relationship between maternal and neonate cortisol in a free-ranging large mammal | Amin, B., Fishman, R., Quinn, M., Matas, D., Palme, R., Koren, L., Ciuti, S. | <p style="text-align: justify;">Maternal phenotypes can have long-term effects on offspring phenotypes. These maternal effects may begin during gestation, when maternal glucocorticoid (GC) levels may affect foetal GC levels, thereby having an orga... | Evolutionary ecology, Maternal effects, Ontogeny, Physiology, Zoology | Matthieu Paquet | 2023-06-05 09:06:56 | View | ||
03 Jan 2024
Diagnosis of planktonic trophic network dynamics with sharp qualitative changesCedric Gaucherel, Stolian Fayolle, Raphael Savelli, Olivier Philippine, Franck Pommereau, Christine Dupuy https://doi.org/10.1101/2023.06.29.547055A new approach to describe qualitative changes of complex trophic networksRecommended by Francis Raoul based on reviews by Tim Coulson and 1 anonymous reviewerModelling the temporal dynamics of trophic networks has been a key challenge for community ecologists for decades, especially when anthropogenic and natural forces drive changes in species composition, abundance, and interactions over time. So far, most modelling methods fail to incorporate the inherent complexity of such systems, and its variability, to adequately describe and predict temporal changes in the topology of trophic networks. Taking benefit from theoretical computer science advances, Gaucherel and colleagues (2024) propose a new methodological framework to tackle this challenge based on discrete-event Petri net methodology. To introduce the concept to naïve readers the authors provide a useful example using a simplistic predator-prey model. The core biological system of the article is a freshwater trophic network of western France in the Charente-Maritime marshes of the French Atlantic coast. A directed graph describing this system was constructed to incorporate different functional groups (phytoplankton, zooplankton, resources, microbes, and abiotic components of the environment) and their interactions. Rules and constraints were then defined to, respectively, represent physiochemical, biological, or ecological processes linking network components, and prevent the model from simulating unrealistic trajectories. Then the full range of possible trajectories of this mechanistic and qualitative model was computed. The model performed well enough to successfully predict a theoretical trajectory plus two trajectories of the trophic network observed in the field at two different stations, therefore validating the new methodology introduced here. The authors conclude their paper by presenting the power and drawbacks of such a new approach to qualitatively model trophic networks dynamics. Reference Cedric Gaucherel, Stolian Fayolle, Raphael Savelli, Olivier Philippine, Franck Pommereau, Christine Dupuy (2024) Diagnosis of planktonic trophic network dynamics with sharp qualitative changes. bioRxiv 2023.06.29.547055, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.06.29.547055 | Diagnosis of planktonic trophic network dynamics with sharp qualitative changes | Cedric Gaucherel, Stolian Fayolle, Raphael Savelli, Olivier Philippine, Franck Pommereau, Christine Dupuy | <p>Trophic interaction networks are notoriously difficult to understand and to diagnose (i.e., to identify contrasted network functioning regimes). Such ecological networks have many direct and indirect connections between species, and these conne... | Community ecology, Ecosystem functioning, Food webs, Freshwater ecology, Interaction networks, Microbial ecology & microbiology | Francis Raoul | Tim Coulson | 2023-07-03 10:42:34 | View | |
19 Mar 2024
How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approachPaul Savary, Cécile Tannier, Jean-Christophe Foltête, Marc Bourgeois, Gilles Vuidel, Aurélie Khimoun, Hervé Moal, Stéphane Garnier https://doi.org/10.32942/X2JS41Gene flow in the city. Unravelling the mechanisms behind the variability in urbanization effects on genetic patterns.Recommended by Aurélie Coulon based on reviews by 2 anonymous reviewersWorldwide, city expansion is happening at a fast rate and at the same time, urbanists are more and more required to make place for biodiversity. Choices have to be made regarding the area and spatial arrangement of suitable spaces for non-human living organisms, that will favor the long-term survival of their populations. To guide those choices, it is necessary to understand the mechanisms driving the effects of land management on biodiversity. Research results on the effects of urbanization on genetic diversity have been very diverse, with studies showing higher genetic diversity in rural than in urban populations (e.g. Delaney et al. 2010), the contrary (e.g. Miles et al. 2018) or no difference (e.g. Schoville et al. 2013). The same is true for studies investigating genetic differentiation. The reasons for these differences probably lie in the relative intensities of gene flow and genetic drift in each case study, which are hard to disentangle and quantify in empirical datasets. In their paper, Savary et al. (2024) used an elegant and powerful simulation approach to better understand the diversity of observed patterns and investigate the effects of dispersal limitation on genetic patterns (diversity and differentiation). Their simulations involved the landscapes of 325 real European cities, each under three different scenarios mimicking 3 virtual urban tolerant species with different abilities to move within cities while genetic drift intensity was held constant across scenarios. The cities were chosen so that the proportion of artificial areas was held constant (20%) but their location and shape varied. This design allowed the authors to investigate the effect of connectivity and spatial configuration of habitat on the genetic responses to spatial variations in dispersal in cities. The main results of this simulation study demonstrate that variations in dispersal spatial patterns, for a given level of genetic drift, trigger variations in genetic patterns. Genetic diversity was lower and genetic differentiation was larger when species had more difficulties to move through the more hostile components of the urban environment. The increase of the relative importance of drift over gene flow when dispersal was spatially more constrained was visible through the associated disappearance of the pattern of isolation by resistance. Forest patches (usually located at the periphery of the cities) usually exhibited larger genetic diversity and were less differentiated than urban green spaces. But interestingly, the presence of habitat patches at the interface between forest and urban green spaces lowered those differences through the promotion of gene flow. One other noticeable result, from a landscape genetic method point of view, is the fact that there might be a limit to the detection of barriers to genetic clusters through clustering analyses because of the increased relative effect of genetic drift. This result needs to be confirmed, though, as genetic structure has only been investigated with a recent approach based on spatial graphs. It would be interesting to also analyze those results with the usual Bayesian genetic clustering approaches. Overall, this study addresses an important scientific question about the mechanisms explaining the diversity of observed genetic patterns in cities. But it also provides timely cues for connectivity conservation and restoration applied to cities. Delaney, K. S., Riley, S. P., and Fisher, R. N. (2010). A rapid, strong, and convergent genetic response to urban habitat fragmentation in four divergent and widespread vertebrates. PLoS ONE, 5(9):e12767. | How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach | Paul Savary, Cécile Tannier, Jean-Christophe Foltête, Marc Bourgeois, Gilles Vuidel, Aurélie Khimoun, Hervé Moal, Stéphane Garnier | <p><em>Context and objectives</em></p> <p>Although urbanization is a major driver of biodiversity erosion, it does not affect all species equally. The neutral genetic structure of populations in a given species is affected by both genetic drift a... | Biodiversity, Conservation biology, Dispersal & Migration, Eco-evolutionary dynamics, Human impact, Landscape ecology, Molecular ecology, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Terrestrial ecology | Aurélie Coulon | 2023-07-25 19:09:16 | View | ||
23 Jan 2024
Use of linear features by red-legged partridges in an intensive agricultural landscape: implications for landscape management in farmlandCharlotte Perrot, Antoine Berceaux, Mathias Noel, Beatriz Arroyo, Leo Bacon https://doi.org/10.1101/2023.07.27.550774The importance of managing linear features in agricultural landscapes for farmland birdsRecommended by Ricardo Correia based on reviews by Matthew Grainger and 1 anonymous reviewerEuropean farmland bird populations continue declining at an alarming rate, and some species require urgent action to avoid their demise (Silva et al. 2024). While factors such as climate change and urbanization also play an important role in driving the decline of farmland bird populations, its main driver seems to be linked with agricultural intensification (Rigal et al. 2023). Besides increased pesticide and fertilizer use, agricultural intensification often results in the homogenization of agricultural landscapes through the removal of seminatural linear features such as hedgerows, field margins, and grassy strips that can be beneficial for biodiversity. These features may be particularly important during the breeding season, when breeding farmland birds can benefit from patches of denser vegetation to conceal nests and improve breeding success. It is both important and timely to understand how landscape management can help to address the ongoing decline of farmland birds by identifying specific actions that can boost breeding success. Perrot et al. 2023 contribute to this effort by exploring how red-legged partridges use linear features in an intensive agricultural landscape during the breeding season. Through a combination of targeted fieldwork and GPS tracking, the authors highlight patterns in home range size and habitat selection that provide insights for landscape management. Specifically, their results suggest that birds have smaller range sizes in the vicinity of traffic routes and seminatural features structured by both herbaceous and woody cover. Furthermore, they show that breeding birds tend to choose linear elements with herbaceous cover whereas non-breeders prefer linear elements with woody cover, underlining the importance of accounting for the needs of both breeding and non-breeding birds. In particular, the authors stress the importance of providing additional vegetation elements such as hedges, grassy strips or embankments in order to increase landscape heterogeneity. These landscape elements are usually found in the vicinity of linear infrastructures such as roads and tracks, but it is important they are available also in separate areas to avoid the risk of bird collision and the authors provide specific recommendations towards this end. Overall, this is an important study with clear recommendations on how to improve landscape management for these farmland birds. References Perrot, C., Séranne, L., Berceaux, A., Noel, M., Arroyo, B., & Bacon, L. (2023) "Use of linear features by red-legged partridges in an intensive agricultural landscape: implications for landscape management in farmland." bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. | Use of linear features by red-legged partridges in an intensive agricultural landscape: implications for landscape management in farmland | Charlotte Perrot, Antoine Berceaux, Mathias Noel, Beatriz Arroyo, Leo Bacon | <p>Current agricultural practices and change are the major cause of biodiversity loss. An important change associated with the intensification of agriculture in the last 50 years is the spatial homogenization of the landscape with substantial loss... | Agroecology, Behaviour & Ethology, Biodiversity, Conservation biology, Habitat selection | Ricardo Correia | 2023-08-01 10:27:33 | View | ||
23 Oct 2023
The Moa the Merrier: Resolving When the Dinornithiformes Went ExtinctFloe Foxon https://doi.org/10.1101/2023.08.07.552261Are Moas ancient Lazarus species?Recommended by Werner Ulrich based on reviews by Tim Coulson and Richard HoldawayAncient human colonisation often had catastrophic consequences for native fauna. The North American Megafauna went extinct shortly after humans entered the scene and Madagascar suffered twice, before 1500 CE and around 1700 CE after the Malayan and European colonisation. Maoris colonised New Zealand by about 1300 and a century later the giant Moa birds (Dinornithiformes) sharply declined. But did they went extinct or are they an ancient example of Lazarus species, species thought to be extinct but still alive? Scattered anecdotes of late sightings of living Moas even up to the 20th century seem to suggest the latter. The quest for later survival has also a criminal aspect. Who did it, the Maoris or the white colonisers in the late 18th century? The present work by Floe Foxon (2023) tries to settle this question. It uses a survival modelling approach and an assessment of the reliability of nearly 100 alleged sightings. The model favours the so-called overkill hypothesis, that Moas probably went extinct in the 15th century shortly after Maori colonisation. A small but still remarkable probability remained for survival up to 1770. Later sightings turned out to be highly unreliable. The paper is important as it does not rely on subjective discussions of late sightings but on a probabilistic modelling approach with sensitivity testing prior applied to marsupials. As common in probabilistic approaches, the study does not finally settle the case. A probability of as much as 20% remained for late survival after 1450 CE. This is not improbable as New Zealand was sufficiently unexplored in those days to harbour a few refuges for late survivors. However, in this respect, it is a bit unfortunate that at the end of the discussion, the paper cites Heuvelmans, the founder of cryptozoology, and it mentions the ivory-billed woodpecker, which has recently been redetected. No Moa remains were found after 1450. References Foxon F (2023) The Moa the Merrier: Resolving When the Dinornithiformes Went Extinct. bioRxiv, 2023.08.07.552261, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.08.07.552261 | The Moa the Merrier: Resolving When the Dinornithiformes Went Extinct | Floe Foxon | <p style="text-align: justify;">The Moa (Aves: Dinornithiformes) are an extinct group of the ratite clade from New Zealand. The overkill hypothesis asserts that the first New Zealand settlers hunted the Moa to extinction by 1450 CE, whereas the st... | Conservation biology, Human impact, Statistical ecology, Zoology | Werner Ulrich | Tim Coulson, Richard Holdaway | 2023-08-08 17:14:30 | View | |
02 Jan 2024
Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy modelsRahel Sollmann https://doi.org/10.1101/2023.08.08.552394Useful clarity on the value of considering temporal variability in detection probabilityRecommended by Benjamin Bolker based on reviews by Dana Karelus and Ben AugustineAs so often quoted, "all models are wrong; more specifically, we always neglect potentially important factors in our models of ecological systems. We may neglect these factors because no-one has built a computational framework to include them; because including them would be computationally infeasible; or because we don't have enough data. When considering whether to include a particular process or form of heterogeneity, the gold standard is to fit models both with and without the component, and then see whether we needed the component in the first place -- that is, whether including that component leads to an important difference in our conclusions. However, this approach is both tedious and endless, because there are an infinite number of components that we could consider adding to any given model. Therefore, thoughtful exercises that evaluate the importance of particular complications under a realistic range of simulations and a representative set of case studies are extremely valuable for the field. While they cannot provide ironclad guarantees, they give researchers a general sense of when they can (probably) safely ignore some factors in their analyses. This paper by Sollmann (2024) shows that for a very wide range of scenarios, temporal and spatiotemporal variability in the probability of detection have little effect on the conclusions of spatial capture-recapture and occupancy models. The author is thoughtful about when such variability may be important, e.g. when variation in detection and density is correlated and thus confounded, or when variation is driven by animals' behavioural responses to being captured. | Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models | Rahel Sollmann | <p>State variables such as abundance and occurrence of species are central to many questions in ecology and conservation, but our ability to detect and enumerate species is imperfect and often varies across space and time. Accounting for imperfect... | Euring Conference, Statistical ecology | Benjamin Bolker | Dana Karelus, Ben Augustine, Ben Augustine | 2023-08-10 09:18:56 | View | |
18 Sep 2024
Predicting species distributions in the open ocean with convolutional neural networksGaétan Morand, Alexis Joly, Tristan Rouyer, Titouan Lorieul, Julien Barde https://doi.org/10.1101/2023.08.11.551418The potential of Convolutional Neural Networks for modeling species distributionsRecommended by François Munoz based on reviews by Jean-Olivier Irisson, Sakina-Dorothee Ayata and 1 anonymous reviewerMorand et al. (2024) designed convolutional neural networks to predict the occurrences of 38 marine animals worldwide. The environmental predictors were sea surface temperature, chlorophyll concentration, salinity and fifteen others. The time of some of the predictors was chosen to be as close as possible to the time of the observed occurrence. A very interesting feature of PCI Ecology is that reviews are provided with the final manuscript and the present recommendation text. The main question debated during the review process was whether the CNN modeling approach used here can be defined as a kind of niche modeling. Another interesting point is that the CNN model is used here as a multi-species classifier, meaning that it provides the ranked probability that a given observation corresponds to one of the 38 species considered in the study, depending on the environmental conditions at the location and time of the observation. In other words, the model provides the relative chance of choosing each of the 38 species at a given time and place. Imagine that you are only studying two species that have exactly the same niche, a standard SDM approach should provide a high probability of occurrence close to 1 in localities where environmental conditions are very and equally suited to both species, while the CNN classifier would provide a value close to 0.5 for both species, meaning that we have an equal chance of choosing one or the other. Consequently, the fact that the probability given by the classifier is higher for a species at a given point than at another point does not (necessarily) mean that the first point presents better environmental conditions for that species but rather that we are more likely to choose it over one of the other species at this point than at another. In fact, the classification task also reflects whether the other 37 species are more or less likely to be found at each point. The classifier, therefore, does not provide the relative probability of occurrence of a species in space but rather a relative chance of finding it instead of one of the other 37 species at each point of space and time. Finally, CNN-based species distribution modelling is a powerful and promising tool for studying the distributions of multi-species assemblages as a function of local environmental features but also of the spatial heterogeneity of each feature around the observation point in space and time (Deneu et al. 2021). It allows acknowledging the complex effects of environmental predictors and the roles of their spatial and temporal heterogeneity through the convolution operations performed in the neural network. As more and more computationally intensive tools become available, and as more and more environmental data becomes available at finer and finer temporal and spatial scales, the CNN approach is likely to be increasingly used to study biodiversity patterns across spatial and temporal scales. References Botella, C., Joly, A., Bonnet, P., Monestiez, P., and Munoz, F. (2018). Species distribution modeling based on the automated identification of citizen observations. Applications in Plant Sciences, 6(2), e1029. https://doi.org/10.1002/aps3.1029 Deneu, B., Servajean, M., Bonnet, P., Botella, C., Munoz, F., and Joly, A. (2021). Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. PLoS Computational Biology, 17(4), e1008856. https://doi.org/10.1371/journal.pcbi.1008856 Morand, G., Joly, A., Rouyer, T., Lorieul, T., and Barde, J. (2024) Predicting species distributions in the open ocean with convolutional neural networks. bioRxiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2023.08.11.551418 Ovaskainen, O., Tikhonov, G., Norberg, A., Guillaume Blanchet, F., Duan, L., Dunson, D., ... and Abrego, N. (2017). How to make more out of community data? A conceptual framework and its implementation as models and software. Ecology letters, 20(5), 561-576. https://doi.org/10.1111/ele.12757 | Predicting species distributions in the open ocean with convolutional neural networks | Gaétan Morand, Alexis Joly, Tristan Rouyer, Titouan Lorieul, Julien Barde | <p>As biodiversity plummets due to anthropogenic disturbances, the conservation of oceanic species is made harder by limited knowledge of their distributions and migrations. Indeed, tracking species distributions in the open ocean is particularly ... | Marine ecology, Species distributions | François Munoz | Jean-Olivier Irisson | 2023-08-13 07:25:28 | View | |
12 Jan 2024
Methods for tagging an ectoparasite, the salmon louse Lepeophtheirus salmonisAlexius Folk, Adele Mennerat https://doi.org/10.1101/2023.08.31.555695Marking invertebrates using RFID tagsRecommended by Nicolas Schtickzelle based on reviews by Simon Blanchet and 1 anonymous reviewerGuiding and monitoring the efficiency of conservation efforts needs robust scientific background information, of which one key element is estimating wildlife abundance and its spatial and temporal variation. As raw counts are by nature incomplete counts of a population, correcting for detectability is required (Clobert, 1995; Turlure et al., 2018). This can be done with Capture-Mark-Recapture protocols (Iijima, 2020). Techniques for marking individuals are diverse, e.g. writing on butterfly wings, banding birds, or using natural specific patterns in the individual’s body such as leopard fur or whale tail. Advancement in technology opens new opportunities for developing marking techniques, including strategies to limit mark identification errors (Burchill & Pavlic, 2019), and for using active marks that can transmit data remotely or be read automatically. The details of such methodological developments frequently remain unpublished, the method being briefly described in studies that use it. For a few years, there has been however a renewed interest in proper publishing of methods for ecology and evolution. This study by Folk & Mennerat (2023) fits in this context, offering a nice example of detailed description and testing of a method to mark salmon ectoparasites using RFID tags. Such tags are extremely small, yet easy to use, even with automatic recording procedure. The study provides a very good basis protocol that should help researchers working for small species, in particular invertebrates. The study is complemented by a video illustrating the placement of the tag so the reader who would like to replicate the procedure can get a very precise idea of it. References Burchill, A. T., & Pavlic, T. P. (2019). Dude, where’s my mark? Creating robust animal identification schemes informed by communication theory. Animal Behaviour, 154, 203–208. https://doi.org/10.1016/j.anbehav.2019.05.013 Clobert, J. (1995). Capture-recapture and evolutionary ecology: A difficult wedding ? Journal of Applied Statistics, 22(5–6), 989–1008. Folk, A., & Mennerat, A. (2023). Methods for tagging an ectoparasite, the salmon louse Lepeophtheirus salmonis (p. 2023.08.31.555695). bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.08.31.555695 Iijima, H. (2020). A Review of Wildlife Abundance Estimation Models: Comparison of Models for Correct Application. Mammal Study, 45(3), 177–188. https://doi.org/10.3106/ms2019-0082 Turlure, C., Pe’er, G., Baguette, M., & Schtickzelle, N. (2018). A simplified mark–release–recapture protocol to improve the cost effectiveness of repeated population size quantification. Methods in Ecology and Evolution, 9(3), 645–656. https://doi.org/10.1111/2041-210X.12900 | Methods for tagging an ectoparasite, the salmon louse *Lepeophtheirus salmonis* | Alexius Folk, Adele Mennerat | <p style="text-align: justify;">Monitoring individuals within populations is a cornerstone in evolutionary ecology, yet individual tracking of invertebrates and particularly parasitic organisms remains rare. To address this gap, we describe here a... | Dispersal & Migration, Evolutionary ecology, Host-parasite interactions, Marine ecology, Parasitology, Terrestrial ecology, Zoology | Nicolas Schtickzelle | 2023-09-04 15:25:08 | View |
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