Which biological traits modulate species distribution has historically been and still is one of the core questions of the macroecology and biogeography agenda [1, 2]. As most of the Earth surface has been modified by human activities [3] understanding the strategies that allow species to inhabit human-dominated landscapes will be key to explain species geographic distribution in the Anthropocene. In this vein, Logan et al. [4] are working on a long-term and integrative project aimed to investigate how great-tailed grackles rapidly expanded their geographic range into North America [4]. Particularly, they want to determine which is the role of behavioral flexibility, i.e. an individual’s ability to modify its behavior when circumstances change based on learning from previous experience [5], in rapid geographic range expansions. The authors are already working in a set of complementary questions described in pre-registrations that have already been recommended at PCI Ecology: (1) Do individuals with greater behavioral flexibility rely more on causal cognition [6]? (2) Which are the mechanisms that lead to behavioral flexibility [7]? (3) Does the manipulation of behavioral flexibility affect exploration, but not boldness, persistence, or motor diversity [8]? (4) Can context changes improve behavioral flexibility [9]?
In this new pre-registration, they aim to determine whether the more behaviorally flexible individuals have more flexible foraging behaviors (i.e. use a wider variety of foraging techniques in the wild and eat a larger number of different foods), habitat use (i.e. higher microhabitat richness) and social relationships (i.e., are more likely to have a greater number of bonds or stronger bonds with other individuals; [4]). The project is ambitious, combining both the experimental characterization of individuals’ behavioral flexibility and the field characterization of the foraging and social behavior of those individuals and of wild ones.
The current great-tailed grackles project will be highly relevant to understand rapid geographic range expansions in a changing world. In this vein, this pre-registration will particularly help to go one step further in our understanding of behavioral flexibility as a determinant of species geographic distribution. Logan et al. [4] pre-registration is very well designed, main and alternative hypotheses have been thought and written and methods are presented in a very detailed way, which includes the R codes that authors will use in their analyses. Authors have answered in a very detailed way each comment that reviewers have pointed out and modified the pre-registration accordingly, which we consider highly improved the quality of this work. That is why we strongly recommend this pre-registration and look forward to see the results.

References

[1] Gaston K. J. (2003) The structure and dynamics of geographic ranges. Oxford series in Ecology and Evolution. Oxford University Press, New York.
[2] Castro-Insua, A., Gómez‐Rodríguez, C., Svenning, J.C., and Baselga, A. (2018) A new macroecological pattern: The latitudinal gradient in species range shape. Global ecology and biogeography, 27(3), 357-367. doi: 10.1111/geb.12702
[3] Newbold, T., Hudson, L. N., Hill, S. L. L., Contu, S., Lysenko, I., Senior, R. A., et al. (2015). Global effects of land use on local terrestrial biodiversity. Nature, 520(7545), 45–50. doi: 10.1038/nature14324
[4] Logan CJ, McCune K, Bergeron L, Folsom M, Lukas D. (2019). Is behavioral flexibility related to foraging and social behavior in a rapidly expanding species? In principle recommendation by Peer Community In Ecology. http://corinalogan.com/Preregistrations/g_flexforaging.html
[5] Mikhalevich, I., Powell, R., and Logan, C. (2017). Is Behavioural Flexibility Evidence of Cognitive Complexity? How Evolution Can Inform Comparative Cognition. Interface Focus 7: 20160121. doi: 10.1098/rsfs.2016.0121.
[6] Fronhofer, E. (2019) From cognition to range dynamics: advancing our understanding of macroecological patterns. Peer Community in Ecology, 100014. doi: 10.24072/pci.ecology.100014
[7] Vogel, E. (2019) Adapting to a changing environment: advancing our understanding of the mechanisms that lead to behavioral flexibility. Peer Community in Ecology, 100016. doi: 10.24072/pci.ecology.100016
[8] Van Cleve, J. (2019) Probing behaviors correlated with behavioral flexibility. Peer Community in Ecology, 100020. doi: 10.24072/pci.ecology.100020
[9] Coulon, A. (2019) Can context changes improve behavioral flexibility? Towards a better understanding of species adaptability to environmental changes. Peer Community in Ecology, 100019. doi: 10.24072/pci.ecology.100019

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

Humans are exploiting biological resources since thousands of years. Exploitation of biological resources has become particularly intense since the beginning of the 20th century and the steep increase in the worldwide human population size. Marine and freshwater fishes are not exception to that rule, and they have been (and continue to be) strongly harvested as a source of proteins for humans. For some species, fishery has been so intense that natural stocks have virtually collapsed in only a few decades. The worst example begin that of the Northwest Atlantic cod that has declined by more than 95% of its historical biomasses in only 20-30 years of intensive exploitation (Frank et al. 2005). These rapid and steep changes in biomasses have huge impacts on the entire ecosystems since species targeted by fisheries are often at the top of trophic chains (Frank et al. 2005). 

Beyond demographic impacts, fisheries also have evolutionary impacts on populations, which can also indirectly alter ecosystems (Uusi-Heikkilä et al. 2015; Palkovacs et al. 2018). Fishermen generally focus on the largest specimens, and hence exert a strong selective pressure against these largest fish (which is called “harvest selection”). There is now ample evidence that harvest selection can lead to rapid evolutionary changes in natural populations toward small individuals (Kuparinen & Festa-Bianchet 2017). These evolutionary changes are of course undesirable from a human perspective, and have attracted many scientific questions. Nonetheless, the consequence of harvest selection is not always observable in natural populations, and there are cases in which no phenotypic change (or on the contrary an increase in mean body size) has been observed after intense harvest pressures. In a conceptual Essay, Edeline and Loeuille (Edeline & Loeuille 2020) propose novel ideas to explain why the evolutionary consequences of harvest selection can be so diverse, and how a cross talk between ecological and evolutionary dynamics can explain patterns observed in natural stocks.

 The general and novel concept proposed by Edeline and Loeuille is actually as old as Darwin’s book; The Origin of Species (Darwin 1859). It is based on the simple idea that natural selection acting on harvested populations can actually be strong, and counter-balance (or on the contrary reinforce) the evolutionary consequence of harvest selection. Although simple, the idea that natural and harvest selection are jointly shaping contemporary evolution of exploited populations lead to various and sometimes complex scenarios that can (i) explain unresolved empirical patterns and (ii) refine predictions regarding the long-term viability of exploited populations. 

The Edeline and Loeuille’s crafty inspiration is that natural selection acting on exploited populations is itself an indirect consequence of harvest (Edeline & Loeuille 2020). They suggest that, by modifying the size structure of populations (a key parameter for ecological interactions), harvest indirectly alters interactions between populations and their biotic environment through competition and predation, which changes the ecological theatre and hence the selective pressures acting back to populations. They named this process “size-dependent eco-evolutionary feedback loops” and develop several scenarios in which these feedback loops ultimately deviate the evolutionary outcome of harvest selection from expectation. The scenarios they explore are based on strong theoretical knowledge, and range from simple ones in which a single species (the harvest species) is evolving to more complex (and realistic) ones in which multiple (e.g. the harvest species and its prey) species are co-evolving.

I will not come into the details of each scenario here, and I will let the readers (re-)discovering the complex beauty of biological life and natural selection. Nonetheless, I will emphasize the importance of considering these eco-evolutionary processes altogether to fully grasp the response of exploited populations. Edeline and Loeuille convincingly demonstrate that reduced body size due to harvest selection is obviously not the only response of exploited fish populations when natural selection is jointly considered (Edeline & Loeuille 2020). On the contrary, they show that –under some realistic ecological circumstances relaxing exploitative competition due to reduced population densities- natural selection can act antagonistically, and hence favour stable body size in exploited populations. Although this seems further desirable from a human perspective than a downsizing of exploited populations, it is actually mere window dressing as Edeline and Loeuille further showed that this response is accompanied by an erosion of the evolvability –and hence a lowest probability of long-term persistence- of these exploited populations.

Humans, by exploiting biological resources, are breaking the relative equilibrium of complex entities, and the response of populations to this disturbance is itself often complex and heterogeneous. In this Essay, Edeline and Loeuille provide –under simple terms- the theoretical and conceptual bases required to improve predictions regarding the evolutionary responses of natural populations to exploitation by humans (Edeline & Loeuille 2020). An important next step will be to generate data and methods allowing confronting the empirical reality to these novel concepts (e.g. (Monk et al. 2021), so as to identify the most likely evolutionary scenarios sustaining biological responses of exploited populations, and hence to set the best management plans for the long-term sustainability of these populations.

References

Darwin, C. (1859). On the Origin of Species by Means of Natural Selection. John Murray, London.

Edeline, E. & Loeuille, N. (2021) Size-dependent eco-evolutionary feedbacks in fisheries. bioRxiv, 2020.04.03.022905, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: https://doi.org/10.1101/2020.04.03.022905

Frank, K.T., Petrie, B., Choi, J. S. & Leggett, W.C. (2005). Trophic Cascades in a Formerly Cod-Dominated Ecosystem. Science, 308, 1621–1623. doi: https://doi.org/10.1126/science.1113075

Kuparinen, A. & Festa-Bianchet, M. (2017). Harvest-induced evolution: insights from aquatic and terrestrial systems. Philos. Trans. R. Soc. B Biol. Sci., 372, 20160036. doi: https://doi.org/10.1098/rstb.2016.0036

Monk, C.T., Bekkevold, D., Klefoth, T., Pagel, T., Palmer, M. & Arlinghaus, R. (2021). The battle between harvest and natural selection creates small and shy fish. Proc. Natl. Acad. Sci., 118, e2009451118. doi: https://doi.org/10.1073/pnas.2009451118 

Palkovacs, E.P., Moritsch, M.M., Contolini, G.M. & Pelletier, F. (2018). Ecology of harvest-driven trait changes and implications for ecosystem management. Front. Ecol. Environ., 16, 20–28. doi: https://doi.org/10.1002/fee.1743

Uusi-Heikkilä, S., Whiteley, A.R., Kuparinen, A., Matsumura, S., Venturelli, P.A., Wolter, C., et al. (2015). The evolutionary legacy of size-selective harvesting extends from genes to populations. Evol. Appl., 8, 597–620. doi: https://doi.org/10.1111/eva.12268

One of the long-standing questions in evolutionary ecology is on the mechanisms involved in arms race coevolution. One way to address this question is to understand the conditions under which one species evolves traits in response to the presence of a second species and so on. However, specialized pairwise interactions are by far less common in nature than interactions involving a higher number of interacting species (Bascompte, Jordano 2013). While interactions between large sets of species are the norm rather than the exception in mutualistic (pollination, seed dispersal), and antagonist (herbivory, parasitism) relationships, few is known on the way species identify, process, and respond to information provided by other interacting species under field conditions (Schaefer, Ruxton 2011). 

Zu et al. (2020) addressed this general question by developing an interesting information theory-based approach that hypothesized conditional entropy in chemical communication plays a role as proxy of fitness in plant-herbivore communities. More specifically, plant fitness was assumed to be related to the efficiency to code signals by plant species, and herbivore fitness to the capacity to decode plant signals. In this way, from the plant perspective, the elaboration of plant signals that elude decoding by herbivores is expected to be favored, as herbivores are expected to attack plants with simple chemical signals. The empirical observation upon which the model was tested was the redundancy in volatile organic compounds (VOC) found across plant species in a plant-herbivore community. Interestingly, Zu et al.’s model predicted successfully that VOC redundancy in the plant community associates with increased conditional entropy, which conveys herbivore confusion and plant protection against herbivory. In this way, plant species that evolve VOCs already present in the community might be benefitted, ultimately leading to the patterns of VOC redundancy commonly observed in nature.

Bass & Kessler performed a series of interesting observations on Zu et al. (2020), that can be organized along three lines of reasoning. First, from an evolutionary perspective, Bass & Kessler note the important point that accepting that conditional information entropy, estimated from the contribution of every plant species to volatile redundancy implies that average plant fitness seems to depend on community-level properties (i.e., what the other species in the community are doing) rather than on population-level characteristics (I.e., what the individuals belonging a population are doing). While the level at which selection acts upon is a longstanding debate (e.g., Goodnight, 1990; Williams, 1992), the model seems to contradict one of the basic tenets of Darwinian evolution. The extent to which this important observation invalidates the contribution of Zu et al. (2020) is open to scrutiny. However, one can indulge the evolutionary criticism by arguing that every theoretical model performs a number of assumptions to preserve the simplicity of analyses. Furthermore, even accepting the criticism, the overall information-based framework is valuable as it provides a fresh perspective to the way coding and decoding chemical information in plant-herbivore interactions may result in arm race coevolution. The question to be assessed by members of the scientific community is how strong the evolutionary assumptions are to be acceptable. A second line of reasoning involves consideration of additional routes of chemical information transfer. If chemical volatiles are involved in another ecological function unrelated to arm race (as they are) such as toxicity, crypsis, aposematism, etc., the conditional information indices considered as proxy to plant and herbivore fitness may be only secondarily related to arms race. This is an interesting observation, which suggests that VOC production may have more than one ecological function, as it often happens in “pleiotropic” traits (Strauss, Irwin 2004). This is an exciting avenue for future research. Finally, a third category of comments involves the relationship between conditional information entropy and plant and herbivore fitness. Bass & Kessler developed a Bayesian treatment of the community-level information developed by Zu et al. (2020) that permitted to estimate fitness on a species rather than community level. Their results revealed that community conditional entropies fail to align with species-level indices, suggesting that conclusions of Strauss & Irwin (2004) are not commensurate with fitness at the species level, where the analysis seems to be pertinent. In general, I strongly recommend Bass & Kessler’s contribution as it provides a series of observations and new perspectives to Zu et al. (2020). Rather than restricting their manuscript to blind criticisms, Bass & Kessler provides new interesting perspectives, which is always welcome as it improves the value and scope of the original work.

References

Bascompte J, Jordano P (2013) Mutualistic Networks. Princeton University Press. https://doi.org/10.23943/princeton/9780691131269.001.0001

Bass E, Kessler A (2022) Comment on “Information arms race explains plant-herbivore chemical communication in ecological communities.” EcoEvoRxiv, ver. 8 peer-reviewed and recommended by Peer Community in Ecology.  https://doi.org/10.32942/osf.io/xsbtm

Goodnight CJ (1990) Experimental Studies of Community Evolution I: The Response to Selection at the Community Level. Evolution, 44, 1614–1624. https://doi.org/10.1111/j.1558-5646.1990.tb03850.x

Schaefer HM, Ruxton GD (2011) Plant-Animal Communication. Oxford University Press, Oxford. https://doi.org/10.1093/acprof:osobl/9780199563609.001.0001

Strauss SY, Irwin RE (2004) Ecological and Evolutionary Consequences of Multispecies Plant-Animal Interactions. Annual Review of Ecology, Evolution, and Systematics, 35, 435–466. https://doi.org/10.1146/annurev.ecolsys.35.112202.130215

Williams GC (1992) Natural Selection: Domains, Levels, and Challenges. Oxford University Press, Oxford, New York.

Zu P, Boege K, del-Val E, Schuman MC, Stevenson PC, Zaldivar-Riverón A, Saavedra S (2020) Information arms race explains plant-herbivore chemical communication in ecological communities. Science, 368, 1377–1381. https://doi.org/10.1126/science.aba2965

Conservation biology is strongly rooted in the theory of island biogeography (TIB). In island systems where the ocean constitutes the inhospitable matrix, TIB predicts that species richness increases with island size as extinction rates decrease with island area (the species-area relationship, SAR), and species richness increases with connectivity as colonisation rates decrease with island isolation (the species-isolation relationship, SIR)[1]. In conservation biology, patches of habitat (habitat islands) are often regarded as analogous to islands within an unsuitable matrix [2], and SAR and SIR concepts have received much attention as habitat loss and habitat fragmentation are increasingly threatening biodiversity [3,4].
The existence of SAR in patch-matrix systems has been confirmed in several studies, while the relative importance of SIR remains debated [2,5] and empirical evidence is mixed. For example, Thiele et al. [6] showed that connectivity effects are trait specific and more important to explain species richness of short-distant dispersers and of specialist species for which the matrix is less permeable. Some authors have also cautioned that the relative support for or against the existence of SIR may depend on methodological decisions related to connectivity metrics, patch classification, scaling decisions and sample size [7].
In this preprint, Laroche and colleagues [8] argue that methodological limits should be fully understood before questioning the validity of SIR in patch-matrix systems. In consequence, they used a virtual ecologist approach [9] to qualify different methodological aspects and derive good practice guidelines related to patch delineation, patch connectivity indices, and scaling of indices with species dispersal distance.
Laroche et al. [8] simulated spatially-explicit neutral meta-communities with up to 100 species in artificial fractal (patch-matrix) landscapes. Each habitat cell could hold up to 100 individuals. In each time step, some individuals died and were replaced by an individual from the regional species pool depending on relative local and regional abundance as well as dispersal distance to the nearest source habitat cell. Different scenarios were run with varying degrees of spatial autocorrelation in the fractal landscape (determining the clumpiness of habitat cells), the proportion of suitable habitat, and the species dispersal distances (with all species showing the same dispersal distance). Laroche and colleagues then sampled species richness in the simulated meta-communities, computed different local connectivity indices for the simulated landscapes (Buffer index with different radii, dIICflux index and dF index, and, finally, related species richness to connectivity.
The complex simulations allowed Laroche and colleagues [8] to test how methodological choices and landscape features may affect SIR. Overall, they found that patch delineation is crucial and should be fine enough to exclude potential within-patch dispersal limitations, and the scaling of the connectivity indices (in simplified words, the window of analyses) should be tailored to the dispersal distance of the species group. Of course, tuning the scaling parameters will be more complicated when dispersal distances vary across species but overall these results corroborate empirical findings that SIR effects are trait specific [6]. Additionally, the results by Laroche and colleagues [8] indicated that indices based on Euclidian rather than topological distance are more performant and that evidence of SIR is more likely if Buffer indices are highly variable between sampled patches.
Although the study is very technical due to the complex simulation approach and the different methods tested, I hope it will not only help guiding methodological choices but also inspire ecologists to further test or even revisit SIR (and SAR) hypotheses for different systems. Also, Laroche and colleagues propose many interesting avenues that could still be explored in this context, for example determining the optimal grid resolution for the patch delineation in empirical studies.

References

[1] MacArthur, R.H. and Wilson, E.O. (1967) The theory of island biogeography. Princeton University Press, Princeton.
[2] Fahrig, L. (2013) Rethinking patch size and isolation effects: the habitat amount hypothesis. Journal of Biogeography, 40(9), 1649-1663. doi: 10.1111/jbi.12130
[3] Hanski, I., Zurita, G.A., Bellocq, M.I. and Rybicki J (2013) Species–fragmented area relationship. Proceedings of the National Academy of Sciences U.S.A., 110(31), 12715-12720. doi: 10.1073/pnas.1311491110
[4] Giladi, I., May, F., Ristow, M., Jeltsch, F. and Ziv, Y. (2014) Scale‐dependent species–area and species–isolation relationships: a review and a test study from a fragmented semi‐arid agro‐ecosystem. Journal of Biogeography, 41(6), 1055-1069. doi: 10.1111/jbi.12299
[5] Hodgson, J.A., Moilanen, A., Wintle, B.A. and Thomas, C.D. (2011) Habitat area, quality and connectivity: striking the balance for efficient conservation. Journal of Applied Ecology, 48(1), 148-152. doi: 10.1111/j.1365-2664.2010.01919.x
[6] Thiele, J., Kellner, S., Buchholz, S., and Schirmel, J. (2018) Connectivity or area: what drives plant species richness in habitat corridors? Landscape Ecology, 33, 173-181. doi: 10.1007/s10980-017-0606-8
[7] Vieira, M.V., Almeida-Gomes, M., Delciellos, A.C., Cerqueira, R. and Crouzeilles, R. (2018) Fair tests of the habitat amount hypothesis require appropriate metrics of patch isolation: An example with small mammals in the Brazilian Atlantic Forest. Biological Conservation, 226, 264-270. doi: 10.1016/j.biocon.2018.08.008
[8] Laroche, F., Balbi, M., Grébert, T., Jabot, F. and Archaux, F. (2020) Three points of consideration before testing the effect of patch connectivity on local species richness: patch delineation, scaling and variability of metrics. bioRxiv, 640995, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/640995
[9] Zurell, D., Berger, U., Cabral, J.S., Jeltsch, F., Meynard, C.N., Münkemüller, T., Nehrbass, N., Pagel, J., Reineking, B., Schröder, B. and Grimm, V. (2010) The virtual ecologist approach: simulating data and observers. Oikos, 119(4), 622-635. doi: 10.1111/j.1600-0706.2009.18284.x