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24 Mar 2023
![]() Rapid literature mapping on the recent use of machine learning for wildlife imageryShinichi 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 https://doi.org/10.32942/X2H59DReview 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 | View |
05 Apr 2019
![]() Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas at conserving North-American breeding birdsVictor Cazalis, Soumaya Belghali, Ana S.L. Rodrigues https://doi.org/10.1101/433037Protected Areas effects on biodiversity: a test using bird data that hopefully will give ideas for much more studies to comeRecommended by Paul Caplat based on reviews by Willson Gaul and 1 anonymous reviewerIn the face of worldwide declines in biodiversity, evaluating the effectiveness of conservation practices is an absolute necessity. Protected Areas (PA) are a key tool for conservation, and the question “Are PA effective” has been on many a research agenda, as the introduction to this preprint will no doubt convince you. A challenge we face is that, until now, few studies have been explicitly designed to evaluate PA, and despite the rise of meta-analyses on the topic, our capacity to quantify their effect on biodiversity remains limited. References [1] Cazalis, V., Belghali, S., & Rodrigues, A. S. (2019). Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas at conserving North-American breeding birds. bioRxiv, 433037, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/433037 | Using a large-scale biodiversity monitoring dataset to test the effectiveness of protected areas at conserving North-American breeding birds | Victor Cazalis, Soumaya Belghali, Ana S.L. Rodrigues | <p>Protected areas currently cover about 15% of the global land area, and constitute one of the main tools in biodiversity conservation. Quantifying their effectiveness at protecting species from local decline or extinction involves comparing prot... | ![]() | Biodiversity, Conservation biology, Human impact, Landscape ecology, Macroecology | Paul Caplat | 2018-10-04 08:43:34 | View | |
29 May 2023
![]() Using integrated multispecies occupancy models to map co-occurrence between bottlenose dolphins and fisheries in the Gulf of Lion, French Mediterranean SeaValentin Lauret, Hélène Labach, Léa David, Matthieu Authier, Olivier Gimenez https://doi.org/10.32942/osf.io/npd6uMapping co-occurence of human activities and wildlife from multiple data sourcesRecommended by Paul Caplat based on reviews by Mason Fidino and 1 anonymous reviewerTwo fields of research have grown considerably over the past twenty years: the investigation of human-wildlife conflicts (e.g. see Treves & Santiago-Ávila 2020), and multispecies occupancy modelling (Devarajan et al. 2020). In their recent study, Lauret et al. (2023) combined both in an elegant methodological framework, applied to the study of the co-occurrence of fishing activities and bottlenose dolphins in the French Mediterranean. A common issue with human-wildlife conflicts (and, in particular, fishery by-catch) is that data is often only available from those conflicts or interactions, limiting the validity of the predictions (Kuiper et al. 2022). Lauret et al. use independent data sources informing the occurrence of fishing vessels and dolphins, combined in a Bayesian multispecies occupancy model where vessels are "the other species". I particularly enjoyed that approach, as integration of human activities in ecological models can be extremely complex, but can also translate in phenomena that can be captured as one would of individuals of a species, as long as the assumptions are made clearly. Here, the model is made more interesting by accounting for environmental factors (seabed depth) borrowing an approach from Generalized Additive Models in the Bayesian framework. While not pretending to provide (yet) practical recommendations to help conserve bottlenose dolphins (and other wildlife conflicts), this study and the associated code are a promising step in that direction. REFERENCES Devarajan, K., Morelli, T.L. & Tenan, S. (2020), Multi-species occupancy models: review, roadmap, and recommendations. Ecography, 43: 1612-1624. https://doi.org/10.1111/ecog.04957 Kuiper, T., Loveridge, A.J. and Macdonald, D.W. (2022), Robust mapping of human–wildlife conflict: controlling for livestock distribution in carnivore depredation models. Anim. Conserv., 25: 195-207. https://doi.org/10.1111/acv.12730 Lauret V, Labach H, David L, Authier M, & Gimenez O (2023) Using integrated multispecies occupancy models to map co-occurrence between bottlenose dolphins and fisheries in the Gulf of Lion, French Mediterranean Sea. Ecoevoarxiv, ver. 2 peer-reviewed and recommended by PCI Ecology. https://doi.org/10.32942/osf.io/npd6u Treves, A. & Santiago-Ávila, F.J. (2020). Myths and assumptions about human-wildlife conflict and coexistence. Conserv. Biol. 34, 811–818. https://doi.org/10.1111/cobi.13472 | Using integrated multispecies occupancy models to map co-occurrence between bottlenose dolphins and fisheries in the Gulf of Lion, French Mediterranean Sea | Valentin Lauret, Hélène Labach, Léa David, Matthieu Authier, Olivier Gimenez | <p style="text-align: justify;">In the Mediterranean Sea, interactions between marine species and human activities are prevalent. The coastal distribution of bottlenose dolphins (<em>Tursiops truncatus</em>) and the predation pressure they put on ... | ![]() | Marine ecology, Population ecology, Species distributions | Paul Caplat | 2022-10-21 11:13:36 | View | |
15 Feb 2024
![]() Sources of confusion in global biodiversity trendsMaelys Boennec, Vasilis Dakos, Vincent Devictor https://doi.org/10.32942/X29W3HUnraveling the Complexity of Global Biodiversity Dynamics: Insights and ImperativesRecommended by Paulo BorgesBiodiversity loss is occurring at an alarming rate across terrestrial and marine ecosystems, driven by various processes that degrade habitats and threaten species with extinction. Despite the urgency of this issue, empirical studies present a mixed picture, with some indicating declining trends while others show more complex patterns. In a recent effort to better understand global biodiversity dynamics, Boennec et al. (2024) conducted a comprehensive literature review examining temporal trends in biodiversity. Their analysis reveals that reviews and meta-analyses, coupled with the use of global indicators, tend to report declining trends more frequently. Additionally, the study underscores a critical gap in research: the scarcity of investigations into the combined impact of multiple pressures on biodiversity at a global scale. This lack of understanding complicates efforts to identify the root causes of biodiversity changes and develop effective conservation strategies. This study serves as a crucial reminder of the pressing need for long-term biodiversity monitoring and large-scale conservation studies. By filling these gaps in knowledge, researchers can provide policymakers and conservation practitioners with the insights necessary to mitigate biodiversity loss and safeguard ecosystems for future generations. References Boennec, M., Dakos, V. & Devictor, V. (2023). Sources of confusion in global biodiversity trend. bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/X29W3H
| Sources of confusion in global biodiversity trends | Maelys Boennec, Vasilis Dakos, Vincent Devictor | <p>Populations and ecological communities are changing worldwide, and empirical studies exhibit a mixture of either declining or mixed trends. Confusion in global biodiversity trends thus remains while assessing such changes is of major social, po... | ![]() | Biodiversity, Conservation biology, Meta-analyses | Paulo Borges | 2023-09-20 11:10:25 | View | |
01 Jun 2018
![]() Data-based, synthesis-driven: setting the agenda for computational ecologyTimothée Poisot, Richard Labrie, Erin Larson, Anastasia Rahlin https://doi.org/10.1101/150128Some thoughts on computational ecology from people who I’m sure use different passwords for each of their accountsRecommended by Phillip P.A. Staniczenko based on reviews by Matthieu Barbier and 1 anonymous reviewerAre you an ecologist who uses a computer or know someone that does? Even if your research doesn’t rely heavily on advanced computational techniques, it likely hasn’t escaped your attention that computers are increasingly being used to analyse field data and make predictions about the consequences of environmental change. So before artificial intelligence and robots take over from scientists, now is great time to read about how experts think computers could make your life easier and lead to innovations in ecological research. In “Data-based, synthesis-driven: setting the agenda for computational ecology”, Poisot and colleagues [1] provide a brief history of computational ecology and offer their thoughts on how computational thinking can help to bridge different types of ecological knowledge. In this wide-ranging article, the authors share practical strategies for realising three main goals: (i) tighter integration of data and models to make predictions that motivate action by practitioners and policy-makers; (ii) closer interaction between data-collectors and data-users; and (iii) enthusiasm and aptitude for computational techniques in future generations of ecologists. The key, Poisot and colleagues argue, is for ecologists to “engage in meaningful dialogue across disciplines, and recognize the currencies of their collaborations.” Yes, this is easier said than done. However, the journey is much easier with a guide and when everyone involved serves to benefit not only from the eventual outcome, but also the process. References [1] Poisot, T., Labrie, R., Larson, E., & Rahlin, A. (2018). Data-based, synthesis-driven: setting the agenda for computational ecology. BioRxiv, 150128, ver. 4 recommended and peer-reviewed by PCI Ecology. doi: 10.1101/150128 | Data-based, synthesis-driven: setting the agenda for computational ecology | Timothée Poisot, Richard Labrie, Erin Larson, Anastasia Rahlin | <p>Computational ecology, defined as the application of computational thinking to ecological problems, has the potential to transform the way ecologists think about the integration of data and models. As the practice is gaining prominence as a way... | ![]() | Meta-analyses, Statistical ecology, Theoretical ecology | Phillip P.A. Staniczenko | 2018-02-05 20:51:41 | 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 | |
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 | |
11 Mar 2022
![]() Comment on “Information arms race explains plant-herbivore chemical communication in ecological communities”Ethan Bass, André Kessler https://doi.org/10.32942/osf.io/xsbtmDoes information theory inform chemical arms race communication?Recommended by Rodrigo Medel based on reviews by Claudio Ramirez and 2 anonymous reviewersOne of the long-standing questions in evolutionary ecology is on the mechanisms involved in arms race coevolution. One way to address this question is to understand the conditions under which one species evolves traits in response to the presence of a second species and so on. However, specialized pairwise interactions are by far less common in nature than interactions involving a higher number of interacting species (Bascompte, Jordano 2013). While interactions between large sets of species are the norm rather than the exception in mutualistic (pollination, seed dispersal), and antagonist (herbivory, parasitism) relationships, few is known on the way species identify, process, and respond to information provided by other interacting species under field conditions (Schaefer, Ruxton 2011). Zu et al. (2020) addressed this general question by developing an interesting information theory-based approach that hypothesized conditional entropy in chemical communication plays a role as proxy of fitness in plant-herbivore communities. More specifically, plant fitness was assumed to be related to the efficiency to code signals by plant species, and herbivore fitness to the capacity to decode plant signals. In this way, from the plant perspective, the elaboration of plant signals that elude decoding by herbivores is expected to be favored, as herbivores are expected to attack plants with simple chemical signals. The empirical observation upon which the model was tested was the redundancy in volatile organic compounds (VOC) found across plant species in a plant-herbivore community. Interestingly, Zu et al.’s model predicted successfully that VOC redundancy in the plant community associates with increased conditional entropy, which conveys herbivore confusion and plant protection against herbivory. In this way, plant species that evolve VOCs already present in the community might be benefitted, ultimately leading to the patterns of VOC redundancy commonly observed in nature. Bass & Kessler performed a series of interesting observations on Zu et al. (2020), that can be organized along three lines of reasoning. First, from an evolutionary perspective, Bass & Kessler note the important point that accepting that conditional information entropy, estimated from the contribution of every plant species to volatile redundancy implies that average plant fitness seems to depend on community-level properties (i.e., what the other species in the community are doing) rather than on population-level characteristics (I.e., what the individuals belonging a population are doing). While the level at which selection acts upon is a longstanding debate (e.g., Goodnight, 1990; Williams, 1992), the model seems to contradict one of the basic tenets of Darwinian evolution. The extent to which this important observation invalidates the contribution of Zu et al. (2020) is open to scrutiny. However, one can indulge the evolutionary criticism by arguing that every theoretical model performs a number of assumptions to preserve the simplicity of analyses. Furthermore, even accepting the criticism, the overall information-based framework is valuable as it provides a fresh perspective to the way coding and decoding chemical information in plant-herbivore interactions may result in arm race coevolution. The question to be assessed by members of the scientific community is how strong the evolutionary assumptions are to be acceptable. A second line of reasoning involves consideration of additional routes of chemical information transfer. If chemical volatiles are involved in another ecological function unrelated to arm race (as they are) such as toxicity, crypsis, aposematism, etc., the conditional information indices considered as proxy to plant and herbivore fitness may be only secondarily related to arms race. This is an interesting observation, which suggests that VOC production may have more than one ecological function, as it often happens in “pleiotropic” traits (Strauss, Irwin 2004). This is an exciting avenue for future research. Finally, a third category of comments involves the relationship between conditional information entropy and plant and herbivore fitness. Bass & Kessler developed a Bayesian treatment of the community-level information developed by Zu et al. (2020) that permitted to estimate fitness on a species rather than community level. Their results revealed that community conditional entropies fail to align with species-level indices, suggesting that conclusions of Strauss & Irwin (2004) are not commensurate with fitness at the species level, where the analysis seems to be pertinent. In general, I strongly recommend Bass & Kessler’s contribution as it provides a series of observations and new perspectives to Zu et al. (2020). Rather than restricting their manuscript to blind criticisms, Bass & Kessler provides new interesting perspectives, which is always welcome as it improves the value and scope of the original work. References Bascompte J, Jordano P (2013) Mutualistic Networks. Princeton University Press. https://doi.org/10.23943/princeton/9780691131269.001.0001 Bass E, Kessler A (2022) Comment on “Information arms race explains plant-herbivore chemical communication in ecological communities.” EcoEvoRxiv, ver. 8 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/osf.io/xsbtm Goodnight CJ (1990) Experimental Studies of Community Evolution I: The Response to Selection at the Community Level. Evolution, 44, 1614–1624. https://doi.org/10.1111/j.1558-5646.1990.tb03850.x Schaefer HM, Ruxton GD (2011) Plant-Animal Communication. Oxford University Press, Oxford. https://doi.org/10.1093/acprof:osobl/9780199563609.001.0001 Strauss SY, Irwin RE (2004) Ecological and Evolutionary Consequences of Multispecies Plant-Animal Interactions. Annual Review of Ecology, Evolution, and Systematics, 35, 435–466. https://doi.org/10.1146/annurev.ecolsys.35.112202.130215 Williams GC (1992) Natural Selection: Domains, Levels, and Challenges. Oxford University Press, Oxford, New York. Zu P, Boege K, del-Val E, Schuman MC, Stevenson PC, Zaldivar-Riverón A, Saavedra S (2020) Information arms race explains plant-herbivore chemical communication in ecological communities. Science, 368, 1377–1381. https://doi.org/10.1126/science.aba2965 | Comment on “Information arms race explains plant-herbivore chemical communication in ecological communities” | Ethan Bass, André Kessler | <p style="text-align: justify;">Zu et al (Science, 19 Jun 2020, p. 1377) propose that an ‘information arms-race’ between plants and herbivores explains plant-herbivore communication at the community level. However, the analysis presented here show... | ![]() | Chemical ecology, Community ecology, Eco-evolutionary dynamics, Evolutionary ecology, Herbivory, Interaction networks, Theoretical ecology | Rodrigo Medel | 2021-10-02 06:06:07 | View | |
14 Jan 2025
Cool topoclimates promote cold-adapted plant diversity in temperate mountain forests.Jeremy Borderieux, Emiel De Lombaerde, Karen De Pauw, Pieter Sanczuk, Pieter Vangansbeke, Thomas Vanneste, Pieter De Frenne, Jean-Claude Gégout, Josep M. Serra- Diaz https://doi.org/10.32942/X2XC8TForest microclimate in mountains and its impact on plant community: Still a question of shade, but this time it’s not coming from the canopyRecommended by Romain Bertrand based on reviews by Martin Macek and 2 anonymous reviewersRecently, microclimate has gained significant momentum [1], as evidenced by the increasing number of studies and the emergence of a dedicated scientific community coordinating research efforts [2]. Several factors underpin this trend, including advances in technology that have made microclimate monitoring [3] and ecological contextualization [4] more accessible, as well as improvements in computational methods that facilitate modeling at unprecedented scales [5]. But the growing emphasis on microclimate is primarily driven by their ecological relevance, as microclimate represent the actual climate conditions experienced by organisms [1]. This makes them more suitable than macroclimate data for understanding and predicting biodiversity responses to climate change [6]. While macroclimate data remain a common tool in ecology, they often represent generalized climatic conditions over large spatial scales. These data are typically derived from statistical models calibrated on observations collected at meteorological stations [7], which are usually located at 2 meters above the ground in open areas and at elevations compatible with human activities. Such characteristics limit the applicability of macroclimate data for understanding biodiversity responses, particularly at finer spatial scales. This is especially true in forest ecosystems, where microclimate results from the filtering of macroclimate conditions by forest habitats [8]. A simple walk in a forest during summer highlights this filtering, with the cooling effect of canopy shading and tree packing being clearly perceptible. If humans can sense these variations, they likely influence forest biodiversity. In fact, microclimates are crucial for defining the thermal niches of understory plant species [9] and understanding plant community reshuffling in response to climate warming [10]. In mountainous areas, topography adds further complexity to microclimates. The drop in temperature with elevation, known as the elevation-temperature lapse rate, is familiar, but topography also drives fine-scale variations [11]. Solar radiation hitting forest varies with aspect and hillshade, creating localized temperature differences. For example, equator-facing slopes receive more sunlight, while west-facing slopes are sunlit during the warmest part of the day. Consequently, in the northern hemisphere, southwest-facing slopes generally exhibit warmer temperatures, longer growing seasons, and shorter snow cover durations [12]. Thus, both topography and forest canopy shape the understory microclimate experienced by organisms in temperate mountainous forests. Is biodiversity more influenced by topography- or canopy-induced temperature buffering? While this question may not seem particularly interesting at first glance, understanding the underlying mechanisms of microclimate is crucial for guiding biodiversity conservation decisions in the face of climate change [13]. Poleward-facing slopes, valley bottoms, and dense canopies buffer warm episodes by creating cooler, more humid habitats that can serve as refugia for biodiversity [12]. Both buffering processes are valuable for conservation, but topography-induced buffering is generally more stable over the long term [14]. In contrast, canopy buffering is more vulnerable to human management, disturbances, and the ongoing acceleration of climate change, which is expected to drive tree mortality and lead to canopy opening [15]. Identifying the dominant buffering process in a given area is essential for mapping biodiversity refugia and fully integrating microclimate into conservation strategies. This approach can improve decision-making and actions aimed at promoting biodiversity sustainability in a warming world. The work of Borderieux and colleagues [16] offers new insights into this question through an innovative approach. They focus on temperate forests in a watershed in the Vosges Mountains, where they monitor understory temperature and inventory forest plant communities in separate samplings. Aiming to disentangle the effects of topography and forest canopy on understory temperature and its impact on plant communities, the authors deployed a network of temperature sensors using stratified sampling, balanced according to topography (elevation, aspect, and slope) and canopy cover. They then correlated mean annual temperatures (daily mean and maximum) with topographic factors and canopy cover, considering their potential interactions in a linear model. The contribution of each microclimate component was computed, and their effects on temperatures were mapped. These predictions were then confronted to floristic inventories to test whether topography- and canopy-induced temperature variations explained plant diversity and assemblages. First, the authors demonstrated that local topographic variations, which determine the amount of solar radiation reaching forests in mountainous areas, outweigh the contribution of canopy shading to understory temperatures. This result is surprising, as many previous studies have emphasized the importance of canopy buffering in shaping forest microclimate conditions [8]. However, these studies mostly focused on lowland areas or large scales, where terrain roughness has less influence. It is also unexpected because the authors observed that canopy cover varies at a smaller scale than aspect or topographic position in their study area, creating habitat heterogeneity that could reasonably drive local temperature variations. Nevertheless, the authors found that aspect, heat load, and topographic position induced more variation in microclimate than canopy filtering, significantly allowing deviations from the expected elevation-temperature lapse rate. Second, the topographic effect on understory temperature propagated to biodiversity. The authors found that topography-induced temperature offset explained plant diversity and composition, while canopy-induced temperature offset did not. Specifically, cold topoclimates harbored 30% more species than the average species richness across the inventoried plots. This increase in species richness was primarily due to an increase in cold-adapted species, highlighting the role of cold topoclimates as refugia. It is difficult to assess the extent to which these results are influenced by the specific forest context of the study area chosen by the authors, as there is no clear consensus in previous research regarding the role of topoclimate. For example, Macek et al. (2019) [17] highlighted the predominance of topography in controlling temperature and, consequently, forest community structure in the Czech Republic, while Vandewiele et al. (2023) [18] demonstrated the dominance of canopy control in the German Alps. The forest conditions investigated by Borderieux et al. (2025) were narrow, as they focused mainly on closed forests (more than 80% of the study area and sampling sites exhibiting canopy cover greater than 79%). Given that the canopy buffering effect on temperature increases with canopy cover until plateauing at around 80% [19], this may explain why the authors did not find a strong contribution from the canopy. Nevertheless, the methodology and case presented in their study are both innovative and applicable to other mountainous regions. The work of Borderieux et al. (2025) deserves attention for highlighting a frequently overlooked component of forest microclimate, as canopy filtering is typically regarded as the dominant driver. Topoclimate is a critical factor to consider when protecting cold-adapted forest species in the context of global warming, especially since topographic features are less subject to change than canopy cover. Future research should aim to test this hypothesis across a broader range of forest and topography conditions to identify general patterns, as well as assess the long-term effectiveness of these topographic refugia for biodiversity. It remains unclear whether the cooling effect provided by topoclimate will be sufficient to stabilize climate conditions despite the expected acceleration of climate warming in the coming decades, and whether it will be able to preserve cold-adapted species, which are among the most unique but threatened components of mountain biodiversity. References [1] Kemppinen, J. et al. Microclimate, an important part of ecology and biogeography. Global Ecology and Biogeography 33, e13834 (2024). https://doi.org/10.1111/geb.13834 [2] Lembrechts, J. J. et al. SoilTemp: A global database of near-surface temperature. Global Change Biology 26, 6616–6629 (2020). https://doi.org/10.1111/gcb.15123 [3] Wild, J. et al. Climate at ecologically relevant scales: A new temperature and soil moisture logger for long-term microclimate measurement. Agricultural and Forest Meteorology 268, 40–47 (2019). https://doi.org/10.1016/j.agrformet.2018.12.018 [4] Zellweger, F., Frenne, P. D., Lenoir, J., Rocchini, D. & Coomes, D. Advances in Microclimate Ecology Arising from Remote Sensing. Trends in Ecology & Evolution 34, 327–341 (2019). https://doi.org/10.1016/j.tree.2018.12.012 [5] Haesen, S. et al. ForestTemp – Sub-canopy microclimate temperatures of European forests. Global Change Biology 27, 6307–6319 (2021). https://doi.org/10.1111/gcb.15892 [6] Lembrechts, J. J. et al. Comparing temperature data sources for use in species distribution models: From in-situ logging to remote sensing. Global Ecology and Biogeography 28, 1578–1596 (2019). https://doi.org/10.1111/geb.12974 [7] Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. International Journal of Climatology 37, 4302–4315 (2017). https://doi.org/10.1002/joc.5086 [8] De Frenne, P. et al. Global buffering of temperatures under forest canopies. Nat Ecol Evol 3, 744–749 (2019). https://doi.org/10.1038/s41559-019-0842-1 [9] Haesen, S. et al. Microclimate reveals the true thermal niche of forest plant species. Ecology Letters 26, 2043–2055 (2023). https://doi.org/10.1111/ele.14312 [10] Zellweger, F. et al. Forest microclimate dynamics drive plant responses to warming. Science 368, 772–775 (2020). https://doi.org/10.1126/science.aba6880 [11] Rolland, C. Spatial and Seasonal Variations of Air Temperature Lapse Rates in Alpine Regions. Journal of climate, 16(7), 1032-1046 (2003). https://doi.org/10.1175/1520-0442(2003)016%3C1032:SASVOA%3E2.0.CO;2 [12] Rita, A. et al. Topography modulates near-ground microclimate in the Mediterranean Fagus sylvatica treeline. Sci Rep 11, 1–14 (2021). https://doi.org/10.1038/s41598-021-87661-6 [13] Bertrand, R., Aubret, F., Grenouillet, G., Ribéron, A. & Blanchet, S. Comment on “Forest microclimate dynamics drive plant responses to warming”. Science 370, eabd3850 (2020). https://doi.org/10.1126/science.abd3850 [14] Hylander, K., Greiser, C., Christiansen, D. M. & Koelemeijer, I. A. Climate adaptation of biodiversity conservation in managed forest landscapes. Conservation Biology 36, e13847 (2022). https://doi.org/10.1111/cobi.13847 [15] McDowell, N. G. & Allen, C. D. Darcy’s law predicts widespread forest mortality under climate warming. Nature Clim Change 5, 669–672 (2015). https://doi.org/10.1038/nclimate2641 [16] Borderieux, J. et al. Cool topoclimates promote cold-adapted plant diversity in temperate mountain forests. Ecoevorxiv, ver. 3( 2024). Peer-reviewed and recommended by PCI Ecology https://doi.org/10.32942/X2XC8T [17] Macek, M., Kopecký, M. & Wild, J. Maximum air temperature controlled by landscape topography affects plant species composition in temperate forests. Landscape Ecol 34, 2541–2556 (2019). https://doi.org/10.1007/s10980-019-00903-x [18] Vandewiele, M. et al. Mapping spatial microclimate patterns in mountain forests from LiDAR. Agricultural and Forest Meteorology 341, 109662 (2023). https://doi.org/10.1016/j.agrformet.2023.109662 [19] Zellweger, F. et al. Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe. Global Ecology and Biogeography 28, 1774–1786 (2019). https://doi.org/10.1111/geb.12991
| Cool topoclimates promote cold-adapted plant diversity in temperate mountain forests. | Jeremy Borderieux, Emiel De Lombaerde, Karen De Pauw, Pieter Sanczuk, Pieter Vangansbeke, Thomas Vanneste, Pieter De Frenne, Jean-Claude Gégout, Josep M. Serra- Diaz | <p>Climate strongly influences the composition and diversity of forest plant communities. Recent studies have highlighted the role of tree canopies in shaping understory thermal conditions at small spatial scales (i.e. microclimate), especially in... | Biodiversity, Climate change, Community ecology, Spatial ecology, Metacommunities & Metapopulations, Terrestrial ecology | Romain Bertrand | 2024-07-05 00:17:37 | View | ||
20 Jun 2024
![]() Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitorsDiogo Prino Godinho, Ines Fragata, Maud Charlery de la Masseliere, Sara Magalhaes https://doi.org/10.1101/2023.08.17.553707We are better together: Spider mites running away from Cadmium contaminated plants make better decisions collectively than individuallyRecommended by Ruben HelenoHyperaccumulator 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 | View |
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