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07 Nov 2024
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Using multiple datasets to account for misalignment between statistical and biological populations for abundance estimation

Diving into detection process to solve sampling and abundance issues in a cryptic species

Recommended by ORCID_LOGO based on reviews by Michael Schaub, Chloé Nater and 1 anonymous reviewer

Estimating population parameters is critical for analysis and management of wildlife populations. Drawing inference at the population level requires a robust sampling scheme and information about the representativeness of the studied population (Williams et al. 2002). In their textbook, Williams et al. (see chapter 5, 2002) listed several sampling issues, including both temporal and spatial heterogeneity and especially imperfect detection. Several methods, either sampling-based or model-based can be used to circumvent these issues.

In their paper, Kissling et al. (2024) addressed the case of the Kittlitz’s murrelet (Brachyramphus brevirostris), a cryptic ice-associated seabird, combining spatial variation in its distribution, temporal variation in breeding propensity, imperfect detection and logistical challenges to access the breeding area. The Kittlitz’s murrelet is thus the perfect species to illustrate common issues and logistical difficulties to implement a standard sampling scheme. 

The authors proposed a modelling framework unifying several datasets from different surveys to extract information on each step of the detection process: the spatial match between the targeted population and the sampled population, the probability of presence in the sample area, the probability of availability given presence in the sample area and finally, the probability of detection given presence and availability. All these components were part of the framework to estimate abundance and trend for this species. 

They took advantage of a radiotracking survey during several years to inform spatial match and probability of presence. They performed a behavioural experiment to assess the probability of availability of murrelets given it was present in sampling area, and they used a conventional distance-sampling boat survey to estimate detection of individuals. This is worth noting that the most variable components were the probability of presence in the sample area, with a global mean of 0.50, and the probability of detection given presence and availability ranging from 0.49 to 0.77. The estimated trend for Kittlitz’s murrelet was negative and all the information gathered in this study will be useful for future conservation plan. 

Coupling a decomposition of the detection process with different data sources was the key to solve problems raised by such “difficult” species, and the paper of Kissling et al. (2024) is a good way to follow for other species, allowing to inform the detection components for the targeted species - and also for our global understanding of detection process, and to infer about the temporal trend of species of conservation concern. 

References

Williams, B. K., Nichols, J. D., and Conroy, M. J. (2002). Analysis and management of animal populations. Academic Press.

Michelle L. Kissling, Paul M. Lukacs, Kelly Nesvacil, Scott M. Gende, Grey W. Pendleton (2024) Using multiple datasets to account for misalignment between statistical and biological populations for abundance estimation. EcoEvoRxiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.32942/X2W03T

Using multiple datasets to account for misalignment between statistical and biological populations for abundance estimationMichelle L. Kissling, Paul M. Lukacs, Kelly Nesvacil, Scott M. Gende, Grey W. Pendleton<p style="text-align: justify;">A fundamental aspect of ecology is identifying and characterizing population processes. Because a complete census is rare, we almost always use sampling to make inference about the biological population, and the par...Euring Conference, Population ecologyGuillaume Souchay2023-12-28 19:59:21 View
30 Oct 2024
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The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models

In the quest for estimating true survival

Recommended by ORCID_LOGO based on reviews by Rémi Fay and 1 anonymous reviewer

Accurately estimating survival rate and identifying the drivers of its variation is essential for our understanding of population dynamics and life history strategies (Sæther and Bakke 2000), as well as for population management and conservation (Francis et al. 1998, Doherty et al. 2014). Many studies estimate survival from capture–recapture data using the Cormack–Jolly–Seber (CJS) model (Lebreton et al. 1992). However, survival estimates are confounded with permanent emigration from the study area, which can be particularly problematic for mobile species. This is problematic, not only because CJS models under estimate true survival in populations where permanent emigration occurs (i.e. they estimate “apparent” survival), but also because some factors of interest may affect both survival and emigration (e.g., habitat quality, Paquet et al. 2020), leaving the interpretation of results challenging, for example in terms of management decisions.

Several methods have been developed to account for permanent emigration when estimating survival, for example by jointly analyzing CMR data with data on individuals’ locations at each capture/resighting site (to estimate their dispersal distances; Schaub and Royle 2013, Badia Boher et al. 2023), with telemetry data (Powel et al. 2000), mark recovery data (Burnham 1993, Fay et al. 2019), or with live-resight data (Barker 1997).

The Barker joint live-recapture/live-resight (JLRLR) model can estimate survival when resight data are continuous over a long interval and from a larger area than the capture recapture data. This model becomes particularly promising with the growing collection of data from citizen science, or remote detection tools (Dzul et al. 2023). However, as pointed out by Dzul et al., this model assumes that resight probability is homogeneous across the area where individuals can move, and this assumption is likely violated for example because of non-random movements or because of non-random location of resighting sites.

In their manuscript, Dzul et al. performed a thorough simulation study to evaluate the accuracy of survival estimates from JLRLR models under various study designs regarding the location of resight sites (global, random, fixed including the capture site, and fixed excluding the capture site). They simulated data with varying survival and movement values, varying recapture and resight probabilities, and varying sample sizes. Finally, they also developed and fitted a multi state version of the JLRLR model. They show that JLRLR models performed better than CJS models. Survival estimates were still often biased (either positively or negatively) but they were less biased when sesight sites were randomly located (rather than at fixed locations), when recapture sites were included in the resighting design, and when using the multi state JLRLR model they developed.

This study highlights (multistate) JLRLR models as an alternative to CJS models one should consider when auxiliary resight data can be collected. Moreover, it shows the importance of evaluating not only model performance, but also the efficiency of alternative sampling designs before choosing one for our studies. Hopefully, this study will help the authors and other researchers making a more informed and efficient choice of model and design to estimate survival in their study populations.

References

Jaume A. Badia-Boher, Joan Real, Joan Lluís Riera, Frederic Bartumeus, Francesc Parés, Josep Maria Bas, and Antonio Hernández-Matías. Joint estimation of survival and dispersal effectively corrects the permanent emigration bias in mark-recapture analyses. (2023) Scientific reports 13, no. 1: 6970. https://doi.org/10.1038/s41598-023-32866-0 

Richard J Barker (1997) Joint modeling of live-recapture, tag-resight, and tag-recovery data. Biometrics: 666-677. https://doi.org/10.2307/2533966 

Kenneth P. Burnham (1993) Marked Individuals in the Study of Bird Populations (ed. J.D. Lebreton), pp. 199–213. Birkhäuser, Basel

Kevin E. Doherty, David E. Naugle, Jason D. Tack, Brett L. Walker, Jon M. Graham, Jeffrey L. Beck (2014) Linking conservation actions to demography: grass height explains variation in greater sage‐grouse nest survival. Wildlife biology 20, no. 6 : 320-325. https://doi.org/10.2981/wlb.00004

Maria C. Dzul, Charles B. Yackulic, William L. Kendall (2023) The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight models. arXiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.48550/arXiv.2312.13414

Rémi Fay, Stephanie Michler, Jacques Laesser, and Michael Schaub (2019) Integrated population model reveals that kestrels breeding in nest boxes operate as a source population. Ecography 42, no. 12: 2122-2131. https://doi.org/10.1111/ecog.04559

Charles M. Francis, John R. Sauer, Jerome R. Serie (1998) Effect of restrictive harvest regulations on survival and recovery rates of American black ducks. The Journal of Wildlife Management : 1544-1557. https://doi.org/10.2307/3802021

Jean-Dominique Lebreton, Kenneth P. Burnham, Jean Clobert, David R. Anderson (1992) Modeling survival and testing biological hypotheses using marked animals: a unified approach with case studies. Ecological monographs 62.1: 67-118. https://doi.org/10.2307/2937171

Matthieu Paquet, Debora Arlt, Jonas Knape, Matthew Low, Pär Forslund, and Tomas Pärt (2020) Why we should care about movements: Using spatially explicit integrated population models to assess habitat source–sink dynamics. Journal of Animal Ecology 89, no. 12: 2922-2933. https://doi.org/10.1111/1365-2656.13357

Larkin A. Powell, Michael J. Conroy, James E. Hines, James D. Nichols, and David G. Krementz. Simultaneous use of mark-recapture and radiotelemetry to estimate survival, movement, and capture rates. (2000) The Journal of Wildlife Management : 302-313. https://doi.org/10.2307/3803003

Bernt-Erik Sæther, Øyvind Bakke (2000) Avian life history variation and contribution of demographic traits to the population growth rate. Ecology 81.3 : 642-653. https://doi.org/10.1890/0012-9658(2000)081[0642:ALHVAC]2.0.CO;2

Michael Schaub, J. Andrew Royle. Estimating true instead of apparent survival using spatial Cormack–Jolly–Seber models (2014) Methods in Ecology and Evolution 5, no. 12: 1316-1326. https://doi.org/10.1111/2041-210X.12134

The importance of sampling design for unbiased estimation of survival using joint live-recapture and live resight modelsMaria C. Dzul, Charles B. Yackulic, William L. Kendall<p>Survival is a key life history parameter that can inform management decisions and life history research. Because true survival is often confounded with permanent and temporary emigration from the study area, many studies must estimate apparent ...Dispersal & Migration, Euring Conference, Population ecology, Statistical ecologyMatthieu Paquet2023-12-22 22:31:07 View
07 Nov 2024
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A dataset of Zostera marina and Zostera noltei structure and functioning in four sites along the French coast over a period of 18 months

A functional ecology reference database on the populations of two species of Zoostera along french coasts

Recommended by ORCID_LOGO based on reviews by Antoine Vernay, Sara PUIJALON and 1 anonymous reviewer

Seagrass beds are in a poor state of conservation and the ecological function of these plant communities is poorly assessed.

Four zones of eelgrass beds (Zostera marina and Zostera noltei) were described in terms of the morphology of the plant populations and the associated fauna. At the same time, parameters related to the functioning of these ecosystems were quantified (benthic fluxes of oxygen, carbon and nutrients) over a two-year cycle.

The article provides the databases collected and provides the main characteristics of these habitats for the measured parameters.

The work provides a reference database on the Zoostera beds of french coastal areas, outlining the ecological contrasts between both ecosystems. This database can on the one hand contribute to help management and restoration of these habitats, and on the other hand provide a reference state of their ecology, with a view to long-term monitoring.

References

Élise Lacoste, Vincent Ouisse, Nicolas Desroy, Lionel Allano, Isabelle Auby, Touria Bajjouk, Constance Bourdier, Xavier Caisey, Marie-Noelle de Casamajor, Nicolas Cimiterra, Céline Cordier, Amélia Curd, Lauriane Derrien, Gabin Droual, Stanislas F. Dubois, Élodie Foucault, Aurélie Foveau, Jean-Dominique Gaffet, Florian Ganthy, Camille Gianaroli, Rachel Ignacio-Cifré, Pierre-Olivier Liabot, Gregory Messiaen, Claire Meteigner, Benjamin Monnier, Robin Van Paemelen, Marine Pasquier, Loic Rigouin, Claire Rollet, Aurélien Royer, Laura Soissons, Aurélien Tancray, Aline Blanchet-Aurigny (2023) A dataset of Zostera marina and Zostera noltei structure and functioning in four sites along the French coast over a period of 18 months.. Zenodo, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.5281/zenodo.10425140

A dataset of *Zostera marina* and *Zostera noltei* structure and functioning in four sites along the French coast over a period of 18 monthsÉlise Lacoste, Vincent Ouisse, Nicolas Desroy, Lionel Allano, Isabelle Auby, Touria Bajjouk, Constance Bourdier, Xavier Caisey, Marie-Noelle de Casamajor, Nicolas Cimiterra, Céline Cordier, Amélia Curd, Lauriane Derrien, Gabin Droual, Stanislas F....<p>This manuscript describes the methodology associated with the dataset entitled: A dataset of <em>Zostera marina </em>and <em>Zostera noltei </em>structure and functioning in four sites along the French coast over a period of 18 months. The data...Biodiversity, Community ecology, Conservation biology, Ecosystem functioning, Marine ecologyGudrun Bornette2023-12-21 11:48:43 View
14 Jun 2024
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Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards

Uncovering the ecology in big-data by hierarchizing multi-scale environmental effects

Recommended by based on reviews by Kévin Tougeron and Jianqiang Sun

Along with the generalization of open-access practices, large, heterogeneous datasets are becoming increasingly available to ecologists (Farley et al. 2018). While such data offer exciting opportunities for unveiling original patterns and trends, they also raise new challenges regarding how to extract relevant information and actually improve our knowledge of complex ecological systems, beyond purely descriptive correlations (Dietze 2017, Farley et al. 2018).

In this work, Caumette et al. (2024) develop an original ecoinformatics approach to relate multi-scale environmental factors to the temporal dynamics of a major pest in mango orchards. Their method relies on the recent tree-boosting method GPBoost (Sigrist 2022) to hierarchize the influence of environmental factors of heterogeneous nature (e.g., orchard composition and management; landscape structure; climate) on the emergence date of the oriental fruit fly, Bactrocera dorsalis. As boosting methods allows the analysis of high-dimensional data, they are particularly adapted to the exploration of such datasets, to uncover unexpected, potentially complex dependencies between ecological dynamics and multiple environmental factors (Farley et al. 2018). In this article, Caumette et al. (2024) make a special effort to guide the reader step by step through their complex analysis pipeline to make it broadly understandable to the average ecologist, which is no small feat. I particularly welcome this commitment, as making new, cutting-edge analytical methods accessible to a large community of science practitioners with varying degrees of statistical or programming expertise is a major challenge for the future of quantitative ecology. 

The main result of Caumette et al. (2024) is that temperature and humidity conditions both at the local and regional scales are the main predictors of B. dorsalis emergence date, while orchard management practices seem to have relatively little influence. This suggests that favourable climatic conditions may allow the persistence of small populations of B. dorsalis over the dry season, which may then act as a propagule source for early re-infestations. However, as the authors explain, the resulting regression model is not designed for predictive purposes and should not at this stage be used for decision-making in pest management. Its main interest rather resides in identifying potential key factors favoring early infestations of B. dorsalis, and help focusing future experimental field studies on the most relevant levers for integrated pest management in mango orchards.

In a wider perspective, this work also provides a convincing proof-of-concept for the use of boosting methods to identify the most influential factors in large, multivariate datasets in a variety of ecological systems. It is also crucial to keep in mind that the current exponential growth in high-throughput environmental data (Lucivero 2020) could quickly come into conflict with the need to reduce the environmental footprint of research (Mariette et al. 2022). In this context, robust and accessible methods for extracting and exploiting all the information available in already existing datasets might prove essential to a sustainable pursuit of science.

References
 
Caumette C, Diatta P, Piry S, Chapuis M-P, Faye E, Sigrist F, Martin O, Papaïx J, Brévault T, Berthier K. 2024. Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of Bactrocera dorsalis population growth in Senegalese orchards. bioRxiv 2023.11.10.566583, ver. 3 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.1101/2023.11.10.566583

Dietze MC. 2017. Ecological Forecasting. Princeton University Press
 
Farley SS, Dawson A, Goring SJ, Williams JW. 2018. Situating Ecology as a Big-Data Science: Current Advances, Challenges, and Solutions. BioScience, 68, 563–576, https://doi.org/10.1093/biosci/biy068
 
Lucivero F. 2020. Big Data, Big Waste? A Reflection on the Environmental Sustainability of Big Data Initiatives. Science and Engineering Ethics 26, 1009–1030. https://doi.org/10.1007/s11948-019-00171-7

Mariette J, Blanchard O, Berné O, Aumont O, Carrey J, Ligozat A-L, Lellouch E, Roche P-E, Guennebaud G, Thanwerdas J, Bardou P, Salin G, Maigne E, Servan S, Ben-Ari T 2022. An open-source tool to assess the carbon footprint of research. Environmental Research: Infrastructure and Sustainability, 2022. https://dx.doi.org/10.1088/2634-4505/ac84a4
 
Sigrist F. 2022. Gaussian process boosting. The Journal of Machine Learning Research, 23, 10565-10610. https://jmlr.org/papers/v23/20-322.html
 

Hierarchizing multi-scale environmental effects on agricultural pest population dynamics: a case study on the annual onset of *Bactrocera dorsalis* population growth in Senegalese orchardsCécile Caumette, Paterne Diatta, Sylvain Piry, Marie-Pierre Chapuis, Emile Faye, Fabio Sigrist, Olivier Martin, Julien Papaïx, Thierry Brévault, Karine Berthier<p>Implementing integrated pest management programs to limit agricultural pest damage requires an understanding of the interactions between the environmental variability and population demographic processes. However, identifying key environmental ...Demography, Landscape ecology, Statistical ecologyElodie Vercken2023-12-11 17:02:08 View
28 Jun 2024
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Accounting for observation biases associated with counts of young when estimating fecundity: case study on the arboreal-nesting red kite (Milvus milvus)

Accounting for observation biases associated with counts of young: you may count too many or too few...

Recommended by ORCID_LOGO based on reviews by Steffen Oppel and 1 anonymous reviewer

Most species are hard to observe, and different methods are required to estimate demographic parameters such as the number of young individuals produced (one measure of breeding success) and survival. In the former case, and in particular for birds of prey, it often relies upon direct observations of breeding pairs on their nests. Two problems can then occur, that some young are missed and therefore the breeding success is underestimated (“false negatives”), but it is also possible that because for example of the nest structure or vegetation surrounding the nest, more young birds than in fact are present are counted (“false positives”). Sollmann et al. (2024) address this problem by using data where the truth is known as each nest was also accessed after climbing the tree, and a hierarchical model accounting for both undercounts and overcounts. Finally, they assess the impact of this correction on projected population size using simulations.

This paper is a solid contribution to the panoply of methods and models that are available for monitoring populations, and has potential applications for many species for which both false positives and false negatives can be a problem. The results on the projected population sizes – showing that for growing populations correcting for bias can lead to large differences in population sizes after a few decades – may seem counterintuitive as population growth rate of long-lived species such as birds of prey is not very sensitive to a change in breeding success (as compared to adult survival). However, one should just be reminded that a small difference in population growth rate may translate to a large difference after many years – for example a growth rate of 1.05 after 50 years mean than population size is multiplied by 11.5, whereas a growth of 1.03 after 50 years mean a multiplication by 4.4, more than twice less individuals. Small differences may matter a lot if they are sustained, and a key aspect of management is to ensure that they are. Of course, management actions having an impact on survival may be more effective, but they might be harder to achieve than for example ensuring that birds of prey breed successfully.

References

Sollmann Rahel, Adenot Nathalie, Spakovszky Péter, Windt Jendrik, Mattsson Brady J. 2024. Accounting for observation biases associated with counts of young when estimating fecundity. bioRxiv, v. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.12.01.569571

 

Accounting for observation biases associated with counts of young when estimating fecundity: case study on the arboreal-nesting red kite (*Milvus milvus*)Sollmann Rahel, Adenot Nathalie, Spakovszky Péter, Windt Jendrik, Brady J. Mattsson<p style="text-align: justify;">Counting the number of young in a brood from a distance is common practice, for example in tree-nesting birds. These counts can, however, suffer from over and undercounting, which can lead to biased estimates of fec...Demography, Statistical ecologyNigel Yoccoz2023-12-11 08:52:22 View
28 Mar 2024
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Changes in length-at-first return of a sea trout (Salmo trutta) population in northern France

Why are trout getting smaller?

Recommended by based on reviews by Jan Kozlowski and 1 anonymous reviewer

Decline in body size over time have been widely observed in fish (but see Solokas et al. 2023), and the ecological consequences of this pattern can be severe (e.g., Audzijonyte et al. 2013, Oke et al. 2020). Therefore, studying the interrelationships between life history traits to understand the causal mechanisms of this pattern is timely and valuable. 

This phenomenon was the subject of a study by Josset et al. (2024), in which the authors analysed data from 39 years of trout trapping in the Bresle River in France. The authors focused mainly on the length of trout on their first return from the sea.   

The most important results of the study were the decrease in fish length-at-first return and the change in the age structure of first-returning trout towards younger (and earlier) returning fish. It seems then that the smaller size of trout is caused by a shorter time spent in the sea rather than a change in a growth pattern, as length-at-age remained relatively constant, at least for those returning earlier. Fish returning after two years spent in the sea had a relatively smaller length-at-age. The authors suggest this may be due to local changes in conditions during fish's stay in the sea, although there is limited environmental data to confirm the causal effect. Another question is why there are fewer of these older fish. The authors point to possible increased mortality from disease and/or overfishing.

These results may suggest that the situation may be getting worse, as another study finding was that “the more growth seasons an individual spent at sea, the greater was its length-at-first return.” The consequences may be the loss of the oldest and largest individuals, whose disproportionately high reproductive contribution to the population is only now understood (Barneche et al. 2018, Marshall and White 2019). 

References

Audzijonyte, A. et al. 2013. Ecological consequences of body size decline in harvested fish species: positive feedback loops in trophic interactions amplify human impact. Biol Lett 9, 20121103. https://doi.org/10.1098/rsbl.2012.1103

Barneche, D. R. et al. 2018. Fish reproductive-energy output increases disproportionately with body size. Science Vol 360, 642-645. https://doi.org/10.1126/science.aao6868

Josset, Q. et al. 2024. Changes in length-at-first return of a sea trout (Salmo trutta) population in northern France. biorXiv, 2023.11.21.568009, ver 4, Peer-reviewed and recommended by PCI Ecology. https://doi.org/10.1101/2023.11.21.568009

Marshall, D. J. and White, C. R. 2019. Have we outgrown the existing models of growth? Trends in Ecology & Evolution, 34, 102-111. https://doi.org/10.1016/j.tree.2018.10.005

Oke, K. B. et al. 2020. Recent declines in salmon body size impact ecosystems and fisheries. Nature Communications, 11, 4155. https://doi.org/10.1038/s41467-020-17726-z

Solokas, M. A. et al. 2023. Shrinking body size and climate warming: many freshwater salmonids do not follow the rule. Global Change Biology, 29, 2478-2492. https://doi.org/10.1111/gcb.16626

Changes in length-at-first return of a sea trout (*Salmo trutta*) population in northern FranceQuentin Josset, Laurent Beaulaton, Atso Romakkaniemi, Marie Nevoux<p style="text-align: justify;">The resilience of sea trout populations is increasingly concerning, with evidence of major demographic changes in some populations. Based on trapping data and related scale collection, we analysed long-term changes ...Biodiversity, Evolutionary ecology, Freshwater ecology, Life history, Marine ecologyAleksandra Walczyńska2023-11-23 14:36:39 View
09 Aug 2024
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Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samples

Pooled samples hold information about the prevalence of wildlife pathogens

Recommended by ORCID_LOGO based on reviews by Megan Griffiths and 2 anonymous reviewers

Although monitoring the prevalence of pathogens in wildlife is crucial, there are logistical constraints that make this difficult, costly, and unpractical. This problem is often compounded when attempting to measure the temporal dynamics of prevalence. To improve the detection rate, a commonly used technique is pooling samples, where multiple individuals are analyzed at once. Yet, this introduces further potential biases: low-prevalence samples are effectively diluted through pooling, creating a false negative risk; negative samples are masked by the inclusion of positive samples, possibly artificially inflating the estimate of prevalence (and masking the inter-sample variability).

In their contribution, Borremans et al. (2024) come up with a modelling technique to provide accurate predictions of prevalence dynamics using a mix of pooled and individual samples. Because this model represents the pooling of individual samples as a complete mixing process, it can accurately estimate the prevalence dynamics from pooled samples only.

It is particularly noteworthy that the model provides an estimation of the false negative rate of the test. When there are false negatives (or more accurately, when the true rate at which false negatives happens), the value of the effect coefficients for individual-level covariates are likely to be off, potentially by a substantial amount. But besides more accurate coefficient estimation, the actual false negative rate is important information about the overall performance of the infection test.

The model described in this article also allows for a numerical calculation of the probability density function of infection. It is worth spending some time on how this is achieved, as I found the approach relying on combinatorics to be particularly interesting. When pooling, both the number of individuals that are mixed is known, and so is the measurement made on the pooled samples. The question is to figure out the number of individuals that because they are infectious, contribute to this score. The approach used by the authors is to draw (with replacement) possible positive and negative test outcomes assuming a number of positive individuals, and from this to estimate a pathogen concentration in the positive samples. This pathogen concentration can be transformed into its test outcome, and this value taken over all possible combinations is a conditional estimate of the test outcome, knowing the number of pooled individuals, and estimating the number of positive ones.

This approach is where the use of individual samples informs the model: by providing additional corrections for the relative volume of sample each individual provides, and by informing the transformation of test values into virus concentrations.

The authors make a strong case that their model can provide robust estimates of prevalence even in the presence of common field epidemiology pitfalls, and notably incomplete individual-level information. More importantly, because the model can work from pooled samples only, it gives additional value to samples that would otherwise have been discarded because they did not allow for prevalence estimates.

References

Benny Borremans, Caylee A. Falvo, Daniel E. Crowley, Andrew Hoegh, James O. Lloyd-Smith, Alison J. Peel, Olivier Restif, Manuel Ruiz-Aravena, Raina K. Plowright (2024) Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samples. bioRxiv, ver.3 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2023.11.02.565200

Reconstructing prevalence dynamics of wildlife pathogens from pooled and individual samplesBenny Borremans, Caylee A. Falvo, Daniel E. Crowley, Andrew Hoegh, James O. Lloyd-Smith, Alison J. Peel, Olivier Restif, Manuel Ruiz-Aravena, Raina K. Plowright<p style="text-align: justify;">Pathogen transmission studies require sample collection over extended periods, which can be challenging and costly, especially in the case of wildlife. A useful strategy can be to collect pooled samples, but this pr...Epidemiology, Statistical ecologyTimothée Poisot Joshua Hewitt2023-11-21 23:16:20 View
18 Apr 2024
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The large and central Caligo martia eyespot may reduce fatal attacks by birds: a case study supports the deflection hypothesis in nature

Intimidation or deflection: field experiments in a tropical forest to simultaneously test two competing hypotheses about how butterfly eyespots confer protection against predators

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Eyespots—round or oval spots, usually accompanied by one or more concentric rings, that together imitate vertebrate eyes—are found in insects of at least three orders and in some tropical fishes (Stevens 2005). They are particularly frequent in Lepidoptera, where they occur on wings of adults in many species (Monteiro et al. 2006), and in caterpillars of many others (Janzen et al. 2010). The resemblance of eyespots to vertebrate eyes often extends to details, such as fake « pupils » (round or slit-like) and « eye sparkle » (Blut et al. 2012). Larvae of one hawkmoth species even have fake eyes that appear to blink (Hossie et al. 2013). Eyespots have interested evolutionary biologists for well over a century. While they appear to play a role in mate choice in some adult Lepidoptera, their adaptive significance in adult Lepidoptera, as in caterpillars, is mainly as an anti-predator defense (Monteiro 2015). However, there are two competing hypotheses about the mechanism by which eyespots confer defense against predators. The « intimidation » hypothesis postulates that eyespots intimidate potential predators, startling them and reducing the probability of attack. The « deflection » hypothesis holds that eyespots deflect attacks to parts of the body where attack has relatively little effect on the animal’s functioning and survival. In caterpillars, there is little scope for the deflection hypothesis, because attack on any part of a caterpillar’s body is likely to be lethal. Much observational and some experimental evidence supports the intimidation hypothesis in caterpillars (Hossie & Sherratt 2012). In adult Lepidoptera, however, both mechanisms are plausible, and both have found support (Stevens 2005). The most spectacular examples of intimidation are in butterflies in which eyespots located centrally in hindwings and hidden in the natural resting position are suddenly exposed, startling the potential predator (e.g., Vallin et al. 2005). The most spectacular examples of deflection are seen in butterflies in which eyespots near the hindwing margin combined with other traits give the appearance of a false head (e.g., Chotard et al. 2022; Kodandaramaiah 2011). 

Most studies have attempted to test for only one or the other of these mechanisms—usually the one that seems a priori more likely for the butterfly species being studied. But for many species, particularly those that have neither spectacular startle displays nor spectacular false heads, evidence for or against the two hypotheses is contradictory.  

Iserhard et al. (2024) attempted to simultaneously test both hypotheses, using the neotropical nymphalid butterfly Caligo martia. This species has a large ventral hindwing eyespot, exposed in the insect’s natural resting position, while the rest of the ventral hindwing surface is cryptically coloured. In a previous study of this species, De Bona et al. (2015) presented models with intact and disfigured eyespots on a computer monitor to a European bird species, the great tit (Parus major). The results favoured the intimidation hypothesis. Iserhard et al. (2024) devised experiments presenting more natural conditions, using fairly realistic dummy butterflies, with eyespots manipulated or unmanipulated, exposed to a diverse assemblage of insectivorous birds in nature, in a tropical forest. Using color-printed paper facsimiles of wings, with eyespots present, UV-enhanced, or absent, they compared the frequency of beakmarks on modeling clay applied to wing margins (frequent attacks would support the deflection hypothesis) and (in one of two experiments) on dummies with a modeling-clay body (eyespots should lead to reduced frequency of attack, to wings and body, if birds are intimidated). Their experiments also included dummies without eyespots whose wings were either cryptically coloured (as in unmanipulated butterflies) or not. Their results, although complex, indicate support for the deflection hypothesis: dummies with eyespots were mostly attacked on these less vital parts. Dummies lacking eyespots were less frequently attacked, especially when they were camouflaged. Camouflaged dummies without eyespots were in fact the least frequently attacked of all the models. However, when dummies lacking eyespots were attacked, attacks were usually directed to vital body parts. These results show some of the complexity of estimating costs and benefits of protective conspicuous signals vs. camouflage (Stevens et al. 2008).

Two complementary experiments were conducted. The first used facsimiles with « wings » in a natural resting position (folded, ventral surfaces exposed), but without a modeling-clay « body ». In the second experiment, facsimiles had a modeling-clay « body », placed between the two unfolded wings to make it as accessible to birds as the wings. However, these dummies displayed the ventral surfaces of unfolded wings, an unnatural resting position. The study was thus not able to compare bird attacks to the body vs. wings in a natural resting position. One can understand the reason for this methodological choice, but it is a limitation of the study.

The naturalness of the conditions under which these field experiments were conducted is a strong argument for the biological significance of their results. However, the uncontrolled conditions naturally result in many questions being left open. The butterfly dummies were exposed to at least nine insectivorous bird species. Do bird species differ in their behavioral response to eyespots? Do responses depend on the distance at which a bird first detects the butterfly? Do eyespots and camouflage markings present on the same animal both function, but at different distances (Tullberg et al. 2005)? Do bird responses vary depending on the particular light environment in the places and at the times when they encounter the butterfly (Kodandaramaiah 2011)? Answering these questions under natural, uncontrolled conditions will be challenging, requiring onerous methods, (e.g., video recording in multiple locations over time). The study indicates the interest of pursuing these questions.

References

Blut, C., Wilbrandt, J., Fels, D., Girgel, E.I., & Lunau, K. (2012). The ‘sparkle’ in fake eyes–the protective effect of mimic eyespots in Lepidoptera. Entomologia Experimentalis et Applicata, 143, 231-244. https://doi.org/10.1111/j.1570-7458.2012.01260.x

Chotard, A., Ledamoisel, J., Decamps, T., Herrel, A., Chaine, A.S., Llaurens, V., & Debat, V. (2022). Evidence of attack deflection suggests adaptive evolution of wing tails in butterflies. Proceedings of the Royal Society B, 289, 20220562. https://doi.org/10.1098/rspb.2022.0562

De Bona, S., Valkonen, J.K., López-Sepulcre, A., & Mappes, J. (2015). Predator mimicry, not conspicuousness, explains the efficacy of butterfly eyespots. Proceedings of the Royal Society B, 282, 1806. https://doi.org/10.1098/RSPB.2015.0202

Hossie, T.J., & Sherratt, T.N. (2012). Eyespots interact with body colour to protect caterpillar-like prey from avian predators. Animal Behaviour, 84, 167-173. https://doi.org/10.1016/j.anbehav.2012.04.027

Hossie, T.J., Sherratt, T.N., Janzen, D.H., & Hallwachs, W. (2013). An eyespot that “blinks”: an open and shut case of eye mimicry in Eumorpha caterpillars (Lepidoptera: Sphingidae). Journal of Natural History, 47, 2915-2926. https://doi.org/10.1080/00222933.2013.791935

Iserhard, C.A., Malta, S.T., Penz, C.M., Brenda Barbon Fraga; Camila Abel da Costa; Taiane Schwantz; & Kauane Maiara Bordin (2024). The large and central Caligo martia eyespot may reduce fatal attacks by birds : a case study supports the deflection hypothesis in nature. Zenodo, ver. 1 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.5281/zenodo.10980357

Janzen, D.H., Hallwachs, W., & Burns, J.M. (2010). A tropical horde of counterfeit predator eyes. Proceedings of the National Academy of Sciences, USA, 107, 11659-11665. https://doi.org/10.1073/pnas.0912122107

Kodandaramaiah, U. (2011). The evolutionary significance of butterfly eyespots. Behavioral Ecology, 22, 1264-1271. https://doi.org/10.1093/beheco/arr123

Monteiro, A. (2015). Origin, development, and evolution of butterfly eyespots. Annual Review of Entomology, 60, 253-271. https://doi.org/10.1146/annurev-ento-010814-020942

Monteiro, A., Glaser, G., Stockslager, S., Glansdorp, N., & Ramos, D. (2006). Comparative insights into questions of lepidopteran wing pattern homology. BMC Developmental Biology, 6, 1-13. https://doi.org/10.1186/1471-213X-6-52

Stevens, M. (2005). The role of eyespots as anti-predator mechanisms, principally demonstrated in the Lepidoptera. Biological Reviews, 80, 573–588. https://doi.org/10.1017/S1464793105006810

Stevens, M., Stubbins, C.L., & Hardman C.J. (2008). The anti-predator function of ‘eyespots’ on camouflaged and conspicuous prey. Behavioral Ecology and Sociobiology, 62, 1787-1793. https://doi.org/10.1007/s00265-008-0607-3

Tullberg, B.S., Merilaita, S., & Wiklund, C. (2005). Aposematism and crypsis combined as a result of distance dependence: functional versatility of the colour pattern in the swallowtail butterfly larva. Proceedings of the Royal Society B, 272, 1315-1321. https://doi.org/10.1098/rspb.2005.3079

Vallin, A., Jakobsson, S., Lind, J., & Wiklund, C. (2005). Prey survival by predator intimidation: an experimental study of peacock butterfly defence against blue tits. Proceedings of the Royal Society B, 272, 1203-1207. https://doi.org/10.1098/rspb.2004.3034

The large and central *Caligo martia* eyespot may reduce fatal attacks by birds: a case study supports the deflection hypothesis in natureCristiano Agra Iserhard, Shimene Torve Malta, Carla Maria Penz, Brenda Barbon Fraga, Camila Abel da Costa, Taiane Schwantz, Kauane Maiara Bordin<p>Many animals have colorations that resemble eyes, but the functions of such eyespots are debated. Caligo martia (Godart, 1824) butterflies have large ventral hind wing eyespots, and we aimed to test whether these eyespots act to deflect or to t...Biodiversity, Community ecology, Conservation biology, Life history, Tropical ecologyDoyle Mc Key2023-11-21 15:00:20 View
18 Apr 2024
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Insights on the effect of mega-carcass abundance on the population dynamics of a facultative scavenger predator and its prey

Unveiling the influence of carrion pulses on predator-prey dynamics

Recommended by ORCID_LOGO based on reviews by Eli Strauss and 1 anonymous reviewer

Most, if not all, predators consume carrion in some circumstances (Sebastián-Gonzalez et al. 2023). Consequently, significant fluctuations in carrion availability can impact predator-prey dynamics by altering the ratio of carrion to live prey in the predators' diet (Roth 2003). Changes in carrion availability may lead to reduced predation when carrion is more abundant (hypo-predation) and intensified predation if predator populations surge in response to carrion influxes but subsequently face scarcity (hyper-predation), (Moleón et al. 2014, Mellard et al. 2021). However, this relationship between predation and scavenging is often challenging because of the lack of empirical data.
 
In the study conducted by Sidous et al. (2024), they used a large database on the abundance of spotted hyenas and their prey in Zimbabwe and Multivariate Autoregressive State-Space Models to calculate hyena and prey population densities and trends over a 60-year span. The researchers took advantage of abrupt fluctuations in elephant carcass availability that produced alternating periods of high and low carrion availability related to changing management strategies (i.e., elephant culling and water supply).
 
Interestingly, their analyses reveal a coupling of predator and prey densities over time, but they do not detect an effect of carcass availability on predator and prey dynamics. However, the density of prey and hyena was partially driven by the different temporal periods, suggesting some subtle effects of carrion availability on population trends. While it is acknowledged that other variables likely impact the population dynamics of hyenas and their prey, this is the first attempt to understand the influence of carrion pulses on predator-prey interactions across an extensive temporal scale. I hope this helps to establish a new research line on the effect of large carrion pulses, as this is currently largely understudied, even though the occurrence of carrion pulses, such as mass mortality events, is expected to increase over time (Fey et al. 2015).
 
References
 
Courchamp, F. et al. 2000. Rabbits killing birds: modelling the hyperpredation process. J. Anim. Ecol. 69: 154-164.
https://doi.org/10.1046/j.1365-2656.2000.00383.x

Fey, S. B. et al. 2015. Recent shifts in the occurrence, cause, and magnitude of animal mass mortality events. PNAS 112: 1083-1088.
https://doi.org/10.1073/pnas.1414894112
 
Mellard, J. P. et al. 2021. Effect of scavenging on predation in a food web. Ecol. Evol. 11: 6742- 6765.
https://doi.org/10.1002/ece3.7525

Moleón, M. et al. 2014. Inter-specific interactions linking predation and scavenging in terrestrial vertebrate assemblages. Biol. Rev. Camb. Philos. Soc. 89: 1042-1054.
https://doi.org/10.1111/brv.12097
 
Roth, J. 2003. Variability in marine resources affects arctic fox population dynamics. J. Anim. Ecol. 72: 668-676.
https://doi.org/10.1046/j.1365-2656.2003.00739.x
 
Sebastián-González, E. et al. 2023. The underestimated role of carrion in diet studies. Global Ecol. Biogeogr. 32: 1302-1310.
https://doi.org/10.1111/geb.13707
 
Sidous, M. et al. 2024. Insights on the effect of mega-carcass abundance on 1 the population dynamics of a facultative scavenger predator and its prey. bioRxiv, ver. 2 peer-reviewed and recommended by PCI Ecology.
https://doi.org/10.1101/2023.11.08.566247

Insights on the effect of mega-carcass abundance on the population dynamics of a facultative scavenger predator and its preyMellina Sidous; Sarah Cubaynes; Olivier Gimenez; Nolwenn Drouet-Hoguet; Stephane Dray; Loic Bollache; Daphine Madhlamoto; Nobesuthu Adelaide Ngwenya; Herve Fritz; Marion Valeix<p>The interplay between facultative scavenging and predation has gained interest in the last decade. The prevalence of scavenging induced by the availability of large carcasses may modify predator density or behaviour, potentially affecting prey....Community ecologyEsther Sebastián González Eli Strauss2023-11-14 15:27:16 View
20 Jun 2024
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Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitors

We are better together: Spider mites running away from Cadmium contaminated plants make better decisions collectively than individually

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Hyperaccumulator plants can concentrate heavy metals present on the soil in their tissues, avoiding their toxic effects and potentially discouraging herbivores (Martens & Boyd, 1994). But not all herbivores are necessarily discouraged, and access to locally abundant resources with low interspecific competition from other herbivores, can affect feeding choices. Godinho et al. performed a series of controlled laboratorial trials to evaluate if herbivores (spider mites) avoid tomato plants with high concentrations of Cadmium under alternative scenarios, namely: the presence/absence of conspecifics, the presence/absence of a competitor species (a congeneric mite), and the relative abundance of contaminated plants.

They found that when looking for plants to lay their eggs, individual spider-mites (females) do not seem to discriminate between plants with or without cadmium, despite a significantly lower performance on the former. However, they consistently chose plants without Cadmium in set-ups where 200 mites are faced with this decision together. This preference was consistent and independent from the relative abundance of cadmium-free plants, but only when mites do this decision collectively. In addition, this preference was stronger than that for plants where interspecific competition was lower, with mites preferring to face high competition from congeneric herbivores than laying their eggs on Cadmium contaminated plants. 

Taken together these experiments suggest that aggregation is a key mechanism by which spider mites can avoid metal contaminated plants. As good research often does, these experiments open several important questions that will need to be addressed in the future. In particular, it will be important to clarify what are the sensorial and behavioural mechanisms that allow this decision/outcome when spider mites make this choice collectively but lead to a different outcome (no choice) when they face this decision alone. Additionally, it will be interesting to explore the potentially adaptive (or non-adaptive) consequences of this behaviour in terms of individual and inclusive fitness. One thing seems certain: both the abiotic and the biotic context can affect spider mite choices, and both need to be considered to advance our understanding about the trade-offs between plant defence mechanisms and associated herbivore decisions and fitness. 

References

Martens, S. N., & Boyd, R. S. (1994). The ecological significance of nickel hyperaccumulation: a plant chemical defense. Oecologia, 98(3–4), 379–384. https://doi.org/10.1007/BF00324227

Godinho, D. P., I. Fragata, M. C. de la Masseliere, S. Magalhaes 2024 Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitors. bioRxiv, ver. 4, peer-reviewed and recommended by PCI Ecology 2023.08.17.553707. https://doi.org/10.1101/2023.08.17.553707

 

Spider mites collectively avoid plants with cadmium irrespective of their frequency or the presence of competitorsDiogo 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, HerbivoryRuben Heleno2023-11-09 11:52:58 View