The metacommunity framework acknowledges that local sites are connected to other sites through dispersal, and that these connectivity patterns can influence local dynamics [1]. This framework is slowly moving from a framework that guides fundamental research to being actively applied in for instance a conservation context (e.g. [2]). Swan and Brown [3,4] analyzed the results of a suite of experimental manipulations in headwater and mainstem streams on invertebrate community structure in the context of the metacommunity concept. This was an important contribution to conservation ecology.
However, David Murray-Stoker [5] was not satisfied with their statistical analyses, and recreated, and more importantly, improved their original analyses in the peer-reviewed article. The new analyses are based on a combination of a more consistent site selection, checking the model assumptions, using different estimation procedures, and focusing more on effect size calculations versus statistical significance. This peer-reviewed article is thus the perfect example of the advantages of open research: the original authors making available both the data and their R script files, initially first updating the analyses and results themselves, followed by more in-depth analyses of the original data and question.
This peer reviewed went through a very in-depth process itself, with several rounds of questions and feedback that addressed both the statistical analyses, the interpretation of the results, and the conclusions. It also, however, addressed something that is often harder to provide feedback on, for instance the tone of the argument. I hope that scientists interested in these issues will not only read the final manuscript, but also the different steps of the peer review processes. These are very informative, I think, and provide a more complete picture of mainly the raison for certain decisions.
Not only does this provide the reader interested in stream conservation with the opportunity to make up their own mind on the appropriateness of these decisions, but it could potentially lead to more analyses of this important data set. For instance, maybe a formal meta-analysis that starts with the effect sizes of all the original studies might bring some new insights into this question?

References

[1] Leibold, M. A., Holyoak, M., Mouquet, N. et al. (2004). The metacommunity concept: a framework for multi‐scale community ecology. Ecology letters, 7(7), 601-613. doi: 10.1111/j.1461-0248.2004.00608.x
[2] Heino, J. (2013). The importance of metacommunity ecology for environmental assessment research in the freshwater realm. Biological Reviews, 88(1), 166-178. doi: 10.1111/j.1469-185X.2012.00244.x
[3] Swan, C. M., and Brown, B. L. (2017). Metacommunity theory meets restoration: isolation may mediate how ecological communities respond to stream restoration. Ecological Applications, 27(7), 2209-2219. doi: 10.1002/eap.1602
[4] Swan, C. M., and Brown, B. L. (2018). Erratum for: Metacommunity theory meets restoration: isolation may mediate how ecological communities respond to stream restoration. Ecological Applications 28:1370–1371. doi: 10.1002/eap.1738
[5] Murray-Stoker, D. (2020). On the efficacy of restoration in stream networks: comments, critiques, and prospective recommendations. bioRxiv, 611939, ver. 7 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/611939

Some biological hypotheses are widely popular, so much so that we tend to forget their original lack of success. This is particularly true for hypotheses with catchy names. The ‘Ghost of competition past’ is part of the title of a paper by the great ecologist, JH Connell, one of the many losses of 2020 (Connell 1980). The hypothesis states that, even though we may not detect competition in current populations, their traits and distributions may be shaped by past competition events. Although this hypothesis has known a great success in the ecological literature, the original paper actually ends with “I will no longer be persuaded by such invoking of "the Ghost of Competition Past"”. Similarly, the hypothesis that mothers of herbivores choose host plants where their offspring will have a higher fitness was proposed by John Jaenike in 1978 (Jaenike 1978), and later coined the ‘mother knows best’ hypothesis. The hypothesis was readily questioned or dismissed: “Mother doesn't know best” (Courtney and Kibota 1990), or “Does mother know best?” (Valladares and Lawton 1991), but remains widely popular. It thus seems that catchy names (and the intuitive ideas behind them) have a heuristic value that is independent from the original persuasion in these ideas and the accumulation of evidence that followed it.

The paper by Castagneryol et al. (2021) analyses the preference-performance relationship in the box tree moth (BTM) Cydalima perspectalis, after defoliation of their host plant, the box tree, by conspecifics. It thus has bearings on the two previously mentioned hypotheses. Specifically, they created an artificial population of potted box trees in a greenhouse, in which 60 trees were infested with BTM third instar larvae, whereas 61 were left uninfested. One week later, these larvae were removed and another three weeks later, they released adult BTM females and recorded their host choice by counting egg clutches laid by these females on the plants. Finally, they evaluated the effect of previously infested vs uninfested plants on BTM performance by measuring the weight of third instar larvae that had emerged from those eggs.  

This experimental design was adopted because BTM is a multivoltine species. When the second generation of BTM arrives, plants have been defoliated by the first generation and did not fully recover. Indeed, Castagneryol et al. (2021) found that larvae that developed on previously infested plants were much smaller than those developing on uninfested plants, and the same was true for the chrysalis that emerged from those larvae. This provides unequivocal evidence for the existence of a ghost of competition past in this system. However, the existence of this ghost still does not result in a change in the distribution of BTM, precisely because mothers do not know best: they lay as many eggs on plants previously infested than on uninfested plants. 

The demonstration that the previous presence of a competitor affects the performance of this herbivore species confirms that ghosts exist. However, whether this entails that previous (interspecific) competition shapes species distributions, as originally meant, remains an open question. Species phenology may play an important role in exposing organisms to the ghost, as this time-lagged competition may have been often overlooked. It is also relevant to try to understand why mothers don’t care in this, and other systems. One possibility is that they will have few opportunities to effectively choose in the real world, due to limited dispersal or to all plants being previously infested. 

References

Castagneyrol, B., Halder, I. van, Kadiri, Y., Schillé, L. and Jactel, H. (2021) Host-mediated, cross-generational intraspecific competition in a herbivore species. bioRxiv, 2020.07.30.228544, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: https://doi.org/10.1101/2020.07.30.228544

Connell, J. H. (1980). Diversity and the coevolution of competitors, or the ghost of competition past. Oikos, 131-138. doi: https://doi.org/10.2307/3544421

Courtney, S. P. and Kibota, T. T. (1990) in Insect-plant interactions (ed. Bernays, E.A.) 285-330.

Jaenike, J. (1978). On optimal oviposition behavior in phytophagous insects. Theoretical population biology, 14(3), 350-356. doi: https://doi.org/10.1016/0040-5809(78)90012-6

Valladares, G., and Lawton, J. H. (1991). Host-plant selection in the holly leaf-miner: does mother know best?. The Journal of Animal Ecology, 227-240. doi: https://doi.org/10.2307/5456

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

In this study, the authors report a new method for estimating the abundance of the Pyrenean brown bear population. Precisely, the methodology involved aims to apply Pollock's closed robust design (PCRD) capture-recapture models to estimate population abundance and trends over time. Overall, the results encourage the use of PCRD to study populations' demographic rates, while minimizing biases due to inter-individual heterogeneity in detection probabilities.

Estimating the size and trends of animal population over time is essential for informing conservation status and management decision-making (Nichols & Williams 2006). This is particularly the case when the population is small, geographically scattered, and threatened. Although several methods can be used to estimate population abundance, they may be difficult to implement when individuals are rare, elusive, solitary, largely nocturnal, highly mobile, and/or occupy large home ranges in remote and/or rugged habitats. Moreover, in such standard methods,

• the population is assumed to be closed both geographically (no immigration nor emigration) and demographically (no births nor deaths) and
• all individuals are assumed to have identical detection probabilities regardless of their individual attributes (e.g., age, body mass, social status) and habitat features (home-range location and composition) (Otis et al. 1978).

However, these conditions are rarely met in real populations, such as wild mammals (e.g., Bellemain et al. 2005; Solbert et al. 2006), and therefore the risk of underestimating population size can rapidly increase because the assumption of perfect detection of all individuals in the population is violated.

Focusing on the critically endangered Pyrenean brown bear that was close to extinction in the mid-1990s, the study by Vanpe et al. (2022), uses protocol and opportunistic data to describe a statistical modeling exercise to construct mark-recapture histories from 2008 to 2020. Among the data, the authors collected non-invasive samples such as a mixture of hair and scat samples used for genetic identification, as well as photographic trap data of recognized individuals. These data are then analyzed in RMark to provide detection and survival estimates. The final model (i.e. PCRD capture-recapture) is then used to provide Bayesian population estimates. Results show a five-fold increase in population size between 2008 and 2020, from 13 to 66 individuals. Thus, this study represents the first published annual abundance and temporal trend estimates of the Pyrenean brown bear population since 2008.

Then, although the results emphasize that the PCRD estimates were broadly close to the MRS counts and had reasonably narrow associated 95% Credibility Intervals, they also highlight that the sampling effort is different according to individuals. Indeed, as expected, the detection of an individual depends on

• the intraspecific home range size variation that results in individuals that move the most being most likely to be detected and
• the mortality rate which is higher on cubs than on adults and subadults (due to infanticide by males, predation, death of the mother, or abandonment).

Overall, the PCRD capture-recapture modelling approach, involved in this study, provides robust estimates of abundance and demographic rates of the Pyrenean brown bear population (with associated uncertainty) while minimizing and considering bias due to inter-individual heterogeneity in detection probabilities.

The authors conclude that mark-recapture provides useful population estimates and urge wildlife ecologists and managers to use robust approaches, such as the RDPC capture-recapture model, when studying large mammal populations. This information is essential to inform management decisions and assess the conservation status of populations.

References

Bellemain, E.V.A., Swenson, J.E., Tallmon, D., Brunberg, S. and Taberlet, P. (2005). Estimating population size of elusive animals with DNA from hunter-collected feces: four methods for brown bears. Cons. Biol. 19(1), 150-161. https://doi.org/10.1111/j.1523-1739.2005.00549.x

Nichols, J.D. and Williams, B.K. (2006). Monitoring for conservation. Trends Ecol. Evol. 21(12), 668-673. https://doi.org/10.1016/j.tree.2006.08.007

Otis, D.L., Burnham, K.P., White, G.C. and Anderson, D.R. (1978). Statistical inference from capture data on closed animal populations. Wildlife Monographs (62), 3-135.

Solberg, K.H., Bellemain, E., Drageset, O.M., Taberlet, P. and Swenson, J.E. (2006). An evaluation of field and non-invasive genetic methods to estimate brown bear (Ursus arctos) population size. Biol. Conserv. 128(2), 158-168. https://doi.org/10.1016/j.biocon.2005.09.025

Vanpé C, Piédallu B, Quenette P-Y, Sentilles J, Queney G, Palazón S, Jordana IA, Jato R, Elósegui Irurtia MM, de la Torre JS, and Gimenez O (2022) Estimating abundance of a recovering transboundary brown bear population with capture-recapture models. bioRxiv, 2021.12.08.471719, ver. 4 recommended and peer-reviewed by PCI Ecology. https://doi.org/10.1101/2021.12.08.471719

Marine protected areas (MPA) have arisen as the main approach for conservation of marine species. Fishes, marine mammals and birds can be conservation targets that justify the implementation of these areas. However, MPAs undergo many of the problems faced by their terrestrial equivalent. One of the major concerns is that these conservation areas are spatially constrained, by logistic reasons, and many times these constraints caused that key areas for the species (reproductive sites, refugees, migration) fall outside the limits, making conservation efforts even more difficult. Lambert et al. [1] evaluate at what point the Bay of Biscay MPA contains key ecological areas for several emblematic species. The evaluation incorporated a spatio-temporal dimension. To evaluate these ideas, authors evaluate two population descriptors: aggregation and persistence of several species of cetaceans and seabirds.
The authors determined that despite the MPA contains key areas for some species, for many others the key areas fall outside the MPA (aggregation sites) or observed aggregation sites are poorly persistent in time. They found that aggregation and persistence behave as two uncorrelated descriptors of the spatio-temporal distribution of populations. Variability of both characteristics was species-specific, but in all cases the message is clear: both features must be taken into account to evaluate the effectiveness of MPAs. Both conclusions pointed out to the difficulties that a strategy based on MPAs could face when the target are those species with low aggregation or those where key sites show low persistence in time.
Conceptually, the manuscript and its conclusions are very interesting, specially its recommendation of including temporal variability of species abundances and aggregation in the design of MPAs. However, despite the clear biological importance of persistence and aggregation of the conservation targets for the design of a MPA, its implementation will still be an extremely complex task. A first constraint is that important areas for one species could not be relevant for others, making the design of the MPA difficult because the more target species we include the larger the area needed for the MPA. As a consequence, the management of the MPA turns difficult and expensive as the area increases. These increased costs could be a key point for accepting/rejecting the implementation of these MPAs for governments. Also larger areas could imply highest level of conflict with local communities or stakeholders. In many the inclusion inside MPAs of areas with traditional social or economic use will be a major source of conflict with the people.
Despite these difficulties, the results of Lambert et al. [1] give us a key message for improving MPA’s design. The best strategy for including their conclusions in the effective implementation of these areas will be the next target in conservation research.

References

[1] Lambert, C., Dorémus, G. and V. Ridoux (2020) The persistence in time of distributional patterns in marine megafauna impacts zonal conservation strategies. bioRxiv, 790634, ver. 3 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/790634