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Latest recommendations
| Id | Title * | Authors * | Abstract * ▲ | Picture * | Thematic fields * | Recommender | Reviewers | Submission date | |
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24 Mar 2023
Rapid literature mapping on the recent use of machine learning for wildlife imageryReview of machine learning uses for the analysis of images on wildlifeRecommended by Olivier Gimenez based on reviews by Falk Huettmann and 1 anonymous reviewerIn the field of ecology, there is a growing interest in machine (including deep) learning for processing and automatizing repetitive analyses on large amounts of images collected from camera traps, drones and smartphones, among others. These analyses include species or individual recognition and classification, counting or tracking individuals, detecting and classifying behavior. By saving countless times of manual work and tapping into massive amounts of data that keep accumulating with technological advances, machine learning is becoming an essential tool for ecologists. We refer to recent papers for more details on machine learning for ecology and evolution (Besson et al. 2022, Borowiec et al. 2022, Christin et al. 2019, Goodwin et al. 2022, Lamba et al. 2019, Nazir & Kaleem 2021, Perry et al. 2022, Picher & Hartig 2023, Tuia et al. 2022, Wäldchen & Mäder 2018). In their paper, Nakagawa et al. (2023) conducted a systematic review of the literature on machine learning for wildlife imagery. Interestingly, the authors used a method unfamiliar to ecologists but well-established in medicine called rapid review, which has the advantage of being quickly completed compared to a fully comprehensive systematic review while being representative (Lagisz et al., 2022). Through a rigorous examination of more than 200 articles, the authors identified trends and gaps, and provided suggestions for future work. Listing all their findings would be counterproductive (you’d better read the paper), and I will focus on a few results that I have found striking, fully assuming a biased reading of the paper. First, Nakagawa et al. (2023) found that most articles used neural networks to analyze images, in general through collaboration with computer scientists. A challenge here is probably to think of teaching computer vision to the generations of ecologists to come (Cole et al. 2023). Second, the images were dominantly collected from camera traps, with an increase in the use of aerial images from drones/aircrafts that raise specific challenges. Third, the species concerned were mostly mammals and birds, suggesting that future applications should aim to mitigate this taxonomic bias, by including, e.g., invertebrate species. Fourth, most papers were written by authors affiliated with three countries (Australia, China, and the USA) while India and African countries provided lots of images, likely an example of scientific colonialism which should be tackled by e.g., capacity building and the involvement of local collaborators. Last, few studies shared their code and data, which obviously impedes reproducibility. Hopefully, with the journals’ policy of mandatory sharing of codes and data, this trend will be reversed. REFERENCES Besson M, Alison J, Bjerge K, Gorochowski TE, Høye TT, Jucker T, Mann HMR, Clements CF (2022) Towards the fully automated monitoring of ecological communities. Ecology Letters, 25, 2753–2775. https://doi.org/10.1111/ele.14123 Borowiec ML, Dikow RB, Frandsen PB, McKeeken A, Valentini G, White AE (2022) Deep learning as a tool for ecology and evolution. Methods in Ecology and Evolution, 13, 1640–1660. https://doi.org/10.1111/2041-210X.13901 Christin S, Hervet É, Lecomte N (2019) Applications for deep learning in ecology. Methods in Ecology and Evolution, 10, 1632–1644. https://doi.org/10.1111/2041-210X.13256 Cole E, Stathatos S, Lütjens B, Sharma T, Kay J, Parham J, Kellenberger B, Beery S (2023) Teaching Computer Vision for Ecology. https://doi.org/10.48550/arXiv.2301.02211 Goodwin M, Halvorsen KT, Jiao L, Knausgård KM, Martin AH, Moyano M, Oomen RA, Rasmussen JH, Sørdalen TK, Thorbjørnsen SH (2022) Unlocking the potential of deep learning for marine ecology: overview, applications, and outlook†. ICES Journal of Marine Science, 79, 319–336. https://doi.org/10.1093/icesjms/fsab255 Lagisz M, Vasilakopoulou K, Bridge C, Santamouris M, Nakagawa S (2022) Rapid systematic reviews for synthesizing research on built environment. Environmental Development, 43, 100730. https://doi.org/10.1016/j.envdev.2022.100730 Lamba A, Cassey P, Segaran RR, Koh LP (2019) Deep learning for environmental conservation. Current Biology, 29, R977–R982. https://doi.org/10.1016/j.cub.2019.08.016 Nakagawa S, Lagisz M, Francis R, Tam J, Li X, Elphinstone A, Jordan N, O’Brien J, Pitcher B, Sluys MV, Sowmya A, Kingsford R (2023) Rapid literature mapping on the recent use of machine learning for wildlife imagery. EcoEvoRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/X2H59D Nazir S, Kaleem M (2021) Advances in image acquisition and processing technologies transforming animal ecological studies. Ecological Informatics, 61, 101212. https://doi.org/10.1016/j.ecoinf.2021.101212 Perry GLW, Seidl R, Bellvé AM, Rammer W (2022) An Outlook for Deep Learning in Ecosystem Science. Ecosystems, 25, 1700–1718. https://doi.org/10.1007/s10021-022-00789-y Pichler M, Hartig F Machine learning and deep learning—A review for ecologists. Methods in Ecology and Evolution, n/a. https://doi.org/10.1111/2041-210X.14061 Tuia D, Kellenberger B, Beery S, Costelloe BR, Zuffi S, Risse B, Mathis A, Mathis MW, van Langevelde F, Burghardt T, Kays R, Klinck H, Wikelski M, Couzin ID, van Horn G, Crofoot MC, Stewart CV, Berger-Wolf T (2022) Perspectives in machine learning for wildlife conservation. Nature Communications, 13, 792. https://doi.org/10.1038/s41467-022-27980-y Wäldchen J, Mäder P (2018) Machine learning for image-based species identification. Methods in Ecology and Evolution, 9, 2216–2225. https://doi.org/10.1111/2041-210X.13075 | Rapid literature mapping on the recent use of machine learning for wildlife imagery | Shinichi Nakagawa, Malgorzata Lagisz, Roxane Francis, Jessica Tam, Xun Li, Andrew Elphinstone, Neil R. Jordan, Justine K. O’Brien, Benjamin J. Pitcher, Monique Van Sluys, Arcot Sowmya, Richard T. Kingsford | <p>1. Machine (especially deep) learning algorithms are changing the way wildlife imagery is processed. They dramatically speed up the time to detect, count, classify animals and their behaviours. Yet, we currently have a very few systematic liter... | | Behaviour & Ethology, Conservation biology | Olivier Gimenez | Anonymous | 2022-10-31 22:05:46 | |
20 Jun 2024
Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitorsWe are better together: Spider mites running away from Cadmium contaminated plants make better decisions collectively than individuallyRecommended by Ruben Heleno based on reviews by 2 anonymous reviewers
Hyperaccumulator plants can concentrate heavy metals present on the soil in their tissues, avoiding their toxic effects and potentially discouraging herbivores (Martens & Boyd, 1994). But not all herbivores are necessarily discouraged, and access to locally abundant resources with low interspecific competition from other herbivores, can affect feeding choices. Godinho et al. performed a series of controlled laboratorial trials to evaluate if herbivores (spider mites) avoid tomato plants with high concentrations of Cadmium under alternative scenarios, namely: the presence/absence of conspecifics, the presence/absence of a competitor species (a congeneric mite), and the relative abundance of contaminated plants. They found that when looking for plants to lay their eggs, individual spider-mites (females) do not seem to discriminate between plants with or without cadmium, despite a significantly lower performance on the former. However, they consistently chose plants without Cadmium in set-ups where 200 mites are faced with this decision together. This preference was consistent and independent from the relative abundance of cadmium-free plants, but only when mites do this decision collectively. In addition, this preference was stronger than that for plants where interspecific competition was lower, with mites preferring to face high competition from congeneric herbivores than laying their eggs on Cadmium contaminated plants. Taken together these experiments suggest that aggregation is a key mechanism by which spider mites can avoid metal contaminated plants. As good research often does, these experiments open several important questions that will need to be addressed in the future. In particular, it will be important to clarify what are the sensorial and behavioural mechanisms that allow this decision/outcome when spider mites make this choice collectively but lead to a different outcome (no choice) when they face this decision alone. Additionally, it will be interesting to explore the potentially adaptive (or non-adaptive) consequences of this behaviour in terms of individual and inclusive fitness. One thing seems certain: both the abiotic and the biotic context can affect spider mite choices, and both need to be considered to advance our understanding about the trade-offs between plant defence mechanisms and associated herbivore decisions and fitness. References Martens, S. N., & Boyd, R. S. (1994). The ecological significance of nickel hyperaccumulation: a plant chemical defense. Oecologia, 98(3–4), 379–384. https://doi.org/10.1007/BF00324227 Godinho, D. P., I. Fragata, M. C. de la Masseliere, S. Magalhaes 2024 Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitors. bioRxiv, ver. 4, peer-reviewed and recommended by PCI Ecology 2023.08.17.553707. https://doi.org/10.1101/2023.08.17.553707
| Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitors | Diogo Prino Godinho, Ines Fragata, Maud Charlery de la Masseliere, Sara Magalhaes | <p>1. Plants can accumulate heavy metals from polluted soils on their shoots and use this to defend themselves against herbivory. One possible strategy for herbivores to cope with the reduction in performance imposed by heavy metal accumulation in... | | Behaviour & Ethology, Competition, Habitat selection, Herbivory | Ruben Heleno | 2023-11-09 11:52:58 | ||
13 May 2024
Getting More by Asking for Less: Linking Species Interactions to Species Co-Distributions in MetacommunitiesBeyond pairwise species interactions: coarser inference of their joined effects is more relevantRecommended by François Munoz based on reviews by Frederik De Laender, Hao Ran Lai and Malyon Bimler
Barbier et al. (2024) investigated the dynamics of species abundances depending on their ecological niche (abiotic component) and on (numerous) competitive interactions. In line with previous evidence and expectations (Barbier et al. 2018), the authors show that it is possible to robustly infer the mean and variance of interaction coefficients from species co-distributions, while it is not possible to infer the individual coefficient values. The authors devised a simulation framework representing multispecies dynamics in an heterogeneous environmental context (2D grid landscape). They used a Lotka-Volterra framework involving pairwise interaction coefficients and species-specific carrying capacities. These capacities depend on how well the species niche matches the local environmental conditions, through a Gaussian function of the distance of the species niche centers to the local environmental values. They considered two contrasted scenarios denoted as « Environmental tracking » and « Dispersal limited ». In the latter case, species are initially seeded over the environmental grid and cannot disperse to other cells, while in the former case they can disperse and possibly be more performant in other cells. The direct effects of species on one another are encoded in an interaction matrix A, and the authors further considered net interactions depending on the inverse of the matrix of direct interactions (Zelnik et al., 2024). The net effects are context-dependent, i.e., it involves the environment-dependent biotic capacities, even through the interaction terms can be defined between species as independent from local environment. The results presented here underline that the outcome of many individual competitive interactions can only be understood in terms of macroscopic properties. In essence, the results here echoe the mean field theories that investigate the dynamics of average ecological properties instead of the microscopic components (e.g., McKane et al. 2000). In a philosophical perspective, community ecology has long struggled with analyzing and inferring local determinants of species coexistence from species co-occurrence patterns, so that it was claimed that no universal laws can be derived in the discipline (Lawton 1999). Using different and complementary methods and perspectives, recent research has also shown that species assembly parameter values cannot be unambiguously inferred from species co-occurrences only, even in simple designs where an equilibrium can be reached (Poggiato et al. 2021). Although the roles of high-order competitive interactions and intransivity can lead to species coexistence, the simple view of a single loop of competitive interactions is easily challenged when further interactions and complexity is added (Gallien et al. 2024). But should we put so much emphasis on inferring individual interaction coefficients? In a quest to understand the emerging properties of elementary processes, ecological theory could go forward with a more macroscopic analysis and understanding of species coexistence in many communities. The authors referred several times to an interesting paper from Schaffer (1981), entitled « Ecological abstraction: the consequences of reduced dimensionality in ecological models ». It proposes that estimating individual species competition coefficients is not possible, but that competition can be assessed at the coarser level of organisation, i.e., between ecological guilds. This idea implies that the dimensionality of the competition equations should be greatly reduced to become tractable in practice. Taking together this claim with the results of the present Barbier et al. (2024) paper, it becomes clearer that the nature of competitive interactions can be addressed through « abstracted » quantities, as those of guilds or the moments of the individual competition coefficients (here the average and the standard deviation). Therefore the scope of Barbier et al. (2024) framework goes beyond statistical issues in parameter inference, but question the way we must think and represent the numerous competitive interactions in a simplified and robust way. References Barbier, Matthieu, Jean-François Arnoldi, Guy Bunin, et Michel Loreau. 2018. « Generic assembly patterns in complex ecological communities ». Proceedings of the National Academy of Sciences 115 (9): 2156‑61. https://doi.org/10.1073/pnas.1710352115 | Getting More by Asking for Less: Linking Species Interactions to Species Co-Distributions in Metacommunities | Matthieu Barbier, Guy Bunin, Mathew A. Leibold | <p>AbstractOne of the more difficult challenges in community ecology is inferring species interactions on the basis of patterns in the spatial distribution of organisms. At its core, the problem is that distributional patterns reflect the ‘realize... | | Biogeography, Community ecology, Competition, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Statistical ecology, Theoretical ecology | François Munoz | 2023-10-21 14:14:16 | ||
18 Dec 2020
Once upon a time in the far south: Influence of local drivers and functional traits on plant invasion in the harsh sub-Antarctic islandsA meaningful application of species distribution models and functional traits to understand invasion dynamicsRecommended by Joaquín Hortal based on reviews by Paula Matos and Peter Convey
Polar and subpolar regions are fragile environments, where the introduction of alien species may completely change ecosystem dynamics if the alien species become keystone species (e.g. Croll, 2005). The increasing number of human visits, together with climate change, are favouring the introduction and settling of new invaders to these regions, particularly in Antarctica (Hughes et al. 2015). Within this context, the joint use of Species Distribution Models (SDM) –to assess the areas potentially suitable for the aliens– with other measures of the potential to become successful invaders can inform on the need for devoting specific efforts to eradicate these new species before they become naturalized (e.g. Pertierra et al. 2016). Bazzichetto et al. (2020) use data from a detailed inventory, SDMs and trait data altogether to assess the drivers of invasion success of six alien plants on Possession Island, in the remote sub-Antarctic archipelago of Crozet. SDMs have inherent limitations to describe different aspects of species distributions, including the fundamental niche and, with it, the areas that could host viable populations (Hortal et al. 2012). Therefore, their utility to predict future biological invasions is limited (Jiménez-Valverde et al. 2011). However, they can be powerful tools to describe species range dynamics if they are thoughtfully used by adopting conscious decisions about the techniques and data used, and interpreting carefully the actual implications of their results. This is what Bazzichetto et al. (2020) do, using General Linear Models (GLM) –a technique well rooted in the original niche-based SDM theory (e.g. Austin 1990)– that can provide a meaningful description of the realized niche within the limits of an adequately sampled region. Further, as alien species share and are similarly affected by several steps of the invasion process (Richardson et al. 2000), these authors model the realized distribution of the six species altogether. This can be done through the recently developed joint-SDM, a group of techniques where the co-occurrence of the modelled species is explicitly taken into account during modelling (e.g. Pollock et al. 2014). Here, the addition of species traits has been identified as a key step to understand the associations of species in space (see Dormann et al. 2018). Bazzichetto et al. (2020) combine their GLM-based SDM for each species with a so-called multi-SDM approach, where they assess together the consistency in the interactions between both species and topographically-driven climate variations, and several plant traits and two key anthropic factors –accessibility from human settlements and distance to hiking paths. This work is a good example on how a theoretically meaningful SDM approach can provide useful –though perhaps not deep– insights on biological invasions for remote landscapes threatened by biotic homogenization. By combining climate and topographic variables as proxies for the spatial variations in the abiotic conditions regulating plant growth, measures of accessibility, and traits of the plant invaders, Bazzichetto et al. (2020) are able to identify the different effects that the interactions between the potential intensity of propagule dissemination by humans, and the ecological characteristics of the invaders themselves, may have on their invasion success. The innovation of modelling together species responses is important because it allows dissecting the spatial dynamics of spread of the invaders, which indeed vary according to a handful of their traits. For example, their results show that no all old residents have profited from the larger time of residence in the island, as Poa pratensis is seemingly as dependent of a higher intensity of human activity as the newcomer invaders in general are. According to Bazzichetto et al. trait-based analyses, these differences are apparently related with plant height, as smaller plants disperse more easily. Further, being perennial also provides an advantage for the persistence in areas with less human influence. This puts name, shame and fame to the known influence of plant life history on their dispersal success (Beckman et al. 2018), at least for the particular case of plant invasions in Possession Island. Of course this approach has limitations, as data on the texture, chemistry and temperature of the soil are not available, and thus were not considered in the analyses. These factors may be critical for both establishment and persistence of small plants in the harsh Antarctic environments, as Bazzichetto et al. (2020) recognize. But all in all, their results provide key insights on which traits may confer alien plants with a higher likelihood of becoming successful invaders in the fragile Antarctic and sub-Antarctic ecosystems. This opens a way for rapid assessments of invasibility, which will help identifying which species in the process of naturalizing may require active contention measures to prevent them from becoming ecological game changers and cause disastrous cascade effects that shift the dynamics of native ecosystems. **References** Austin, M. P., Nicholls, A. O., and Margules, C. R. (1990). Measurement of the realized qualitative niche: environmental niches of five Eucalyptus species. Ecological Monographs, 60(2), 161-177. doi: [https://doi.org/10.2307/1943043](https://doi.org/10.2307/1943043) Bazzichetto, M., Massol, F., Carboni, M., Lenoir, J., Lembrechts, J. J. and Joly, R. (2020) Once upon a time in the far south: Influence of local drivers and functional traits on plant invasion in the harsh sub-Antarctic islands. bioRxiv, 2020.07.19.210880, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: [https://doi.org/10.1101/2020.07.19.210880](https://doi.org/10.1101/2020.07.19.210880) Beckman, N. G., Bullock, J. M., and Salguero-Gómez, R. (2018). High dispersal ability is related to fast life-history strategies. Journal of Ecology, 106(4), 1349-1362. doi: [https://doi.org/10.1111/1365-2745.12989](https://doi.org/10.1111/1365-2745.12989) Croll, D. A., Maron, J. L., Estes, J. A., Danner, E. M., and Byrd, G. V. (2005). Introduced predators transform subarctic islands from grassland to tundra. Science, 307(5717), 1959-1961. doi: [https://doi.org/10.1126/science.1108485](https://doi.org/10.1126/science.1108485) Dormann, C. F., Bobrowski, M., Dehling, D. M., Harris, D. J., Hartig, F., Lischke, H., Moretti, M. D., Pagel, J., Pinkert, S., Schleuning, M., Schmidt, S. I., Sheppard, C. S., Steinbauer, M. J., Zeuss, D., and Kraan, C. (2018). Biotic interactions in species distribution modelling: 10 questions to guide interpretation and avoid false conclusions. Global Ecology and Biogeography, 27(9), 1004-1016. doi: [https://doi.org/10.1111/geb.12759](https://doi.org/10.1111/geb.12759) Jiménez-Valverde, A., Peterson, A., Soberón, J., Overton, J., Aragón, P., and Lobo, J. (2011). Use of niche models in invasive species risk assessments. Biological Invasions, 13(12), 2785-2797. doi: [https://doi.org/10.1007/s10530-011-9963-4](https://doi.org/10.1007/s10530-011-9963-4) Hortal, J., Lobo, J. M., and Jiménez-Valverde, A. (2012). Basic questions in biogeography and the (lack of) simplicity of species distributions: Putting species distribution models in the right place. Natureza & Conservação – Brazilian Journal of Nature Conservation, 10(2), 108-118. doi: [https://doi.org/10.4322/natcon.2012.029](https://doi.org/10.4322/natcon.2012.029) Hughes, K. A., Pertierra, L. R., Molina-Montenegro, M. A., and Convey, P. (2015). Biological invasions in terrestrial Antarctica: what is the current status and can we respond? Biodiversity and Conservation, 24(5), 1031-1055. doi: [https://doi.org/10.1007/s10531-015-0896-6](https://doi.org/10.1007/s10531-015-0896-6) Pertierra, L. R., Baker, M., Howard, C., Vega, G. C., Olalla-Tarraga, M. A., and Scott, J. (2016). Assessing the invasive risk of two non-native Agrostis species on sub-Antarctic Macquarie Island. Polar Biology, 39(12), 2361-2371. doi: [https://doi.org/10.1007/s00300-016-1912-3](https://doi.org/10.1007/s00300-016-1912-3) Pollock, L. J., Tingley, R., Morris, W. K., Golding, N., O'Hara, R. B., Parris, K. M., Vesk, P. A., and McCarthy, M. A. (2014). Understanding co-occurrence by modelling species simultaneously with a Joint Species Distribution Model (JSDM). Methods in Ecology and Evolution, 5(5), 397-406. doi: [https://doi.org/10.1111/2041-210X.12180](https://doi.org/10.1111/2041-210X.12180) Richardson, D. M., Pyšek, P., Rejmánek, M., Barbour, M. G., Panetta, F. D., and West, C. J. (2000). Naturalization and invasion of alien plants: concepts and definitions. Diversity and Distributions, 6(2), 93-107. doi: [https://doi.org/10.1046/j.1472-4642.2000.00083.x](https://doi.org/10.1046/j.1472-4642.2000.00083.x) | Once upon a time in the far south: Influence of local drivers and functional traits on plant invasion in the harsh sub-Antarctic islands | Manuele Bazzichetto, François Massol, Marta Carboni, Jonathan Lenoir, Jonas Johan Lembrechts, Rémi Joly, David Renault | <p>Aim Here, we aim to: (i) investigate the local effect of environmental and human-related factors on alien plant invasion in sub-Antarctic islands; (ii) explore the relationship between alien species features and their dependence on anthropogeni... | | Biogeography, Biological invasions, Spatial ecology, Metacommunities & Metapopulations, Species distributions | Joaquín Hortal | 2020-07-21 21:13:08 | ||
16 May 2025
Is the audience gender-blind? Smaller attendance in female talks highlights imbalanced visibility in academiaGender matters: smaller audiences for women in academiaRecommended by Natalia Mariel Schroeder based on reviews by Silvia Beatriz Lomascolo and Letícia dos Anjos
The current lack of social diversity - that is, gender, race and ethnicity - in academia reinforces a historical pattern of exclusion, wherein the knowledge, perspectives and advances of certain groups dominate the narrative, set rhythms and agenda, while the contributions of others are minimised or overlooked. The underrepresentation of and discrimination against women in academia is a well-documented and persistent issue. Despite policies designed to increase female representation and mitigate the structural processes that lead women to abandon their academic careers (Shaw & Stanton, 2012), women scientists continue to face inequalities in authorship, publications, funding, salaries, recognition and decision-making spaces (Astegiano et al., 2019, Woolston, 2019; Fox et a. 2023; Fontanarrosa et al. 2024; Zandonà, 2022; among others). Making these inequalities visible and fostering open discussion is a critical first step toward dismantling them. In this sense, the study by Rodrigues Barreto et al. (2025) makes an important contribution. The authors examine gender bias in seminar series within the field of Ecology, Evolution and Conservation Biology at the University of São Paulo (Brazil), using audience size as an indirect measure of speaker recognition. The most interesting and novel finding of this work is that talks given by women -especially by female professors- attract smaller audiences than those given by men counterparts, despite the women having comparable levels of academic productivity, similar career trajectories, and presenting on equivalent topics to those of their male colleagues. These results suggest that seminar culture is not gender-blind (Dupas et al., 2021) and provide a new layer of evidence on how gender-based stereotypes continue to influence the visibility and recognition of women in science. The authors also investigated whether the implementation of affirmative actions (i.e., open calls for volunteer speakers that prioritised women) improved both the representation of female speakers and the size of their audiences. As expected, these actions did succeed in increasing the representation of women among presenters, especially at senior academic levels; however, they did not lead to a proportional rise in audience size. While the time series and number of talks considered before the implementation of affirmative actions were considerably higher than those after this policy, the comparison remains relevant given the importance and timeliness of the topic. The authors found that women give fewer talks than men. However, as they discuss, their results do not allow them to distinguish whether this inequality is due to gender bias or to a structural gender imbalance. Through a supplementary analysis of a subset of data from the University of São Paulo community, they find some evidence that the underrepresentation of women in the academic population itself may partly explain the gender gap in the seminar series. In any case, these findings, along with similar results from other studies (e.g. Greska, 2023) raise valuable questions: Will simply increasing the number of women in academia be enough to close the recognition gap between men and women scholars? What role might affirmative actions play in attracting a wider audience or enhancing the visibility and recognition of women's work? What kinds of initiatives could change the way we acknowledge women researchers’ contributions? What could reconfigure that “recognition landscape” from a feminist perspective, i.e., one less competitive, less hierarchical, more communitarian and less individual-centered? As the authors acknowledge, the study has limitations (e.g., its focus on a single institution, a short timeframe to assess the impact of affirmative actions), but it provides valuable evidence to initiate broader approaches that include other disciplines, institutions, experimental approaches, and intersectional perspectives. References Astegiano J, Sebastián-González E, Castanho C de T (2019) Unravelling the gender 465 productivity gap in science: a meta-analytical review. Royal Society Open Science 6: 466 181566. https://doi.org/10.1098/rsos.181566 Dupas P, Modestino AS, Niederle M, Wolfers J, Collective TSD (2021) Gender and the Dynamics of Economics Seminars. Cambridge, MA: National Bureau of Economic Research. http://www.nber.org/papers/w28494.pdf Fontanarrosa, G., Zarbá, L., Aschero, V., Dos Santos, D. A., Montellano, M. G. N. et al. (2024). Over twenty years of publications in Ecology: Over-contribution of women reveals a new dimension of gender bias. PLoS ONE 19(9): e0307813. https://doi.org/10.1371/journal.pone.0307813 Fox CW, Meyer J, Aimé E (2023) Double-blind peer review affects reviewer ratings and 509 editor decisions at an ecology journal. Functional Ecology 37: 1144–1157. https://doi.org/10.1111/1365-2435.14259 Greska L (2023) Women in Academia: Why and where does the pipeline leak, and how can we fix it? MIT Science Policy Review 4: 102–109. https://doi.org/10.38105/spr.xmvdiojee1 Rodrigues Barreto J, Romitelli I, Santana PC, Aprígio Assis A.N., Pardini R, de Souza Leite M. (2025) Is the audience gender-blind? Smaller attendance in female talks highlights imbalanced visibility in academia. EcoEvoRxiv, ver.4 peer-reviewed and recommended by PCI Ecology https://doi.org/10.32942/X25607 Shaw AK, Stanton DE (2012) Leaks in the pipeline: separating demographic inertia from ongoing gender differences in academia. Proceedings of the Royal Society B: Biological Sciences 279: 3736–3741. https://doi.org/10.1098/rspb.2012.0822 Woolston C (2019) Scientists’ salary data highlight US$18,000 gender pay gap. Nature 565: 597 527–527. https://doi.org/10.1038/d41586-019-00220-y Zandonà E (2022) Female ecologists are falling from the academic ladder: A call for action. 602 Perspectives in Ecology and Conservation 20: 294–299. https://doi.org/10.1016/j.pecon.2022.04.001 | Is the audience gender-blind? Smaller attendance in female talks highlights imbalanced visibility in academia | Júlia Rodrigues Barreto, Isabella Romitelli, Pamela Cristina Santana, Ana Paula Aprígio Assis, Renata Pardini, Melina de Souza Leite | <p>Although diverse perspectives are fundamental for fostering and advancing science, power relations have limited the development, propagation of ideas, and recognition of political minority groups in academia. Gender bias is one of the most well... | | Biodiversity, Conservation biology, Evolutionary ecology, Tropical ecology | Natalia Mariel Schroeder | 2024-05-30 23:00:46 | ||
06 Sep 2019
Assessing metacommunity processes through signatures in spatiotemporal turnover of community compositionOn the importance of temporal meta-community dynamics for our understanding of assembly processesRecommended by Werner Ulrich based on reviews by Joaquín Hortal and 2 anonymous reviewers
The processes that trigger community assembly are still in the centre of ecological interest. While prior work mostly focused on spatial patterns of co-occurrence within a meta-community framework [reviewed in 1, 2] recent studies also include temporal patterns of community composition [e.g. 3, 4, 5, 6]. In this preprint [7], Franck Jabot and co-workers extend they prior approaches to quasi neutral community assembly [8, 9, 10] and develop an analytical framework of spatial and temporal diversity turnover. A simple and heuristic path model for beta diversity and an extended ecological drift model serve as starting points. The model can be seen as a counterpart to Ulrich et al. [5]. These authors implemented competitive hierarchies into their neutral meta-community model while the present paper focuses on environmental filtering. Most important, the model and parameterization of four empirical data sets on aquatic plant and animal meta-communities used by Jabot et al. returned a consistent high influence of environmental stochasticity on species turnover. Of course, this major result does not come to a surprise. As typical for this kind of models it depends also to a good deal on the initial model settings. It nevertheless makes a strong conceptual point for the importance of environmental variability over dispersal and richness effects. One interesting side effect regards the impact of richness differences (ΔS). Jabot et al. interpret this as a ‘nuisance variable’ as they do not have a stringent explanation. Of course, it might be a pure statistical bias introduced by the Soerensen metric of turnover that is normalized by richness. However, I suspect that there is more behind the ΔS effect. Richness differences are generally associated with respective differences in total abundances and introduce source – sink dynamics that inevitably shape subsequent colonization – extinction processes. It would be interesting to see whether ΔS alone is able to trigger observed patterns of community assembly and community composition. Such an analysis would require partitioning of species turnover into richness and nestedness effects [11]. I encourage Jabot et al. to undertake such an effort. References [1] Götzenberger, L. et al. (2012). Ecological assembly rules in plant communities—approaches, patterns and prospects. Biological reviews, 87(1), 111-127. doi: 10.1111/j.1469-185X.2011.00187.x | Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition | Franck Jabot, Fabien Laroche, Francois Massol, Florent Arthaud, Julie Crabot, Maxime Dubart, Simon Blanchet, Francois Munoz, Patrice David, Thibault Datry | <p>Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and still consists mostly of r... | | Biodiversity, Coexistence, Community ecology, Spatial ecology, Metacommunities & Metapopulations | Werner Ulrich | 2018-11-29 14:58:54 | ||
03 Mar 2022
Artificial reefs geographical location matters more than its age and depth for sessile invertebrate colonization in the Gulf of Lion (NorthWestern Mediterranean Sea)A longer-term view on benthic communities on artificial reefs: it’s all about locationRecommended by James Davis Reimer based on reviews by 2 anonymous reviewersIn this study by Blouet, Bramanti, and Guizen (2022), the authors aim to tackle a long-standing data gap regarding research on marine benthic communities found on artificial reefs. The study is well thought out, and should serve as an important reference on this topic going forward. Blouet S, Bramanti L, Guizien K (2022) Artificial reefs geographical location matters more than shape, age and depth for sessile invertebrate colonization in the Gulf of Lion (NorthWestern Mediterranean Sea). bioRxiv, 2021.10.08.463669, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2021.10.08.463669 | Artificial reefs geographical location matters more than its age and depth for sessile invertebrate colonization in the Gulf of Lion (NorthWestern Mediterranean Sea) | sylvain blouet, Katell Guizien, lorenzo Bramanti | <p>Artificial reefs (ARs) have been used to support fishing activities. Sessile invertebrates are essential components of trophic networks within ARs, supporting fish productivity. However, colonization by sessile invertebrates is possible only af... | | Biodiversity, Biogeography, Colonization, Ecological successions, Life history, Marine ecology | James Davis Reimer | 2021-10-11 10:21:36 | ||
18 Sep 2024
Predicting species distributions in the open ocean with convolutional neural networksThe 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 reviewer
Morand 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 | |
12 Jun 2019
Environmental heterogeneity drives tsetse fly population dynamics and controlModeling 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 | ||
17 Mar 2021
Intra and inter-annual climatic conditions have stronger effect than grazing intensity on root growth of permanent grasslandsResolving herbivore influences under climate variabilityRecommended by Jennifer Krumins based on reviews by 3 anonymous reviewersWe know that herbivory can have profound influences on plant communities with respect to their distribution and productivity (recently reviewed by Jia et al. 2018). However, the degree to which these effects are realized belowground in the rhizosphere is far less understood. Indeed, many independent studies and synthesis find that the environmental context can be more important than the direct effects of herbivore activity and its removal of plant biomass (Andriuzzi and Wall 2017, Schrama et al. 2013). In spite of dedicated attention, generalizable conclusions remain a bit elusive (Sitters and Venterink 2015). Picon-Cochard and colleagues (2021) help address this research conundrum in an elegant analysis that demonstrates the interaction between long-term cattle grazing and climatic variability on primary production aboveground and belowground. Over the course of two years, Picon-Cochard et al. (2021) measured above and belowground net primary productivity in French grasslands that had been subject to ten years of managed cattle grazing. When they compared these data with climatic trends, they find an interesting interaction among grazing intensity and climatic factors influencing plant growth. In short, and as expected, plants allocate more resources to root growth in dry years and more to above ground biomass in wet and cooler years. However, this study reveals the degree to which this is affected by cattle grazing. Grazed grasslands support warmer and dryer soils creating feedback that further and significantly promotes root growth over green biomass production. The implications of this work to understanding the capacity of grassland soils to store carbon is profound. This study addresses one brief moment in time of the long trajectory of this grazed ecosystem. The legacy of grazing does not appear to influence soil ecosystem functioning with respect to root growth except within the environmental context, in this case, climate. This supports the notion that long-term research in animal husbandry and grazing effects on landscapes is deeded. It is my hope that this study is one of many that can be used to synthesize many different data sets and build a deeper understanding of the long-term effects of grazing and herd management within the context of a changing climate. Herbivory has a profound influence upon ecosystem health and the distribution of plant communities (Speed and Austrheim 2017), global carbon storage (Chen and Frank 2020) and nutrient cycling (Sitters et al. 2020). The analysis and results presented by Picon-Cochard (2021) help to resolve the mechanisms that underly these complex effects and ultimately make projections for the future. References Andriuzzi WS, Wall DH. 2017. Responses of belowground communities to large aboveground herbivores: Meta‐analysis reveals biome‐dependent patterns and critical research gaps. Global Change Biology 23:3857-3868. doi: https://doi.org/10.1111/gcb.13675 Chen J, Frank DA. 2020. Herbivores stimulate respiration from labile and recalcitrant soil carbon pools in grasslands of Yellowstone National Park. Land Degradation & Development 31:2620-2634. doi: https://doi.org/10.1002/ldr.3656 Jia S, Wang X, Yuan Z, Lin F, Ye J, Hao Z, Luskin MS. 2018. Global signal of top-down control of terrestrial plant communities by herbivores. Proceedings of the National Academy of Sciences 115:6237-6242. doi: https://doi.org/10.1073/pnas.1707984115 Picon-Cochard C, Vassal N, Martin R, Herfurth D, Note P, Louault F. 2021. Intra and inter-annual climatic conditions have stronger effect than grazing intensity on root growth of permanent grasslands. bioRxiv, 2020.08.23.263137, version 6 peer-reviewed and recommended by PCI Ecology. doi: https://doi.org/10.1101/2020.08.23.263137 Schrama M, Veen GC, Bakker EL, Ruifrok JL, Bakker JP, Olff H. 2013. An integrated perspective to explain nitrogen mineralization in grazed ecosystems. Perspectives in Plant Ecology, Evolution and Systematics 15:32-44. doi: https://doi.org/10.1016/j.ppees.2012.12.001 Sitters J, Venterink HO. 2015. The need for a novel integrative theory on feedbacks between herbivores, plants and soil nutrient cycling. Plant and Soil 396:421-426. doi: https://doi.org/10.1007/s11104-015-2679-y Sitters J, Wubs EJ, Bakker ES, Crowther TW, Adler PB, Bagchi S, Bakker JD, Biederman L, Borer ET, Cleland EE. 2020. Nutrient availability controls the impact of mammalian herbivores on soil carbon and nitrogen pools in grasslands. Global Change Biology 26:2060-2071. doi: https://doi.org/10.1111/gcb.15023 Speed JD, Austrheim G. 2017. The importance of herbivore density and management as determinants of the distribution of rare plant species. Biological Conservation 205:77-84. doi: https://doi.org/10.1016/j.biocon.2016.11.030 | Intra and inter-annual climatic conditions have stronger effect than grazing intensity on root growth of permanent grasslands | Catherine Picon-Cochard, Nathalie Vassal, Raphaël Martin, Damien Herfurth, Priscilla Note, Frédérique Louault | <p>Background and Aims: Understanding how direct and indirect changes in climatic conditions, management, and species composition affect root production and root traits is of prime importance for the delivery of carbon sequestration services of gr... | | Agroecology, Biodiversity, Botany, Community ecology, Ecosystem functioning | Jennifer Krumins | 2020-08-30 19:27:30 |
