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20 Jun 2019
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Sexual segregation in a highly pagophilic and sexually dimorphic marine predator

Sexual segregation in a sexually dimorphic seabird: a matter of spatial scale

Recommended by based on reviews by Dries Bonte and 1 anonymous reviewer

Sexual segregation appears in many taxa and can have important ecological, evolutionary and conservation implications. Sexual segregation can take two forms: either the two sexes specialise in different habitats but share the same area (habitat segregation), or they occupy the same habitat but form separate, unisex groups (social segregation) [1,2]. Segregation would have evolved as a way to avoid, or at least, reduce intersexual competition.
Testing whether social or habitat segregation is at play necessitates the use of combined approaches to determine the spatial scale at which segregation occurs. This enterprise is even more challenging when studying marine species, which travel over long distances to reach their foraging areas. This is what Barbraud et al. [3] have endeavoured on the snow petrel (Pagodroma nivea), a sexually dimorphic, polar seabird. Studying sexual segregation at sea requires tools for indirect measures of habitat use and foraging tactics. During the incubation period, in a colony based at Pointe Geologie, Adelie land, East Antarctica, the team has equipped birds with GPS loggers to analyse habitat use and foraging behaviour. It has also compared short-, mid-, and long-term stable isotopic profiles, from plasma, blood cells, and feather samples, respectively.
Barbraud et al. [3] could not detect any evidence for sexual segregation in space use. Furthermore, the two sexes showed similar δ13C profiles, illustrating similar foraging latitudes, and indicating no sexual segregation at large spatial scales. Snow petrels all forage exclusively in the sea ice environment formed over the deep Antarctic continental shelf. The authors, however, found other forms of segregation: males consistently foraged at higher sea ice concentrations than females. Males also fed on higher trophic levels than females. Therefore, male and female snow petrels segregate at a smaller spatial scale, and use different foraging tactics and diet specialisations. Females also took shorter foraging trips than males, with higher mass gain that strongly benefit from higher sea ice concentration. Mass gain in males increased with the length of their foraging trip at sea ice areas.
The authors conclude that high sea ice concentration offers the most favourable foraging habitat for snow petrels, and thus that intersexual competition may drive females away from high sea ice areas. This study shows that combining information from different tools provides an elegant way of isolating the potential factors driving sexual segregation and the spatial scales at which it occurs.

References

[1] Conradt, L. (2005). Definitions, hypotheses, models and measures in the study of animal segregation. In Sexual segregation in vertebrates: ecology of the two sexes (Ruckstuhl K.E. and Neuhaus, P. eds). Cambridge University Press, Cambridge, United Kingdom. Pp:11–34.
[2] Ruckstuhl, K. E. (2007). Sexual segregation in vertebrates: proximate and ultimate causes. Integrative and Comparative Biology, 47(2), 245-257. doi: 10.1093/icb/icm030
[3] Barbraud, C., Delord, K., Kato, A., Bustamante, P., & Cherel, Y. (2018). Sexual segregation in a highly pagophilic and sexually dimorphic marine predator. bioRxiv, 472431, ver. 3 peer-reviewed and recommended bt PCI Ecology. doi: 10.1101/472431

Sexual segregation in a highly pagophilic and sexually dimorphic marine predatorChristophe Barbraud, Karine Delord, Akiko Kato, Paco Bustamante, Yves Cherel<p>Sexual segregation is common in many species and has been attributed to intra-specific competition, sex-specific differences in foraging efficiency or in activity budgets and habitat choice. However, very few studies have simultaneously quantif...Foraging, Marine ecologyDenis Réale Dries Bonte, Anonymous2018-11-19 13:40:59 View
06 Jan 2021
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Comparing statistical and mechanistic models to identify the drivers of mortality within a rear-edge beech population

The complexity of predicting mortality in trees

Recommended by based on reviews by Lisa Hülsmann and 2 anonymous reviewers

One of the main issues of forest ecosystems is rising tree mortality as a result of extreme weather events (Franklin et al., 1987). Eventually, tree mortality reduces forest biomass (Allen et al., 2010), although its effect on forest ecosystem fluxes seems not lasting too long (Anderegg et al., 2016). This controversy about the negative consequences of tree mortality is joined to the debate about the drivers triggering and the mechanisms accelerating tree decline. For instance, there is still room for discussion about carbon starvation or hydraulic failure determining the decay processes (Sevanto et al., 2014) or about the importance of mortality sources (Reichstein et al., 2013). Therefore, understanding and predicting tree mortality has become one of the challenges for forest ecologists in the last decade, doubling the rate of articles published on the topic (*). Although predicting the responses of ecosystems to environmental change based on the traits of species may seem a simplistic conception of ecosystem functioning (Sutherland et al., 2013), identifying those traits that are involved in the proneness of a tree to die would help to predict how forests will respond to climate threatens.
Modelling tree mortality is complex, involving multiple factors acting simultaneously at different scales, from tree genetics to ecosystem dynamics and from microsite conditions to global climatic events. Therefore, taking into account different approaches to reduce uncertainty of the predictions is needed (Bugmann et al., 2019). Petit-Cailleux et al. (2020) uses statistical and process-based models to detect the main mortality drivers of a drought- and frost-prone beech population. Particularly, they assessed the intra-individual characteristics of the population, that may play a decisive role explaining the differences in tree vulnerability to extreme weather events. Comparing the results of both analytical approaches, they find out several key factors, such as defoliation, leaf phenology and tree size, that were consistent between them. Even more, the process-based model showed the physiological mechanisms that may explain the individual vulnerability, for instance higher loss of hydraulic conductance may increase the mortality risk of trees with early budburst phenology and large stem diameter. The authors also successfully model annual mortality rate with a linear relationship including only three parameters: loss of conductance, biomass of reserves and late frost days.
This valuable study is a good example of the complexity in understanding and predicting tree mortality. The authors carried out the ambitious commitment of studying the inter-annual variation in mortality with 14-year dataset. However, it might be not enough time to control for the dependence of temporal data to soundly model mortality rate. The authors also acknowledge that the use of two approaches increases the knowledge from different perspectives, but at the same time comparing their results is difficult because the parameters used are not identical. Particularly, process-based models tend to consider the same microclimatic conditions for every tree in the population, and may produce inconsistences with statistical models. Alternatively, individual-based modelling might overcome some of the incompatibilities between the approaches (Zhu et al., 2019).

(*) Number (and percentage) of articles found in Web of Sciences after searching (December the 10th, 2020) “tree mortality”: from 163 (0.006%) in 2010 to 412 (0.013%) in 2020.

References

Allen et al. (2010). A global overview of drought and heat-induced tree mortality reveals emerging climate change risks for forests. Forest ecology and management, 259(4), 660-684. doi: https://doi.org/10.1016/j.foreco.2009.09.001
Anderegg et al. (2016). When a tree dies in the forest: scaling climate-driven tree mortality to ecosystem water and carbon fluxes. Ecosystems, 19(6), 1133-1147. doi: https://doi.org/10.1007/s10021-016-9982-1
Bugmann et al. (2019). Tree mortality submodels drive simulated long‐term forest dynamics: assessing 15 models from the stand to global scale. Ecosphere, 10(2), e02616. doi: https://doi.org/10.1002/ecs2.2616
Franklin, J. F., Shugart, H. H. and Harmon, M. E. (1987) Death as an ecological process: the causes, consequences, and variability of tree mortality. BioScience, 37, 550–556. doi: https://doi.org/10.2307/1310665
Petit-Cailleux, C., Davi, H., Lefèvre, F., Garrigue, J., Magdalou, J.-A., Hurson, C., Magnanou, E. and Oddou-Muratorio, S. (2020) Comparing statistical and mechanistic models to identify the drivers of mortality within a rear-edge beech population. bioRxiv, 645747, ver 7 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/645747
Reichstein et al. (2013). Climate extremes and the carbon cycle. Nature, 500(7462), 287-295. doi: https://doi.org/10.1038/nature12350
Sevanto, S., Mcdowell, N. G., Dickman, L. T., Pangle, R., and Pockman, W. T. (2014). How do trees die? A test of the hydraulic failure and carbon starvation hypotheses. Plant, cell & environment, 37(1), 153-161. doi: https://doi.org/10.1111/pce.12141
Sutherland et al. (2013). Identification of 100 fundamental ecological questions. Journal of ecology, 101(1), 58-67. doi: https://doi.org/10.1111/1365-2745.12025
Zhu, Y., Liu, Z., and Jin, G. (2019). Evaluating individual-based tree mortality modeling with temporal observation data collected from a large forest plot. Forest Ecology and Management, 450, 117496. doi: https://doi.org/10.1016/j.foreco.2019.117496

Comparing statistical and mechanistic models to identify the drivers of mortality within a rear-edge beech populationCathleen Petit-Cailleux, Hendrik Davi, François Lefevre, Christophe Hurson, Joseph Garrigue, Jean-André Magdalou, Elodie Magnanou and Sylvie Oddou-Muratorio<p>Since several studies have been reporting an increase in the decline of forests, a major issue in ecology is to better understand and predict tree mortality. The interactions between the different factors and the physiological processes giving ...Climate change, Physiology, Population ecologyLucía DeSoto2019-05-24 11:37:38 View
04 Apr 2023
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Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation study

Species Distribution Models: the delicate balance between signal and noise

Recommended by ORCID_LOGO based on reviews by Alejandra Zarzo Arias and 1 anonymous reviewer

Species Distribution Models (SDMs) are one of the most commonly used tools to predict where species are, where they may be in the future, and, at times, what are the variables driving this prediction. As such, applying an SDM to a dataset is akin to making a bet: that the known occurrence data are informative, that the resolution of predictors is adequate vis-à-vis the scale at which their impact is expressed, and that the model will adequately capture the shape of the relationships between predictors and predicted occurrence.

In this contribution, Lambert & Virgili (2023) perform a comprehensive assessment of different sources of complications to this process, using replicated simulations of two synthetic species. Their experimental process is interesting, in that both the data generation and the data analysis stick very close to what would happen in "real life". The use of synthetic species is particularly relevant to the assessment of SDM robustness, as they enable the design of species for which the shape of the relationship is given: in short, we know what the model should capture, and can evaluate the model performance against a ground truth that lacks uncertainty.

Any simulation study is limited by the assumptions established by the investigators; when it comes to spatial data, the "shape" of the landscape, both in terms of auto-correlation and in where the predictors are available. Lambert & Virgili (2023) nicely circumvent these issues by simulating synthetic species against the empirical distribution of predictors; in other words, the species are synthetic, but the environment for which the prediction is made is real. This is an important step forward when compared to the use of e.g. neutral landscapes (With 1997), which can have statistical properties that are not representative of natural landscapes (see e.g. Halley et al., 2004).

A striking point in the study by Lambert & Virgili (2023) is that they reveal a deep, indeed deeper than expected, stochasticity in SDMs; whether this is true in all models remains an open question, but does not invalidate their recommendation to the community: the interpretation of outcomes is a delicate exercise, especially because measures that inform on the goodness of the model fit do not capture the predictive quality of the model outputs. This preprint is both a call to more caution, and a call to more curiosity about the complex behavior of SDMs, while also providing a sensible template to perform future analyses of the potential issues with predictive models.


References

Halley, J. M., et al. (2004) “Uses and Abuses of Fractal Methodology in Ecology: Fractal Methodology in Ecology.” Ecology Letters, vol. 7, no. 3, pp. 254–71. https://doi.org/10.1111/j.1461-0248.2004.00568.x.

Lambert, Charlotte, and Auriane Virgili (2023). Data Stochasticity and Model Parametrisation Impact the Performance of Species Distribution Models: Insights from a Simulation Study. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.01.17.524386

With, Kimberly A. (1997) “The Application of Neutral Landscape Models in Conservation Biology. Aplicacion de Modelos de Paisaje Neutros En La Biologia de La Conservacion.” Conservation Biology, vol. 11, no. 5, pp. 1069–80. https://doi.org/10.1046/j.1523-1739.1997.96210.x.

Data stochasticity and model parametrisation impact the performance of species distribution models: insights from a simulation studyCharlotte Lambert, Auriane Virgili<p>Species distribution models (SDM) are widely used to describe and explain how species relate to their environment, and predict their spatial distributions. As such, they are the cornerstone of most of spatial planning efforts worldwide. SDM can...Biogeography, Habitat selection, Macroecology, Marine ecology, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Statistical ecologyTimothée Poisot2023-01-20 09:43:51 View
30 Sep 2020
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How citizen science could improve Species Distribution Models and their independent assessment

Citizen science contributes to SDM validation

Recommended by based on reviews by Maria Angeles Perez-Navarro and 1 anonymous reviewer

Citizen science is becoming an important piece for the acquisition of scientific knowledge in the fields of natural sciences, and particularly in the inventory and monitoring of biodiversity (McKinley et al. 2017). The information generated with the collaboration of citizens has an evident importance in conservation, by providing information on the state of populations and habitats, helping in mitigation and restoration actions, and very importantly contributing to involve society in conservation (Brown and Williams 2019). An obvious advantage of these initiatives is the ability to mobilize human resources on a large territorial scale and in the medium term, which would otherwise be difficult to finance. The resulting increasing information then can be processed with advanced computational techniques (Hochachka et al 2012; Kelling et al. 2015), thus improving our interpretation of the distribution of species. Specifically, the ability to obtain information on a large territorial scale can be integrated into studies based on Species Distribution Models SDMs. One of the common problems with SDMs is that they often work from species occurrences that have been opportunistically recorded, either by professionals or amateurs. A great challenge for data obtained from non-professional citizens, however, remains to ensure its standardization and quality (Kosmala et al. 2016). This requires a clear and effective design, solid volunteer training, and a high level of coordination that turns out to be complex (Brown and Williams 2019). Finally, it is essential to perform a quality validation following scientifically recognized standards, since they are often conditioned by errors and biases in obtaining information (Bird et al. 2014). There are two basic approaches to obtain the necessary data for this validation: getting it from an external source (external validation), or allocating a part of the database itself (internal validation or cross-validation) to this function.
Matutini et al. (2020) in his work 'How citizen science could improve Species Distribution Models and their independent assessment' shows a novel application of the data generated by a citizen science initiative ('Un Dragon dans mon Jardin') by providing an external source for the validation of SDMs, as a tool to construct habitat suitability maps for nine species of amphibians in western France. Importantly, 'Un Dragon dans mon Jardin' contains standardized presence-absence data, the approximation recognized as the most robust (Guisan, et al. 2017). The SDMs to be validated, in turn, were based on opportunistic information obtained by citizens and professionals. The result shows the usefulness of this external data source by minimizing the overestimation of model accuracy that is obtained with cross-validation with the internal evaluation dataset. It also shows the importance of properly filtering the information obtained by citizens by determining the threshold of sampling effort.
The destiny of citizen science is to be integrated into the complex world of science. Supported by the increasing level of the formation of society, it is becoming a fundamental piece in the scientific system dedicated to the study of biodiversity and its conservation. After funding for scientists specialized in the recognition of biodiversity has been cut back, we are seeing a transformation of the activity of these scientists towards the design, coordination, training and verification of programs for the acquisition of field information obtained by citizens. A main goal is that a substantial part of this information will eventually get integrated into the scientific system, and rigorous verification process a fundamental element for such purpose, as shown by Matutini et al. (2020) work.

References

[1] Bird TJ et al. (2014) Statistical solutions for error and bias in global citizen science datasets. Biological Conservation 173: 144-154. doi: 10.1016/j.biocon.2013.07.037
[2] Brown ED and Williams BK (2019) The potential for citizen science to produce reliable and useful information in ecology. Conservation Biology 33: 561-569. doi: 10.1111/cobi.13223
[3] Guisan A, Thuiller W and Zimmermann N E (2017) Habitat Suitability and Distribution Models: With Applications in R. The University of Chicago Press. doi: 10.1017/9781139028271
[4] Hochachka WM, Fink D, Hutchinson RA, Sheldon D, Wong WK and Kelling S (2012) Data-intensive science applied to broad-scale citizen science. Trens Ecol Evol 27: 130-137. doi: 10.1016/j.tree.2011.11.006
[5] Kelling S, Fink D, La Sorte FA, Johnston A, Bruns NE and Hochachka WM (2015) Taking a ‘Big Data’ approach to data quality in a citizen science project. Ambio 44(Supple. 4):S601-S611. doi: 10.1007/s13280-015-0710-4
[6] Kosmala M, Wiggins A, Swanson A and Simmons B (2016) Assessing data quality in citizen science. Front Ecol Environ 14: 551–560. doi: 10.1002/fee.1436
[7] Matutini F, Baudry J, Pain G, Sineau M and Pithon J (2020) How citizen science could improve Species Distribution Models and their independent assessment. bioRxiv, 2020.06.02.129536, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/2020.06.02.129536
[8] McKinley DC et al. (2017) Citizen science can improve conservation science, natural resource management, and environmental protection. Biological Conservation 208:15-28. doi: 10.1016/j.biocon.2016.05.015

How citizen science could improve Species Distribution Models and their independent assessmentFlorence Matutini, Jacques Baudry, Guillaume Pain, Morgane Sineau, Josephine Pithon<p>Species distribution models (SDM) have been increasingly developed in recent years but their validity is questioned. Their assessment can be improved by the use of independent data but this can be difficult to obtain and prohibitive to collect....Biodiversity, Biogeography, Conservation biology, Habitat selection, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Statistical ecologyFrancisco Lloret2020-06-03 09:36:34 View
02 Jan 2024
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Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models

Useful clarity on the value of considering temporal variability in detection probability

Recommended by ORCID_LOGO based on reviews by Dana Karelus and Ben Augustine

As so often quoted, "all models are wrong; more specifically, we always neglect potentially important factors in our models of ecological systems. We may neglect these factors because no-one has built a computational framework to include them; because including them would be computationally infeasible; or because we don't have enough data.  When considering whether to include a particular process or form of heterogeneity, the gold standard is to fit models both with and without the component, and then see whether we needed the component in the first place ​-- that is, whether including that component leads to an important difference in our conclusions. However, this approach is both tedious and endless, because there are an infinite number of components that we could consider adding to any given model.

Therefore, thoughtful exercises that evaluate the importance of particular complications under a realistic range of simulations and a representative set of case studies are extremely valuable for the field. While they cannot provide ironclad guarantees, they give researchers a general sense of when they can (probably) safely ignore some factors in their analyses. This paper by Sollmann (2024) shows that for a very wide range of scenarios, temporal and spatiotemporal variability in the probability of detection have little effect on the conclusions of spatial capture-recapture and occupancy models.  The author is thoughtful about when such variability may be important, e.g. when variation in detection and density is correlated and thus confounded, or when variation is driven by animals' behavioural responses to being captured.

Reference

Sollmann R (2024). Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy models. bioRxiv, 2023.08.08.552394, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.08.08.552394

Mt or not Mt: Temporal variation in detection probability in spatial capture-recapture and occupancy modelsRahel Sollmann<p>State variables such as abundance and occurrence of species are central to many questions in ecology and conservation, but our ability to detect and enumerate species is imperfect and often varies across space and time. Accounting for imperfect...Euring Conference, Statistical ecologyBenjamin Bolker Dana Karelus, Ben Augustine, Ben Augustine 2023-08-10 09:18:56 View
03 Oct 2023
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Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sources

Biodiversity databases are ever more numerous, but can they be used reliably for Species Distribution Modelling?

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Proposing efficient guidelines for biodiversity conservation often requires the use of forecasting tools. Species Distribution Models (SDM) are more and more used to predict how the distribution of a species will react to environmental change, including any large-scale management actions that could be implemented. Their use is also boosted by the increase of publicly available biodiversity databases[1]. The now famous aphorism by George Box "All models are wrong but some are useful"[2] very well summarizes that the outcome of a model must be adjusted to, and will depend on, the data that are used to parameterize it. The question of the reliability of using biodiversity databases to parameterize biodiversity models such as SDM –but the question would also apply to other kinds of biodiversity models, e.g. Population Viability Analysis models[3]– is key to determine the confidence that can be placed in model predictions. This point is often overlooked by some categories of biodiversity conservation stakeholders, in particular the fact that some data were collected using controlled protocols while others are opportunistic. 

In this study[4], the authors use a collection of databases covering a range of species as well as of geographic scales in France and using different data collection and validation approaches as a case study to evaluate the impact of data quality when performing Strategic Environmental Assessment (SEA). Among their conclusions, the fact that a large-scale database (what they call the “country” level) is necessary to reliably parameterize SDM. Besides this and other conclusions of their study, which are likely to be in part specific to their case study –unfortunately for its conservation, biodiversity is complex and varies a lot–, the merit of this work lies in the approach used to test the impact of data on model predictions.

References

1.  Feng, X. et al. A review of the heterogeneous landscape of biodiversity databases: Opportunities and challenges for a synthesized biodiversity knowledge base. Global Ecology and Biogeography 31, 1242–1260 (2022). https://doi.org/10.1111/geb.13497

2.  Box, G. E. P. Robustness in the Strategy of Scientific Model Building. in Robustness in Statistics (eds. Launer, R. L. & Wilkinson, G. N.) 201–236 (Academic Press, 1979). https://doi.org/10.1016/B978-0-12-438150-6.50018-2.

3.  Beissinger, S. R. & McCullough, D. R. Population Viability Analysis. (The University of Chicago Press, 2002).

4.  Ferraille, T., Kerbiriou, C., Bigard, C., Claireau, F. & Thompson, J. D. (2023) Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sources. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.1101/2023.05.09.539999

Integrating biodiversity assessments into local conservation planning: the importance of assessing suitable data sourcesThibaut Ferraille, Christian Kerbiriou, Charlotte Bigard, Fabien Claireau, John D. Thompson<p>Strategic Environmental Assessment (SEA) of land-use planning is a fundamental tool to minimize environmental impacts of artificialization. In this context, Systematic Conservation Planning (SCP) tools based on Species Distribution Models (SDM)...Biodiversity, Conservation biology, Species distributions, Terrestrial ecologyNicolas Schtickzelle2023-05-11 09:41:05 View
25 Oct 2021
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The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes

The difficult interpretation of species co-distribution

Recommended by based on reviews by Anthony Maire and Emilie Macke

Ecology is the study of the distribution of organisms in space and time and their interactions. As such, there is a tradition of studies relating abiotic environmental conditions to species distribution, while another one is concerned by the effects of consumers on the abundance of their resources.  Interestingly, joining the dots appears more difficult than it would suggest: eluding the effect of species interactions on distribution remains one of the greatest challenges to elucidate nowadays (Kissling et al. 2012). Theory suggests that yes, species interactions such as predation and competition should influence range limits (Godsoe et al. 2017), but the common intuition among many biogeographers remains that over large areas such as regions and continents, environmental drivers like temperature and precipitation overwhelm their local effects. Answering this question is of primary importance in the context where species are moving around with climate warming.  Inconsistencies in food web structure may arise with asynchronized movements of consumers and their resources, leading to a major disruption in regulation and potentially ecosystem functioning. Solving this problem, however, remains very challenging because we have to rely on observational data since experiments are hard to perform at the biogeographical scale. 

The study of St-Gelais is an interesting step forward to solve this problem. Their main objective was to assess the strength of the association between phytoplankton and zooplankton communities at a large spatial scale, looking at the spatial covariation of both taxonomic and functional composition. To do so, they undertook a massive survey of more than 100 lakes across three regions of the boreal region of Québec. Species and functional composition were recorded, along with a set of abiotic variables. Classic community ecology at this point. The difficulty they faced was to disentangle the multiple causal relationships involved in the distribution of both trophic levels. Teasing apart bottom-up and top-down forces driving the assembly of plankton communities using observational data is not an easy task. On the one hand, both trophic levels could respond to variations in temperature, nutrient availability and dissolved organic carbon. The interpretation is fairly straightforward if the two levels respond to different factors, but the situation is much more complicated when they do respond similarly. There are potentially three possible underlying scenarios. First, the phyto and zooplankton communities may share the same environmental requirements, thereby generating a joint distribution over gradients such as temperature and nutrient availability. Second, the abiotic environment could drive the distribution of the phytoplankton community, which would then propagate up and influence the distribution of the zooplankton community. Alternatively, the abiotic environment could constrain the distribution of the zooplankton, which could then affect the one of phytoplankton. In addition to all of these factors, St-Gelais et al also consider that dispersal may limit the distribution, well aware of previous studies documenting stronger dispersal limitations for zooplankton communities. 

Unfortunately, there is not a single statistical approach that could be taken from the shelf and used to elucidate drivers of co-distribution. Joint species distribution was once envisioned as a major step forward in this direction (Warton et al. 2015), but there are several limits preventing the direct interpretation that co-occurrence is linked to interactions (Blanchet et al. 2020). Rather, St-Gelais used a variety of multivariate statistics to reveal the structure in their observational data. First, using a Procrustes analysis (a method testing if the spatial variation of one community is correlated to the structure of another community), they found a significant correlation between phytoplankton and zooplankton communities, indicating a taxonomic coupling between the groups. Interestingly, this observation was maintained for functional composition only when interaction-related traits were considered. At this point, these results strongly suggest that interactions are involved in the correlation, but it's hard to decipher between bottom-up and top-down perspectives. A complementary analysis performed with a constrained ordination, per trophic level, provided complementary pieces of information. First observation was that only functional variation was found to be related to the different environmental variables, not taxonomic variation. Despite that trophic levels responded to water quality variables, spatial autocorrelation was more important for zooplankton communities and the two layers appear to respond to different variables. 

It is impossible with those results to formulate a strong conclusion about whether grazing influence the co-distribution of phytoplankton and zooplankton communities. That's the mere nature of observational data. While there is a strong spatial association between them, there are also diverging responses to the different environmental variables considered. But the contrast between taxonomic and functional composition is nonetheless informative and it seems that beyond the idiosyncrasies of species composition, trait distribution may be more informative and general. Perhaps the most original contribution of this study is the hierarchical approach to analyze the data, combined with the simultaneous analysis of taxonomic and functional distributions. Having access to a vast catalog of multivariate statistical techniques, a careful selection of analyses helps revealing key features in the data, rejecting some hypotheses and accepting others. Hopefully, we will see more and more of such multi-trophic approaches to distribution because it is now clear that the factors driving distribution are much more complicated than anticipated in more traditional analyses of community data. Biodiversity is more than a species list, it is also all of the interactions between them, influencing their distribution and abundance (Jordano 2016).

References

Blanchet FG, Cazelles K, Gravel D (2020) Co-occurrence is not evidence of ecological interactions. Ecology Letters, 23, 1050–1063. https://doi.org/10.1111/ele.13525

Godsoe W, Jankowski J, Holt RD, Gravel D (2017) Integrating Biogeography with Contemporary Niche Theory. Trends in Ecology & Evolution, 32, 488–499. https://doi.org/10.1016/j.tree.2017.03.008

Jordano P (2016) Chasing Ecological Interactions. PLOS Biology, 14, e1002559. https://doi.org/10.1371/journal.pbio.1002559

Kissling WD, Dormann CF, Groeneveld J, Hickler T, Kühn I, McInerny GJ, Montoya JM, Römermann C, Schiffers K, Schurr FM, Singer A, Svenning J-C, Zimmermann NE, O’Hara RB (2012) Towards novel approaches to modelling biotic interactions in multispecies assemblages at large spatial extents. Journal of Biogeography, 39, 2163–2178. https://doi.org/10.1111/j.1365-2699.2011.02663.x

St-Gelais NF, Vogt RJ, Giorgio PA del, Beisner BE (2021) The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakes. bioRxiv, 373332, ver. 4 peer-reviewed and recommended by Peer community in Ecology. https://doi.org/10.1101/373332

Warton DI, Blanchet FG, O’Hara RB, Ovaskainen O, Taskinen S, Walker SC, Hui FKC (2015) So Many Variables: Joint Modeling in Community Ecology. Trends in Ecology & Evolution, 30, 766–779. https://doi.org/10.1016/j.tree.2015.09.007

Wisz MS, Pottier J, Kissling WD, Pellissier L, Lenoir J, Damgaard CF, Dormann CF, Forchhammer MC, Grytnes J-A, Guisan A, Heikkinen RK, Høye TT, Kühn I, Luoto M, Maiorano L, Nilsson M-C, Normand S, Öckinger E, Schmidt NM, Termansen M, Timmermann A, Wardle DA, Aastrup P, Svenning J-C (2013) The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling. Biological Reviews, 88, 15–30. https://doi.org/10.1111/j.1469-185X.2012.00235.x

The taxonomic and functional biogeographies of phytoplankton and zooplankton communities across boreal lakesNicolas F St-Gelais, Richard J Vogt, Paul A del Giorgio, Beatrix E Beisner<p>Strong trophic interactions link primary producers (phytoplankton) and consumers (zooplankton) in lakes. However, the influence of such interactions on the biogeographical distribution of the &nbsp;taxa and functional traits of planktonic organ...Biogeography, Community ecology, Species distributionsDominique Gravel2018-07-24 15:01:51 View
31 May 2023
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Conservation networks do not match the ecological requirements of amphibians

Amphibians under scrutiny - When human-dominated landscape mosaics are not in full compliance with their ecological requirements

Recommended by ORCID_LOGO based on reviews by Peter Vermeiren and 1 anonymous reviewer

Among vertebrates, amphibians are one of the most diverse groups with more than 7,000 known species. Amphibians occupy various ecosystems, including forests, wetlands, and freshwater habitats. Amphibians are known to be highly sensitive to changes in their environment, particularly to water quality and habitat degradation, so that monitoring abundance of amphibian populations can provide early warning signs of ecosystem disturbances that may also affect other organisms including humans (Bishop et al., 2012). Accordingly, efforts in habitat preservation and sustainable land and water management are necessary to safeguard amphibian populations.

In this context, Matutini et al. (2023) compared ecological requirements of amphibian species with the quality of agricultural landscape mosaics. Doing so, they identified critical gaps in existing conservation tools that include protected areas, green infrastructures, and inventoried sites. Matutini et al. (2023) focused on nine amphibian species in the Pays-de-la-Loire region where the landscape has been fashioned over the years by human activities. Three of the chosen amphibian species are living in a dense hedgerow mosaic landscape, while five others are more generalists.

Matutini et al. (2023) established multi-species habitat suitability maps, together with their levels of confidence, by combining single species maps with a probabilistic stacking method at 500-m resolution. From these maps, habitats were classified in five categories, from not suitable to highly suitable. Then, the circuit theory was used to map the potential connections between each highly suitable patch at the regional scale. Finally, comparing suitability maps with existing conservation tools, Matutini et al. (2023) were able to assess their coverage and efficiency.

Whatever their species status (endangered or not), Matutini et al. (2023) highlighted some discrepancies between the ecological requirements of amphibians in terms of habitat quality and the conservation tools of the landscape mosaic within which they are evolving. More specifically, Matutini et al. (2023) found that protected areas and inventoried sites covered only a small proportion of highly suitable habitats, while green infrastructures covered around 50% of the potential habitat for amphibian species. Such a lack of coverage and efficiency of protected areas brings to light that geographical sites with amphibian conservation challenges are known but not protected. Regarding the landscape fragmentation, Matutini et al. (2023) found that generalist amphibian species have a more homogeneous distribution of suitable habitats at the regional scale. They also identified two bottlenecks between two areas of suitable habitats, a situation that could prove critical to amphibian movements if amphibians were forced to change habitats to global change.

In conclusion, Matutini et al. (2023) bring convincing arguments in support of land-use species-conservation planning based on a better consideration of human-dominated landscape mosaics in full compliance with ecological requirements of the species that inhabit the regions concerned.

References

Bishop, P.J., Angulo, A., Lewis, J.P., Moore, R.D., Rabb, G.B., Moreno, G., 2012. The Amphibian Extinction Crisis - what will it take to put the action into the Amphibian Conservation Action Plan? Sapiens - Surveys and Perspectives Integrating Environment and Society 5, 1–16. http://journals.openedition.org/sapiens/1406

Matutini, F., Baudry, J., Fortin, M.-J., Pain, G., Pithon, J., 2023. Conservation networks do not match ecological requirements of amphibians. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.07.18.500425

Conservation networks do not match the ecological requirements of amphibiansMatutini Florence, Jacques Baudry, Marie-Josée Fortin, Guillaume Pain, Joséphine Pithon<p style="text-align: justify;">1. Amphibians are among the most threatened taxa as they are highly sensitive to habitat degradation and fragmentation. They are considered as model species to evaluate habitats quality in agricultural landscapes. I...Biodiversity, Biogeography, Human impact, Landscape ecology, Macroecology, Spatial ecology, Metacommunities & Metapopulations, Species distributions, Terrestrial ecologySandrine Charles2022-09-20 14:40:03 View
09 Nov 2023
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Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasets

Marks lost in action, biased estimations

Recommended by ORCID_LOGO based on reviews by Olivier Gimenez, Devin Johnson and 1 anonymous reviewer

Capture-Mark-Recapture (CMR) data are commonly used to estimate ecological variables such as abundance, survival probability, or transition rates from one state to another (e.g. from juvenile to adult, or migration from one site to another). Many studies have shown how estimations can be affected by neglecting one aspect of the population under study (e.g. the heterogeneity in survival between individuals) or one limit of the methodology itself (e.g. the fact that observers might not detect an individual although it is still alive). Strikingly, very few studies have yet assessed the robustness of one fundamental assumption of all CMR-based inferences: marks are supposed definitive and immutable. If they are not, how are estimations affected? Addressing this issue is the main goal of the paper by Touzalin et al. (2023), and they did a very nice work. But, because the answer is not that simple, it also calls for further investigations.

When and why would mark loss bias estimation? In at least two situations. First, when estimating survival rates: if an individual loses its mark, it will be considered as dead, hence death rates will be overestimated. Second, more subtly, when estimating transition rates: if one individual loses its mark at the specific moment where its state changes, then a transition will be missed in data. The history of the marked individual would then be split into two independent CMR sequences as if there were two different individuals, including one which died.

Touzalin et al. (2023) thoroughly studied these two situations by estimating ecological parameters on 1) well-thought simulated datasets, that cover a large range of possible situations inspired from a nice compilation of hundreds of estimations from fish and bats studies, and 2) on their own bats dataset, for which they had various sources of information about mark losses, i.e. different mark types on the same individuals, including mark based on genotypes, and marks found on the soil in the place where bats lived. Their main findings from the simulated datasets are that there is a general trend for underestimation of survival and transition rates if mark loss is not accounting for in the model, as it would be intuitively expected. However, they also showed from the bats dataset that biases do not show any obvious general trend, suggesting complex interactions between different ecological processes and/or with the estimation procedure itself.

The results by Touzalin et al. (2023) strongly suggest that mark loss should systematically be included in models estimating parameters from CMR data. In addition to adapt the inferential models, the authors also recommend considering either a double marking, or even a single but ‘permanent’ mark such as one based on the genotypes. However, the potential gain of a double marking or of the use of genotypes is still to be evaluated both in theory and practice, and it seems to be not that obvious at first sight. First because double marking can be costly for experimenters but also for the marked animals, especially as several studies showed that marks can significantly affect survival or recapture rates. Second because multiple sources of errors can affect genotyping, which would result in wrong individual assignations especially in populations with low genetic diversity or high inbreeding, or no individual assignation at all, which would increase the occurrence of missing data in CMR datasets. Touzalin et al. (2023) supposed in their paper that there were no genotyping errors, but one can doubt it to be true in most situations. They have now important and interesting other issues to address.

References

Frédéric Touzalin, Eric J. Petit, Emmanuelle Cam, Claire Stagier, Emma C. Teeling, Sébastien J. Puechmaille (2023) Mark loss can strongly bias demographic rates in multi-state models: a case study with simulated and empirical datasets. BioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.03.25.485763

Mark loss can strongly bias estimates of demographic rates in multi-state models: a case study with simulated and empirical datasetsFrédéric Touzalin, Eric J. Petit, Emmanuelle Cam, Claire Stagier, Emma C. Teeling, Sébastien J. Puechmaille<p style="text-align: justify;">1. The development of methods for individual identification in wild species and the refinement of Capture-Mark-Recapture (CMR) models over the past few decades have greatly improved the assessment of population demo...Conservation biology, DemographySylvain Billiard2022-04-12 18:49:34 View
19 Feb 2020
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Soil variation response is mediated by growth trajectories rather than functional traits in a widespread pioneer Neotropical tree

Growth trajectories, better than organ-level functional traits, reveal intraspecific response to environmental variation

Recommended by ORCID_LOGO based on reviews by Georges Kunstler and François Munoz

Functional traits are “morpho-physio-phenological traits which impact fitness indirectly via their effects on growth, reproduction and survival” [1]. Most functional traits are defined at organ level, e.g. for leaves, roots and stems, and reflect key aspects of resource acquisition and resource use by organisms for their development and reproduction [2]. More rarely, some functional traits can be related to spatial development, such as vegetative height and lateral spread in plants.
Organ-level traits are especially popular because they can be measured in a standard way and easily compared over many plants. But these traits can broadly vary during the life of an organism. For instance, Roggy et al. [3] found that Leaf Mass Area can vary from 30 to 140 g.m^(-2) between seedling and adult stages for the canopy tree Dicorynia guianensis in French Guiana. Fortunel et al. [4] have also showed that developmental stages much contribute to functional trait variation within several Micropholis tree species in lowland Amazonia.
The way plants grow and invest resources into organs is variable during life and allows defining specific developmental sequences and architectural models [5,6]. There is clear ontogenic variation in leaf number, leaf properties and ramification patterns. Ontogenic variations reflect changing adaptation of an individual over its life, depending on the changing environmental conditions.
In this regard, measuring a single functional trait at organ level in adult trees should miss the variation of resource acquisition and use strategies over time. Thus we should built a more integrative approach of ecological development, also called “eco-devo” approach [7].
Although the ecological significance of ontogeny and developmental strategies is now well known, the extent to which it contributes to explain species survival and coexistence in communities is still broadly ignored in functional ecology. Levionnois et al. [8] investigated intraspecific variation of functional traits and growth trajectories in a typical, early-successional tree species in French Guiana, Amazonia. This species, Cecropia obtusa, is generalist regarding soil type and can be found on both white sand and ferralitic soil. The study examines whether there in intraspecific variation in functional traits and growth trajectories of C. obtusa in response to the contrasted soil types.
The tree communities observed on the two types of soils include species with distinctive functional trait values, that is, there are changes in species composition related to different species strategies along the classical wood and leaf economic spectra. The populations of C. obtusa found on the two soils showed some difference in functional traits, but it did not concern traits related to the main economic spectra. Conversely, the populations showed different growth strategies, in terms of spatial and temporal development.
The major lessons we can learn from the study are:
(i) Functional traits measured at organ level cannot reflect well how long-lived plants collect and invest resources during their life. The results show the potential of considering architectural and developmental traits together with organ-level functional traits, to better acknowledge the variation in ecological strategies over plant life, and thus to better understand community assembly processes.
(ii) What makes functional changes between communities differs when considering interspecific and intraspecific variation. Species turnover should encompass different corteges of soil specialists. These specialists are sorted along economic spectra, as shown in tropical rainforests and globally [2]. Conversely, a generalist species such as C. obtusa does occur on contrasted soil, which entails that it can accommodate the contrasted ecological conditions. However, the phenotypic adjustment is not related to how leaves and wood ensure photosynthesis, water and nutrient acquisition, but regards the way the resources are allocated to growth and reproduction over time.
The results of the study stress the need to better integrate growth strategies and ontogeny in the research agenda of functional ecology. We can anticipate that organ-level functional traits and growth trajectories will be more often considered together in ecological studies. The integration should help better understand the temporal niche of organisms, and how organisms can coexist in space and time with other organisms during their life. Recently, Klimešová et al. [9] have proposed standardized protocols for collecting plant modularity traits. Such effort to propose easy-to-measure traits representing plant development and ontogeny, with clear functional roles, should foster the awaited development of an “eco-devo” approach.

References

[1] Violle, C., Navas, M. L., Vile, D., Kazakou, E., Fortunel, C., Hummel, I., & Garnier, E. (2007). Let the concept of trait be functional!. Oikos, 116(5), 882-892. doi: 10.1111/j.0030-1299.2007.15559.x
[2] Díaz, S. et al. (2016). The global spectrum of plant form and function. Nature, 529(7585), 167-171. doi: 10.1038/nature16489
[3] Roggy, J. C., Nicolini, E., Imbert, P., Caraglio, Y., Bosc, A., & Heuret, P. (2005). Links between tree structure and functional leaf traits in the tropical forest tree Dicorynia guianensis Amshoff (Caesalpiniaceae). Annals of forest science, 62(6), 553-564. doi: 10.1051/forest:2005048
[4] Fortunel, C., Stahl, C., Heuret, P., Nicolini, E. & Baraloto, C. (2020). Disentangling the effects of environment and ontogeny on tree functional dimensions for congeneric species in tropical forests. New Phytologist. doi: 10.1111/nph.16393
[5] Barthélémy, D., & Caraglio, Y. (2007). Plant architecture: a dynamic, multilevel and comprehensive approach to plant form, structure and ontogeny. Annals of botany, 99(3), 375-407. doi: 10.1093/aob/mcl260
[6] Hallé, F., & Oldeman, R. A. (1975). An essay on the architecture and dynamics of growth of tropical trees. Kuala Lumpur: Penerbit Universiti Malaya.
[7] Sultan, S. E. (2007). Development in context: the timely emergence of eco-devo. Trends in Ecology & Evolution, 22(11), 575-582. doi: 10.1016/j.tree.2007.06.014
[8] Levionnois, S., Tysklind, N., Nicolini, E., Ferry, B., Troispoux, V., Le Moguedec, G., Morel, H., Stahl, C., Coste, S., Caron, H. & Heuret, P. (2020). Soil variation response is mediated by growth trajectories rather than functional traits in a widespread pioneer Neotropical tree. bioRxiv, 351197, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/351197
[9] Klimešová, J. et al. (2019). Handbook of standardized protocols for collecting plant modularity traits. Perspectives in Plant Ecology, Evolution and Systematics, 40, 125485. doi: 10.1016/j.ppees.2019.125485

Soil variation response is mediated by growth trajectories rather than functional traits in a widespread pioneer Neotropical treeSébastien Levionnois, Niklas Tysklind, Eric Nicolini, Bruno Ferry, Valérie Troispoux, Gilles Le Moguedec, Hélène Morel, Clément Stahl, Sabrina Coste, Henri Caron, Patrick Heuret<p style="text-align: justify;">1- Trait-environment relationships have been described at the community level across tree species. However, whether interspecific trait-environment relationships are consistent at the intraspecific level is yet unkn...Botany, Eco-evolutionary dynamics, Habitat selection, Ontogeny, Tropical ecologyFrançois Munoz2018-06-21 17:13:17 View