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12 Mar 2023
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Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities.

Processing environmental DNA samples in turbid waters from coastal lagoons

Recommended by based on reviews by David Murray-Stoker and Rutger De Wit

Coastal lagoons are among the most productive natural ecosystems on Earth. These relatively closed basins are important habitats and nursery for endemic and endangered species and are extremely vulnerable to nutrient input from the surrounding catchment; therefore, they are highly susceptible to anthropogenic influence, pollution and invasion (Pérez-Ruzafa et al., 2019). In general, coastal lagoons exhibit great spatial and temporal variability in their physicochemical water characteristics due to the sporadic mixing of freshwater with marine influx. One of the alternatives for monitoring communities or target species in aquatic ecosystems is the environmental DNA (eDNA), since overcomes some limitations from traditional methods and enables the investigation of multiple species from a single sample (Thomsen and Willerslev, 2015). In coastal lagoons, where the water turbidity is highly variable, there is a major challenge for monitoring the eDNA because filtering turbid water to obtain the eDNA is problematic (filters get rapidly clogged, there is organic and inorganic matter accumulation, etc.). 

The study by Turba et al. (2023) analyzes different ways of dealing with eDNA sampling and processing in turbid waters and sediments of coastal lagoons, and offers guidelines to obtain unbiased results from the subsequent sequencing using 12S (fish) and 16S (Bacteria and Archaea) universal primers. They analyzed the effect on taxa detection of: i) freezing or not prior to filtering; ii) freezing prior to centrifugation to obtain a sample pellet; and iii) using frozen sediment samples as a proxy of what happens in the water. The authors propose these different alternatives (freeze, do not freeze, sediment sampling) because they consider that they are the easiest to carry out. They found that freezing before filtering using a 3 µm pore size filter had no effects on community composition for either primer, and therefore it is a worthwhile approach for comparison of fish, bacteria and archaea in this kind of system. However, significantly different bacterial community composition was found for sediment compared to water samples. Also, in sediment samples the replicates showed to be more heterogeneous, so the authors suggest increasing the number of replicates when using sediment samples. Something that could be a concern with the study is that the rarefaction curves based on sequencing effort for each protocol did not saturate in any case, this being especially evident in sediment samples. The authors were aware of this, used the slopes obtained from each curve as a measure of comparison between samples and considering that the sequencing depth did not meet their expectations, they managed to achieve their goal and to determine which protocol is the most promising for eDNA monitoring in coastal lagoons. Although there are details that could be adjusted in relation to this item, I consider that the approach is promising for this type of turbid system.


Pérez-Ruzafa A, Campillo S, Fernández-Palacios JM, García-Lacunza A, García-Oliva M, Ibañez H, Navarro-Martínez PC, Pérez-Marcos M, Pérez-Ruzafa IM, Quispe-Becerra JI, Sala-Mirete A, Sánchez O, Marcos C (2019) Long-Term Dynamic in Nutrients, Chlorophyll a, and Water Quality Parameters in a Coastal Lagoon During a Process of Eutrophication for Decades, a Sudden Break and a Relatively Rapid Recovery. Frontiers in Marine Science, 6.

Thomsen PF, Willerslev E (2015) Environmental DNA – An emerging tool in conservation for monitoring past and present biodiversity. Biological Conservation, 183, 4–18.

Turba R, Thai GH, Jacobs DK (2023) Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities. bioRxiv, 2022.06.17.495388, ver. 2 peer-reviewed and recommended by Peer Community in Ecology.

Different approaches to processing environmental DNA samples in turbid waters have distinct effects for fish, bacterial and archaea communities.Rachel Turba, Glory H. Thai, and David K Jacobs<p style="text-align: justify;">Coastal lagoons are an important habitat for endemic and threatened species in California that have suffered impacts from urbanization and increased drought. Environmental DNA has been promoted as a way to aid in th...Biodiversity, Community genetics, Conservation biology, Freshwater ecology, Marine ecology, Molecular ecologyClaudia Piccini David Murray-Stoker2022-06-20 20:31:51 View
20 Feb 2019
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Differential immune gene expression associated with contemporary range expansion of two invasive rodents in Senegal

Are all the roads leading to Rome?

Recommended by based on reviews by Nadia Aubin-Horth and 1 anonymous reviewer

Identifying the factors which favour the establishment and spread of non-native species in novel environments is one of the keys to predict - and hence prevent or control - biological invasions. This includes biological factors (i.e. factors associated with the invasive species themselves), and one of the prevailing hypotheses is that some species traits may explain their impressive success to establish and spread in novel environments [1]. In animals, most research studies have focused on traits associated with fecundity, age at maturity, level of affiliation to humans or dispersal ability for instance. The “composite picture” of the perfect (i.e. successful) invader that has gradually emerged is a small-bodied animal strongly affiliated to human activities with high fecundity, high dispersal ability and a super high level of plasticity. Of course, the story is not that simple, and actually a perfect invader sometimes – if not often- takes another form… Carrying on to identify what makes a species a successful invader or not is hence still an important research axis with major implications.
In this manuscript, Charbonnel and collaborators [2] provide an interesting opportunity to gain novel insights into our understanding of (the) traits underlying invasion success. They nicely combine the power of Next-Generation Sequencing (NGS) with a clever comparative approach of two closely-related invasive rodents (the house mouse Mus musculus and the black rat Rattus rattus) in a common environment. They use this experimental design to test the appealing hypothesis that pathogens may be actors of the story, and may indirectly explain why some non-native species are so successful in invading novel habitats.
It is generally assumed that the community of pathogens encountered by non-native species in novel environments is different from that of their native area. On the one hand (the enemy-release hypothesis), it can be hypothesized that non-native species, when they arrive into a novel environment, will be relaxed from the pressure imposed by their native pathogens because local pathogens are not adapted (and hence do not infect) to this novel host. Because immune defence against pathogens is highly costly, non-native species establishing into a novel environment could hence reallocate these costs to other functions such as fecundity or dispersal apparatus. This scenario has been termed the “evolution of increased competitive ability” (EICA) hypothesis [3]. On the other hand (the EICA-refined hypothesis [4]), one can assume that invaders will encounter new pathogens in newly established areas, and will allocate energy toward cost-effective immune pathways to permit allocating a non-negligible amount of energy toward other functions. Finally, a last hypothesis (the “immune protection” hypothesis) assumes major changes in pathogen composition between native and invaded areas, which should lead to an overall increase in immune investment by the native species to successfully invade novel environments [4]. This last hypothesis suggests that only non-native species being able to take up the associated costs of immunity will be successful invaders.
The role of immunity in invasion success has yet been poorly investigated, mainly because of the difficulty to simultaneously analyse multiple immune pathways [4]. Charbonnel and collaborators [2] overpass this difficulty by screening all genes expressed (using a whole RNA sequencing approach) in an immune tissue: the spleen. They do so along the invasion routes of two sympatric invasive rodents in Africa and compare anciently and newly invaded areas (respectively). For one of the two species (the house mouse), they found a high number of immune-related genes to be up-regulated in newly invaded areas compared to anciently invaded areas. All categories of immune pathways (costly and cost-effective) were up-regulated, suggesting an overall increase in immune investment in the mouse, which corroborates the “immune protection” hypothesis. For the black rat, patterns of gene expression were somewhat different, with much less pronounced differentiation in gene expression between newly and anciently invaded areas. Among the few differentiated genes, a few were associated to immune responses and some of theses genes were even down-regulated in the newly invaded areas. This pattern may actually corroborate the EICA hypothesis, although it could alternatively suggest that stochastic processes (drift) associated to recent decrease in population size (which is expected during a colonisation event) are more important than selection imposed by pathogens in shaping patterns of immune gene expression.
Overall, this study [2] suggests (i) that immune-related traits are important in predicting invasion success and (ii) that two successful species with a similar invasion history and living in similar environments can use different life-history strategies to reach the same success. This later finding is particularly relevant and intriguing as it suggests that the traits and strategies deployed by species to colonise new habitats might actually be idiosyncratic, and that, if general trends actually emerge in regards of traits predicting the success of invaders, the devil might actually be into the details. Comparative studies are extremely important to identify the general rules and the specificities sustaining actual patterns, but these approaches are yet poorly used in biological invasions (at least empirically). The work presented by Charbonnel and colleagues [2] calls for future comparative studies performed at multiple spatial scales (native vs. non-native areas, anciently vs. recently invaded areas), multiple taxonomic resolutions and across multiple traits (to search for trade-offs), so that the success of invasive species can be properly understood and predicted.


[1] Jeschke, J. M., & Strayer, D. L. (2006). Determinants of vertebrate invasion success in Europe and North America. Global Change Biology, 12(9), 1608-1619. doi: 10.1111/j.1365-2486.2006.01213.x
[2] Blossey, B., & Notzold, R. (1995). Evolution of increased competitive ability in invasive nonindigenous plants: a hypothesis. Journal of Ecology, 83(5), 887-889. doi: 10.2307/2261425
[3] Charbonnel, N., Galan, M., Tatard, C., Loiseau, A., Diagne, C. A., Dalecky, A., Parrinello, H., Rialle, S., Severac, D., & Brouat, C. (2019). Differential immune gene expression associated with contemporary range expansion of two invasive rodents in Senegal. bioRxiv, 442160, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/442160
[4] Lee, K. A., & Klasing, K. C. (2004). A role for immunology in invasion biology. Trends in Ecology & Evolution, 19(10), 523-529. doi: 10.1016/j.tree.2004.07.012

Differential immune gene expression associated with contemporary range expansion of two invasive rodents in SenegalNathalie Charbonnel, Maxime Galan, Caroline Tatard, Anne Loiseau, Christophe Diagne, Ambroise Dalecky, Hugues Parrinello, Stephanie Rialle, Dany Severac and Carine Brouat<p>Background: Biological invasions are major anthropogenic changes associated with threats to biodiversity and health. What determines the successful establishment of introduced populations still remains unsolved. Here we explore the appealing as...Biological invasions, Eco-immunology & Immunity, Population ecologySimon Blanchet2018-10-14 12:21:52 View
28 Mar 2019
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Direct and transgenerational effects of an experimental heat wave on early life stages in a freshwater snail

Escargots cooked just right: telling apart the direct and indirect effects of heat waves in freashwater snails

Recommended by based on reviews by Amanda Lynn Caskenette, Kévin Tougeron and arnaud sentis

Amongst the many challenges and forms of environmental change that organisms face in our era of global change, climate change is perhaps one of the most straightforward and amenable to investigation. First, measurements of day-to-day temperatures are relatively feasible and accessible, and predictions regarding the expected trends in Earth surface temperature are probably some of the most reliable we have. It appears quite clear, in particular, that beyond the overall increase in average temperature, the heat waves locally experienced by organisms in their natural habitats are bound to become more frequent, more intense, and more long-lasting [1]. Second, it is well appreciated that temperature is a major environmental factor with strong impacts on different facets of organismal development and life-history [2-4]. These impacts have reasonably clear mechanistic underpinnings, with definite connections to biochemistry, physiology, and considerations on energetics. Third, since variation in temperature is a challenge already experienced by natural populations across their current and historical ranges, it is not a completely alien form of environmental change. Therefore, we already learnt quite a lot about it in several species, and so did the species, as they may be expected to have evolved dedicated adaptive mechanisms to respond to elevated temperatures. Last, but not least, temperature is quite amenable to being manipulated as an experimental factor.
For all these reasons, experimental studies of the consequences of increased temperature hit some of a sweetspot and are a source of very nice research, in many different organisms. The work by Leicht and Seppala [5] complements a sequence of earlier studies by this group, using the freshwater snail Lymnaea stagnalis as their model system [6-7].
In the present study, the authors investigate how a heat wave (a period of abnormally elevated temperature, here 25°C versus a normal 15°C) may have indirect effects on the next generation, through maternal effects. They question whether such indirect effects exist, and if they exist, how they compare, in terms of effect size, with the (more straightforward) direct effects observed in individuals that directly experience a heat wave. Transgenerational effects are well-known to occur following periods of physiological stress, and might thus have non negligible contributions to the overall effect of warming.
In this freshwater snail, heat has very strong direct effects: mortality increases at high temperature, but survivors grow much bigger, with a greater propensity to lay eggs and a (spectacular) three-fold increase in the number of eggs laid [6]. Considering that, it is easy to consider that transgenerational effects should be small game. And indeed, the present study also observes the big and obvious direct effects of elevated temperature: higher mortality, but greater propensity to oviposit. However, it was also found that the eggs were smaller if from mothers exposed to high temperature, with a correspondingly smaller size of hatchlings. This suggests that a heat wave causes the snails to lay more eggs, but smaller ones, reminiscent of a size-number trade-off. Unfortunately, clutch size could not be measured in this experiment, so this cannot be investigated any further. For this trait, the indirect effect may indeed be regarded as small game : eggs and hatchlings were about 15 % smaller, an effect size pretty small compared to the mammoth direct positive effect of temperature on shell length (see Figure 4 ; and also [6]). The same is true for developmental time (Figure 3).
However, for some traits the story was different. In particular, it was found that the (smaller) eggs produced from heated mothers were more likely to hatch by almost 10% (Figure 2). Here the indirect effect not only goes against the direct effect (hatching rate is lower at high temperature), but it also has similar effect size. As a consequence, taking into account both the indirect and direct effects, hatching success is essentially the same at 15°C and 25°C (Figure 2). Survival also had comparable effect sizes for direct and indirect effects. Indeed, survival was reduced by about 20% regardless of whom endured the heat stress (the focal individual or her mother; Figure 4). Interestingly, the direct and indirect effects were not quite cumulative: if a mother experienced a heat wave, heating up the offspring did not do much more damage, as though the offspring were ‘adapted’ to the warmer conditions (but keep in mind that, surprisingly, the authors’ stats did not find a significant interaction; Table 2).
At the end of the day, even though at first heat seems a relatively simple and understandable component of environmental change, this study shows how varied its effects can be effects on different components of individual fitness. The overall impact most likely is a mix of direct and indirect effects, of shifts along allocation trade-offs, and of maladaptive and adaptive responses, whose overall ecological significance is not so easy to grasp. That said, this study shows that direct and indirect (maternal) effects can sometimes go against one another and have similar intensities. Indirect effects should therefore not be overlooked in this kind of studies. It also gives a hint of what an interesting challenge it is to understand the adaptive or maladaptive nature of organism responses to elevated temperatures, and to evaluate their ultimate fitness consequences.


[1] Meehl, G. A., & Tebaldi, C. (2004). More intense, more frequent, and longer lasting heat waves in the 21st century. Science (New York, N.Y.), 305(5686), 994–997. doi: 10.1126/science.1098704
[2] Adamo, S. A., & Lovett, M. M. E. (2011). Some like it hot: the effects of climate change on reproduction, immune function and disease resistance in the cricket Gryllus texensis. The Journal of Experimental Biology, 214(Pt 12), 1997–2004. doi: 10.1242/jeb.056531
[3] Deutsch, C. A., Tewksbury, J. J., Tigchelaar, M., Battisti, D. S., Merrill, S. C., Huey, R. B., & Naylor, R. L. (2018). Increase in crop losses to insect pests in a warming climate. Science (New York, N.Y.), 361(6405), 916–919. doi: 10.1126/science.aat3466
[4] Sentis, A., Hemptinne, J.-L., & Brodeur, J. (2013). Effects of simulated heat waves on an experimental plant–herbivore–predator food chain. Global Change Biology, 19(3), 833–842. doi: 10.1111/gcb.12094
[5] Leicht, K., & Seppälä, O. (2019). Direct and transgenerational effects of an experimental heat wave on early life stages in a freshwater snail. BioRxiv, 449777, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/449777
[6] Leicht, K., Seppälä, K., & Seppälä, O. (2017). Potential for adaptation to climate change: family-level variation in fitness-related traits and their responses to heat waves in a snail population. BMC Evolutionary Biology, 17(1), 140. doi: 10.1186/s12862-017-0988-x
[7] Leicht, K., Jokela, J., & Seppälä, O. (2013). An experimental heat wave changes immune defense and life history traits in a freshwater snail. Ecology and Evolution, 3(15), 4861–4871. doi: 10.1002/ece3.874

Direct and transgenerational effects of an experimental heat wave on early life stages in a freshwater snailKatja Leicht, Otto Seppälä<p>Global climate change imposes a serious threat to natural populations of many species. Estimates of the effects of climate change‐mediated environmental stresses are, however, often based only on their direct effects on organisms, and neglect t...Climate changevincent calcagno2018-10-22 22:19:22 View
30 May 2024
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Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons

Untangling Eutrophication Effects on Coastal Lagoon Ecosystems

Recommended by ORCID_LOGO based on reviews by Kaylee P. Smit, Matthew J. Pruden and Kendyl Wright

Disentangling the effects on ecosystem structure and functioning of natural and human-induced impacts in transitional waters is a great challenge in coast ecology. This is due to the observation that the ecosystems of transitional waters are naturally dynamic systems with characteristics of stressed systems. For example, the benthic communities present low species richness and high abundance of species with a high tolerance to variations, e.g., salinity. This general observation is known as the paradigm of the “Transitional Waters Quality Paradox” (Zaldívar et al., 2008) derived from the previously described “Estuarine Quality Paradox” (Elliott and Quintino, 2007). 

In Jones et al. (2024) “Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons”, a great diversity of lagoons is analyzed to disentangle the effects of eutrophication from those of natural environmental variability on benthic macroinvertebrates and understanding the links between environmental variables affecting benthic macroinvertebrates. These authors use a very elegant set of numerical approaches, including correlograms, linear models and variance partitioning. They apply this suite to a dataset of macrobenthic invertebrate abundances and environmental variables from 29 Mediterranean coastal lagoons in France.

Through this suite of analyses, they demonstrate the strong complexity of the mechanisms interplaying in a situation of eutrophication on lagoon macrobenthos. The mechanisms involved are direct, like toxicity, or indirect, for example, through modifications of the sediment's biogeochemistry. Such a result on the different interactions involved is very important in the context of the search for indicators to define ecosystem status. Improving the definition of metrics is essential in environmental management decisions.


Elliott, M. and Quintino, V. (2007) The estuarine quality paradox, environmental homeostasis and the difficulty of detecting anthropogenic stress in naturally stressed areas. Marine Pollution Bulletin 54, 640–645.

Jones et al. (2024) Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoons bioRxiv, 2022.08.18.504439, ver. 4 peer-reviewed and recommended by Peer Community in Ecology.

Zaldívar, J. (2008). Eutrophication in transitional waters: an overview.

Disentangling the effects of eutrophication and natural variability on macrobenthic communities across French coastal lagoonsAuriane G. Jones, Gauthier Schaal, Aurélien Boyé, Marie Creemers, Valérie Derolez, Nicolas Desroy, Annie Fiandrino, Théophile L. Mouton, Monique Simier, Niamh Smith, Vincent Ouisse<p style="text-align: justify;">Coastal lagoons are transitional ecosystems that host a unique diversity of species and support many ecosystem services. Owing to their position at the interface between land and sea, they are also subject to increa...Biodiversity, Community ecology, Ecosystem functioning, Marine ecologyNathalie Niquil Matthew J. Pruden2023-09-08 11:26:01 View
01 Mar 2022
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Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiring

How to evaluate and interpret the contribution of species turnover and interaction rewiring when comparing ecological networks?

Recommended by ORCID_LOGO based on reviews by Ignasi Bartomeus and 1 anonymous reviewer

A network includes a set of vertices or nodes (e.g., species in an interaction network), and a set of edges or links (e.g., interactions between species). Whether and how networks vary in space and/or time are questions often addressed in ecological research. 

Two ecological networks can differ in several extents: in that species are different in the two networks and establish new interactions (species turnover), or in that species that are present in both networks establish different interactions in the two networks (rewiring). The ecological meaning of changes in network structure is quite different according to whether species turnover or interaction rewiring plays a greater role. Therefore, much attention has been devoted in recent years on quantifying and interpreting the relative changes in network structure due to species turnover and/or rewiring.

Poisot et al. (2012) proposed to partition the global variation in structure between networks, \( \beta_{WN} \) (WN = Whole Network) into two terms: \( \beta_{OS} \) (OS = Only Shared species) and \( \beta_{ST} \) (ST = Species Turnover), such as \( \beta_{WN} = \beta_{OS} + \beta_{ST} \).

The calculation lays on enumerating the interactions between species that are common or not to two networks, as illustrated on Figure 1 for a simple case. Specifically, Poisot et al. (2012) proposed to use a Sorensen type measure of network dissimilarity, i.e., \( \beta_{WN} = \frac{a+b+c}{(2a+b+c)/2} -1=\frac{b+c}{2a+b+c} \) , where \( a \) is the number of interactions shared between the networks, while \( b \) and \( c \) are interaction numbers unique to one and the other network, respectively. \( \beta_{OS} \) is calculated based on the same formula, but only for the subnetworks including the species common to the two networks, in the form \( \beta_{OS} = \frac{b_{OS}+c_{OS}}{2a_{OS}+b_{OS}+c_{OS}} \) (e.g., Fig. 1). \( \beta_{ST} \) is deduced by subtracting \( \beta_{OS} \) from \( \beta_{WN} \) and represents in essence a "dissimilarity in interaction structure introduced by dissimilarity in species composition" (Poisot et al. 2012).

Figure 1. Ecological networks exemplified in Fründ (2021) and discussed in Poisot (2022). a is the number of shared links (continuous lines in right figures), while b+c is the number of edges unique to one or the other network (dashed lines in right figures).

Alternatively, Fründ (2021) proposed to define \( \beta_{OS} = \frac{b_{OS}+c_{OS}}{2a+b+c} \) and \( \beta_{ST} = \frac{b_{ST}+c_{ST}}{2a+b+c} \), where \( b_{ST}=b-b_{OS} \)  and \( c_{ST}=c-c_{OS} \) , so that the components \( \beta_{OS} \) and \( \beta_{ST} \) have the same denominator. In this way, Fründ (2021) partitioned the count of unique \( b+c=b_{OS}+b_{ST}+c_{ST} \) interactions, so that \( \beta_{OS} \) and \( \beta_{ST} \) sums to \( \frac{b_{OS}+c_{OS}+b_{ST}+c_{ST}}{2a+b+c} = \frac{b+c}{2a+b+c} = \beta_{WN} \). Fründ (2021) advocated that this partition allows a more sensible comparison of \( \beta_{OS} \) and \( \beta_{ST} \), in terms of the number of links that contribute to each component.

For instance, let us consider the networks 1 and 2 in Figure 1 (left panel) such as \( a_{OS}=2 \) (continuous lines in right panel), \( b_{ST} + c_{ST} = 1 \) and \( b_{OS} + c_{OS} = 1 \) (dashed lines in right panel), and thereby \( a = 2 \), \( b+c=2 \), \( \beta_{WN} = 1/3 \). Fründ (2021) measured \( \beta_{OS}=\beta_{ST}=1/6 \) and argued that it is appropriate insofar as it reflects that the number of unique links in the OS and ST components contributing to network dissimilarity (dashed lines) are actually equal. Conversely, the formula of Poisot et al. (2012) yields \( \beta_{OS}=1/5 \), hence \( \beta_{ST} = \frac{1}{3}-\frac{1}{5}=\frac{2}{15}<\beta_{OS} \). Fründ (2021) thus argued that the method of Poisot tends to underestimate the contribution of species turnover.

To clarify and avoid misinterpretation of the calculation of \( \beta_{OS} \) and \( \beta_{ST} \) in Poisot et al. (2012), Poisot (2022) provides a new, in-depth mathematical analysis of the decomposition of \( \beta_{WN} \). Poisot et al. (2012) quantify in \( \beta_{OS} \) the actual contribution of rewiring in network structure for the subweb of common species. Poisot (2022) thus argues that \( \beta_{OS} \) relates only to the probability of rewiring in the subweb, while the definition of \( \beta_{OS} \) by Fründ (2021) is relative to the count of interactions in the global network (considered in denominator), and is thereby dependent on both rewiring probability and species turnover. Poisot (2022) further clarifies the interpretation of \( \beta_{ST} \). \( \beta_{ST} \) is obtained by subtracting \( \beta_{OS} \) from \( \beta_{WN} \) and thus represents the influence of species turnover in terms of the relative architectures of the global networks and of the subwebs of shared species. Coming back to the example of Fig.1., the Poisot et al. (2012) formula posits that \( \frac{\beta_{ST}}{\beta_{WN}}=\frac{2/15}{1/3}=2/5 \), meaning that species turnover contributes two-fifths of change in network structure, while rewiring in the subweb of common species contributed three fifths.  Conversely, the approach of Fründ (2021) does not compare the architectures of global networks and of the subwebs of shared species, but considers the relative contribution of unique links to network dissimilarity in terms of species turnover and rewiring. 

Poisot (2022) concludes that the partition proposed in Fründ (2021) does not allow unambiguous ecological interpretation of rewiring. He provides guidelines for proper interpretation of the decomposition proposed in Poisot et al. (2012).


Fründ J (2021) Dissimilarity of species interaction networks: how to partition rewiring and species turnover components. Ecosphere, 12, e03653.

Poisot T, Canard E, Mouillot D, Mouquet N, Gravel D (2012) The dissimilarity of species interaction networks. Ecology Letters, 15, 1353–1361.

Poisot T (2022) Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiring. EcoEvoRxiv Preprints, ver. 4 peer-reviewed and recommended by Peer Community in Ecology.

Dissimilarity of species interaction networks: quantifying the effect of turnover and rewiringTimothée Poisot<p style="text-align: justify;">Despite having established its usefulness in the last ten years, the decomposition of ecological networks in components allowing to measure their β-diversity retains some methodological ambiguities. Notably, how to ...Biodiversity, Interaction networks, Theoretical ecologyFrançois Munoz2021-07-31 00:18:41 View
17 May 2023
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Distinct impacts of food restriction and warming on life history traits affect population fitness in vertebrate ectotherms

Effect of food conditions on the Temperature-Size Rule

Recommended by based on reviews by Wolf Blanckenhorn and Wilco Verberk

Temperature-size rule (TSR) is a phenomenon of plastic changes in body size in response to temperature, originally observed in more than 80% of ectothermic organisms representing various groups (Atkinson 1994). In particular, ectotherms were observed to grow faster and reach smaller size at higher temperature and grow slower and achieve larger size at lower temperature. This response has fired the imagination of researchers since its invention, due to its counterintuitive pattern from an evolutionary perspective (Berrigan and Charnov 1994). The main question to be resolved is: why do organisms grow fast and achieve smaller sizes under more favourable conditions (= relatively higher temperature), while they grow longer and achieve larger sizes under less favourable conditions (relatively lower temperature), if larger size means higher fitness, while longer development may be risky? 

This evolutionary conundrum still awaits an ultimate explanation (Angilletta Jr et al. 2004; Angilletta and Dunham 2003; Verberk et al. 2021). Although theoretical modelling has shown that such a growth pattern can be achieved as a response to temperature alone, with a specific combination of energetic parameters and external mortality (Kozłowski et al. 2004), it has been suggested that other temperature-dependent environmental variables may be the actual drivers of this pattern. One of the most frequently invoked variable is the relative oxygen availability in the environment (e.g., Atkinson et al. 2006; Audzijonyte et al. 2019; Verberk et al. 2021; Woods 1999), which decreases with temperature increase. Importantly, this effect is more pronounced in aquatic systems (Forster et al. 2012). However, other temperature-dependent parameters are also being examined in the context of their possible effect on TSR induction and strength.

Food availability is among the interfering factors in this regard. In aquatic systems, nutritional conditions are generally better at higher temperature, while a range of relatively mild thermal conditions is considered. However, there are no conclusive results so far on how nutritional conditions affect the plastic body size response to acute temperature changes. A study by Bazin et al. (2023) examined this particular issue, the effects of food and temperature on TSR, in medaka fish. An important value of the study was to relate the patterns found to fitness. This is a rare and highly desirable approach since evolutionary significance of any results cannot be reliably interpreted unless shown as expressed in light of fitness. 

The authors compared the body size of fish kept at 20°C and 30°C under conditions of food abundance or food restriction. The results showed that the TSR (smaller body size at 30°C compared to 20°C) was observed in both food treatments, but the effect was delayed during fish development under food restriction. Regarding the relevance to fitness, increased temperature resulted in more eggs laid but higher mortality, while food restriction increased survival but decreased the number of eggs laid in both thermal treatments. Overall, food restriction seemed to have a more severe effect on development at 20°C than at 30°C, contrary to the authors’ expectations. 

I found this result particularly interesting. One possible interpretation, also suggested by the authors, is that the relative oxygen availability, which was not controlled for in this study, could have affected this pattern. According to theoretical predictions confirmed in quite many empirical studies so far, oxygen restriction is more severe at higher temperatures. Perhaps for these particular two thermal treatments and in the case of the particular species studied, this restriction was more severe for organismal performance than the food restriction. This result is an example that all three variables, temperature, food and oxygen, should be taken into account in future studies if the interrelationship between them is to be understood in the context of TSR. It also shows that the reasons for growing smaller in warm may be different from those for growing larger in cold, as suggested, directly or indirectly, in some previous studies (Hessen et al. 2010; Leiva et al. 2019). 

Since medaka fish represent predatory vertebrates, the results of the study contribute to the issue of global warming effect on food webs, as the authors rightly point out. This is an important issue because the general decrease in the size or organisms in the aquatic environment with global warming is a fact (e.g., Daufresne et al. 2009), while the question of how this might affect entire communities is not trivial to resolve (Ohlberger 2013). 


Angilletta Jr, M. J., T. D. Steury & M. W. Sears, 2004. Temperature, growth rate, and body size in ectotherms: fitting pieces of a life–history puzzle. Integrative and Comparative Biology 44:498-509.

Angilletta, M. J. & A. E. Dunham, 2003. The temperature-size rule in ectotherms: Simple evolutionary explanations may not be general. American Naturalist 162(3):332-342.

Atkinson, D., 1994. Temperature and organism size – a biological law for ectotherms. Advances in Ecological Research 25:1-58.

Atkinson, D., S. A. Morley & R. N. Hughes, 2006. From cells to colonies: at what levels of body organization does the 'temperature-size rule' apply? Evolution & Development 8(2):202-214

Audzijonyte, A., D. R. Barneche, A. R. Baudron, J. Belmaker, T. D. Clark, C. T. Marshall, J. R. Morrongiello & I. van Rijn, 2019. Is oxygen limitation in warming waters a valid mechanism to explain decreased body sizes in aquatic ectotherms? Global Ecology and Biogeography 28(2):64-77

Bazin, S., Hemmer-Brepson, C., Logez, M., Sentis, A. & Daufresne, M. 2023. Distinct impacts of food restriction and warming on life history traits affect population fitness in vertebrate ectotherms. HAL, ver.3  peer-reviewed and recommended by PCI Ecology.

Berrigan, D. & E. L. Charnov, 1994. Reaction norms for age and size at maturity in response to temperature – a puzzle for life historians. Oikos 70:474-478.

Daufresne, M., K. Lengfellner & U. Sommer, 2009. Global warming benefits the small in aquatic ecosystems. Proceedings of the National Academy of Sciences USA 106(31):12788-93

Forster, J., A. G. Hirst & D. Atkinson, 2012. Warming-induced reductions in body size are greater in aquatic than terrestrial species. Proceedings of the National Academy of Sciences of the United States of America 109(47):19310-19314.

Hessen, D. O., P. D. Jeyasingh, M. Neiman & L. J. Weider, 2010. Genome streamlining and the elemental costs of growth. Trends in Ecology & Evolution 25(2):75-80.

Kozłowski, J., M. Czarnoleski & M. Dańko, 2004. Can optimal resource allocation models explain why ectotherms grow larger in cold? Integrative and Comparative Biology 44(6):480-493.

Leiva, F. P., P. Calosi & W. C. E. P. Verberk, 2019. Scaling of thermal tolerance with body mass and genome size in ectotherms: a comparison between water- and air-breathers. Philosophical Transactions of the Royal Society B 374:20190035.

Ohlberger, J., 2013. Climate warming and ectotherm body szie - from individual physiology to community ecology. Functional Ecology 27:991-1001.

Verberk, W. C. E. P., D. Atkinson, K. N. Hoefnagel, A. G. Hirst, C. R. Horne & H. Siepel, 2021. Shrinking body sizes in response to warming: explanations for the temperature-size rule with special emphasis on the role of oxygen. Biological Reviews 96:247-268.

Woods, H. A., 1999. Egg-mass size and cell size: effects of temperature on oxygen distribution. American Zoologist 39:244-252.

Distinct impacts of food restriction and warming on life history traits affect population fitness in vertebrate ectothermsSimon Bazin, Claire Hemmer-Brepson, Maxime Logez, Arnaud Sentis, Martin Daufresne<p>The reduction of body size with warming has been proposed as the third universal response to global warming, besides geographical and phenological shifts. Observed body size shifts in ectotherms are mostly attributed to the temperature size rul...Climate change, Experimental ecology, Freshwater ecology, Phenotypic plasticity, Population ecologyAleksandra Walczyńska2022-07-27 09:28:29 View
06 Dec 2019
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Does phenology explain plant-pollinator interactions at different latitudes? An assessment of its explanatory power in plant-hoverfly networks in French calcareous grasslands

The role of phenology for determining plant-pollinator interactions along a latitudinal gradient

Recommended by based on reviews by Ignasi Bartomeus, Phillip P.A. Staniczenko and 1 anonymous reviewer

Increased knowledge of what factors are determining species interactions are of major importance for our understanding of dynamics and functionality of ecological communities [1]. Currently, when ongoing temperature modifications lead to changes in species temporal and spatial limits the subject gets increasingly topical. A species phenology determines whether it thrive or survive in its environment. However, as the phenologies of different species are not necessarily equally affected by environmental changes, temporal or spatial mismatches can occur and affect the species-species interactions in the network [2] and as such the full network structure.
In this preprint by Manincor et al. [3] the authors explore the effect of phenology overlap on a large network of species interactions in calcareous grasslands in France. They analyze if and how this effect varies along a latitudinal gradient using empirical data on six plant-hoverfly networks. When comparing ecological network along gradients a well-known problem is that the network metrics is dependent on network size [4]. Therefore, instead of focusing on complete network structure the authors here focus on the factors that determine the probability of interactions and interaction frequency (number of visits). The authors use Bayesian Structural Equation Models (SEM) to link the interaction probability and number of visits to phenology overlap and species abundance. SEM is a multivariate technique that can be used to test several hypotheses and evaluate multiple causal relationships using both observed and latent variables to explain some other observed variables. The authors provide a nice description of the approach for this type of study system. In addition, the study also tests whether phenology affects network compartmentalization, by analyzing species subgroups using a latent block model (LBM) which is a clustering method particularly well-suited for weighted networks.
The authors identify phenology overlap as an important determinant of plant-pollinator interactions, but also conclude this factor alone is not sufficient to explain the species interactions. Species abundances was important for number of visits. Plant phenology drives the duration of the phenology overlap between plant and hoverflies in the studied system. This in turn influences either the probability of interaction or the expected number of visits, as well as network compartmentalization. Longer phenologies correspond to lower modularity inferring less constrained interactions, and shorter phenologies correspond to higher modularity inferring more constrained interactions.
What make this study particularly interesting is the presentation of SEMs as an innovative approach to compare networks of different sizes along environmental gradients. The authors show that these methods can be a useful tool when the aim is to understand the structure of plant-pollinator networks and data is varying in complexities. During the review process the authors carefully addressed to the comments from the two reviewers and the manuscript improved during the process. Both reviewers have expertise highly relevant for the research performed and the development of the manuscript. In my opinion this is a highly interesting and valuable piece of work both when it comes to the scientific question and the methodology. I look forward to further follow this research.


[1] Pascual, M., and Dunne, J. A. (Eds.). (2006). Ecological networks: linking structure to dynamics in food webs. Oxford University Press.
[2] Parmesan, C. (2007). Influences of species, latitudes and methodologies on estimates of phenological response to global warming. Global Change Biology, 13(9), 1860-1872. doi: 10.1111/j.1365-2486.2007.01404.x
[3] de Manincor, N., Hautekeete, N., Piquot, Y., Schatz, B., Vanappelghem, C. and Massol, F. (2019). Does phenology explain plant-pollinator interactions at different latitudes? An assessment of its explanatory power in plant-hoverfly networks in French calcareous grasslands. Zenodo, 2543768, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.5281/zenodo.2543768
[4] Staniczenko, P. P., Kopp, J. C., and Allesina, S. (2013). The ghost of nestedness in ecological networks. Nature communications, 4, 1391. doi: 10.1038/ncomms2422

Does phenology explain plant-pollinator interactions at different latitudes? An assessment of its explanatory power in plant-hoverfly networks in French calcareous grasslandsNatasha de Manincor, Nina Hautekeete, Yves Piquot, Bertrand Schatz, Cédric Vanappelghem, François Massol<p>For plant-pollinator interactions to occur, the flowering of plants and the flying period of pollinators (i.e. their phenologies) have to overlap. Yet, few models make use of this principle to predict interactions and fewer still are able to co...Interaction networks, Pollination, Statistical ecologyAnna Eklöf2019-01-18 19:02:13 View
06 Oct 2020
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Does space use behavior relate to exploration in a species that is rapidly expanding its geographic range?

Explore and move: a key to success in a changing world?

Recommended by based on reviews by Joe Nocera, Marion Nicolaus and Laure Cauchard

Changes in the spatial range of many species are one of the major consequences of the profound alteration of environmental conditions due to human activities. Some species expand, sometimes spectacularly during invasions; others decline; some shift. Because these changes result in local biodiversity loss (whether local species go extinct or are replaced by colonizing ones), understanding the factors driving spatial range dynamics appears crucial to predict biodiversity dynamics. Identifying the factors that shape individual movement is a main step towards such understanding. The study described in this preregistration (McCune et al. 2020) falls within this context by testing possible links between individual exploration behaviour and movements related to daily space use in an avian study model currently rapidly expanding, the great-tailed grackle (Quiscalus mexicanus).

Movement and exploration: which direction(s) for the link between exploration and dispersal?
Individuals are known to differ in their tendency to explore the environment (Réale et al. 2007; Wolf and Weissing 2012) and therefore in their motivation to move. Accordingly, exploration has been shown to relate to dispersal behaviour, i.e. movements between breeding sites (Dingemanse et al. 2003, Le Galliard et al. 2011, Rasmussen and Belk 2012; reviews in Cote et al. 2010, Ronce et al. 2012). Yet, the mechanisms underlying this link often remain unclear, due to the correlative nature of the data. A classical assumption is that dispersers may benefit from a high capacity to explore, allowing them to familiarize quicker with their new environment once reached, thus alleviating dispersal costs (Bonte et al. 2012). The association between dispersal and exploration would in this case result from selection for this combination of traits (Ronce et al. 2012), even though dispersal event itself may be independent from (and precede the effect of) exploration behaviour. Alternatively (but not exclusively), dispersal may simply be the final outcome of longer movements by individuals exploring larger ranges (Badyaev et al. 1996, Schliehe-Diecks et al. 2012). In the absence of easy ways to manipulate dispersal behaviour, on the one hand, and exploration tendency, on the other hand, investigating detailed, small-scale individual movements in relation to exploration should thus shed light on which processes may yield the observed relations between exploration as an individual personality trait and large-scale, long-term movements, such as dispersal, underlying species range dynamics.
In this project, the exploration behaviour of grackles will be measured in controlled conditions using standardized tests in captivity (McCune et al. 2019) before individuals are released and their daily space use behaviour will then be measured using remote tracking over long time periods (McCune et al. 2020). Importantly, these coupled measures will be obtained for individuals captured in three different populations: within the historical range of the species, in the middle of its expanding range and at the edge of the range (McCune et al. 2020). Therefore, the project will test (i) whether daily space use of individuals is linked to their intrinsic exploration tendency and (ii) whether space use differs between individuals from different populations along the expanding range. The preregistration echoes a complementary project by the same team that will focus on exploration and test (iii) whether exploration tendency differs between individuals from these different populations. Taken together, these three analyses will therefore provide solid background information to assess the role of exploration in the individuals’ decisions leading to movement and range dynamics in this species.
As underlined in the preregistration, previous studies addressing the links between individual exploration behaviour and movements have mostly focused on dispersal. A first type of studies have (as will be done here) measured exploration behaviour of individuals, often in captivity (Dingemanse et al. 2003, Korsten et al. 2013) but also in the wild (Rasmussen and Belk 2012, Debeffe et al. 2013), and related these measures to subsequent dispersal behaviour. The (often implicit) underlying assumption is that more exploratory individuals will be more likely to move further, explore different habitats and thus end up breeding farther than less explorative ones. In other words, exploration tendency precedes and drives dispersal. Sometimes, exploratory behaviour is measured on individuals of known dispersal status, i.e. after the dispersal event (Hoset et al. 2011), in which case selection for certain exploration phenotypes among dispersers may already have occurred. Besides this first approach, another type of studies have measured ‘exploration’ behaviour under the form of prospecting movements of individuals and linked these movements to subsequent dispersal (often in the context of habitat selection). While these studies were in the past based on direct thus potentially biased observations (Reed et al. 1999), they now rely more and more on technological advances using (miniaturized) remote tracking devices (Ponchon et al. 2013) that provide far more complete and unbiased movement data, and sometimes also complementary measures of individuals’ internal state. In this case, the implicit assumption is that individuals prospecting farther and/or in more habitat patches will be more likely to settle in a site located farther away from their departure site, because of a more exhaustive sampling of possible sites allowing individuals to identify higher-quality sites (Badyaev et al. 1996). In other words, exploration tendency would not directly lead to higher movements or longer distances, but would allow individuals to optimize their habitat choice among more numerous options, thus leading to an increased dispersal probability or distance; the relation between exploration and dispersal would thus be indirect. Prospecting studies address more closely the underlying mechanisms of movement; however, they cannot easily separate intrinsic individual exploratory tendency from the prospecting movements themselves, with potential feedback effects of the information already gathered on future exploration of other sites or patches, thus on subsequent movements.
By focusing on individual daily space use movements as a mechanistic approach to understand large-scale movements potentially involved in colonization and range expansion, the grackle study described in this preregistration (McCune et al. 2020) will thus contribute to bridge the knowledge gaps between exploration and dispersal. By linking exploration measures obtained from a battery of standardized tests conducted in controlled conditions to individual daily space use and movements recorded in the wild, the grackle project is set in between previous studies addressing the links between exploration and dispersal: it will document exploration in a separate and independent context with respect to the movements themselves, and it will use a mechanistic view of detailed movements by the same individuals in the wild to explore potential implications for dispersal and range expansion. Testing differences between the three study populations over the species range will indeed inform about potential large-scale, population implications of among-individual variation in the link between exploration and movements. Because this study will only measure already settled adult individuals whose previous history is unknown, there will nevertheless be no direct possible exploration of the link with either previous or subsequent dispersal behaviour. Thus, the potential links studied here relate more directly to post-dispersal benefits of exploration for an optimal exploitation of the new environment. Yet, if exploration is a life-long personality trait linked to daily movement patterns, it may also relate to natal dispersal movements in young individuals.

Evolutionary and conservation perspectives
If the results of the project reveal that exploration tendency and daily space use movements are indeed linked, and that individuals from populations across the species range differ in these traits, new questions will emerge. A first question would be whether such among-individual differences are at the origin of range expansion or rather one of its consequences since, again, we deal with correlative data here. In other words, individuals may differ in exploration tendency, and this may confer them different ability to move around, find and colonize new habitats; or individuals may show differences in exploration following arrival in a new habitat, either because more explorative individuals gain fitness benefits and are thus selected, or because of behavioural plasticity and post-colonization adjustment of exploration behaviour when facing new ecological and social conditions in the new environment. Another open question relates to the link between daily space use and dispersal: is dispersal a by-product of higher daily movements that allow individuals to discover new favorable places where to settle? Exploring this link could involve measuring just fledged individuals before natal dispersal occurs and/or individuals chosen according to their own dispersal history, and this would then imply long-term population monitoring as an efficient (but constraining) tool to address such questions. Finally, assessing the fitness consequences of the link between exploration and space use behaviour, and whether these consequences differ between populations along the range expansion, would also be needed to understand the contribution of this link to the invasion success of this species.
The study model chosen for this project is a rapidly expanding species. Importantly, however, and as emphasized in the preregistration, documenting links between exploration and daily space use patterns as well as differences between populations with different trajectories can provide crucial information in general to understand population persistence in response to global climate and landscape changes, both regarding invasion ability or extinction risk. The information should be key to assess the probability that a species may decline, persist or expand in studies addressing biodiversity and community dynamics in a changing world.


Badayev, A. V., Martin, T. E and Etges, W. J. 1996. Habitat sampling and habitat selection by female wild turkeys: ecological correlates and reproductive consequences. Auk 113: 636-646. doi:
Bonte, D. et al. 2012. Costs of dispersal. Biological Reviews 87: 290-312. doi:
Cote, J., Clobert, J., Brodin, T., Fogarty, S. and Sih, A. 2010. Personality-dependent dispersal: characterization, ontogeny and consequences for spatially structured populations. Philosophical Transactions of the Royal Society B 365: 4065-4576. doi:
Debeffe, L., Morellet, N., Cargnelutti, B., Lourtet, B., Coulon, A., Gaillard, J.-M., Bon, R. and Hewison A. J. M. 2013. Exploration as a key component of natal dispersal: dispersers explore more than philopatric individuals in roe deer. Animal Behaviour 86: 143-151. doi:
Dingemanse, N. J., Both, C., van Noordwijk, A. J., Rutten, A. L. and Drent, P. J. 2003. Natal dispersal and personalities in great tits (Parus major). Proceedings of the Royal Society B 270: 741-747. doi:
Hoset, K. S., Ferchaud, A.-L., Dufour, F., Mersch, D., Cote, J. and Le Galliard, J.-F. 2011. Natal dispersal correlates with behavioral traits that are not consistent across early life stages. Behavioral Ecology 22: 176–183. doi:
Korsten, P., van Overveld, T., Adriaensen, F. and Matthysen, E. 2013. Genetic integration of local dispersal and exploratory behaviour in a wild bird. Nature Communications 4: 2362. doi:
Le Galliard, J.-F., Rémy, A., Ims, R. A. and Lambin, X. 2011. Patterns and processes of dispersal behaviour in arvicoline rodents. Molecular Ecology 21: 505-523. doi:
McCune K, Ross C, Folsom M, Bergeron L, Logan CJ. 2020. Does space use behavior relate to exploration in a species that is rapidly expanding its geographic range? In principle acceptance by PCI Ecology of the version on 23 Sep 2020
McCune K, MacPherson M, Rowney C, Bergeron L, Folsom M, Logan CJ. 2019. Is behavioral flexibility linked with exploration, but not boldness, persistence, or motor diversity? ( In principle acceptance by PCI Ecology of the version on 27 Mar 2019
Ponchon, A., Grémillet, D., Doligez, B., Chambert, T., Tveraa, T., González-Solís, J. and Boulinier, T. 2013. Tracking prospecting movements involved in breeding habitat selection: insights, pitfalls and perspectives. Methods in Ecology and Evolution 4: 143-150. doi:
Rasmussen, J. E. and Belk, M. C. 2012. Dispersal behavior correlates with personality of a North American fish. Current Zoology 58: 260–270. doi:
Réale, D., Reader, S. M., Sol, D., McDougall, P. T. and Dingemanse, N. J. 2007. Integrating animal temperament within ecology and evolution. Biological Reviews 82: 291-318. doi:
Reed, J. M., Boulinier, T., Danchin, E. and Oring, L. W. 1999. Informed dispersal: prospecting by birds for breeding sites. Current Ornithology 15: 189-259. doi:
Ronce, O. and Clobert, J. 2012. Dispersal syndromes. pp. 119-138 In Dispersal Ecology and Evolution (eds. Clobert, J., Baguette, M., Benton, T. G. and Bullock, J. M.), pp. 119-138. Oxford University Press.
Schliehe-Diecks, S., Eberle, M. and Kappeler, P. M. 2012. Walk the line - dispersal movements of gray mouse lemurs (Microcebus murinus). Behavioral Ecology and Sociobiology 66: 1175-1185. doi:
Wolf, M. and Weissing, F. J. 2012. Animal personalities: consequences for ecology and evolution. Trends in Ecology and Evolution 27: 452-461. doi:

Does space use behavior relate to exploration in a species that is rapidly expanding its geographic range?Kelsey B. McCune, Cody Ross, Melissa Folsom, Luisa Bergeron, Corina LoganGreat-tailed grackles (Quiscalus mexicanus) are rapidly expanding their geographic range (Wehtje 2003). Range expansion could be facilitated by consistent behavioural differences between individuals on the range edge and those in other parts of th...Behaviour & Ethology, Biological invasions, Conservation biology, Habitat selection, Phenotypic plasticity, Preregistrations, Spatial ecology, Metacommunities & MetapopulationsBlandine Doligez2019-09-30 19:27:40 View
31 Jan 2019
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Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed grackles

From cognition to range dynamics: advancing our understanding of macroecological patterns

Recommended by based on reviews by 2 anonymous reviewers

Understanding the distribution of species on earth is one of the fundamental challenges in ecology and evolution. For a long time, this challenge has mainly been addressed from a correlative point of view with a focus on abiotic factors determining a species abiotic niche (classical bioenvelope models; [1]). It is only recently that researchers have realized that behaviour and especially plasticity in behaviour may play a central role in determining species ranges and their dynamics [e.g., 2-5]. Blaisdell et al. propose to take this even one step further and to analyse how behavioural flexibility and possibly associated causal cognition impacts range dynamics.
The current preregistration is integrated in an ambitious long-term research plan that aims at addressing the above outlined question and focuses specifically on investigating whether more behaviourally flexible individuals are better at deriving causal inferences. The model system the authors plan on using are Great-tailed Grackles which have expanded their range into North America during the last century. The preregistration by Blaisdell et al. is a great example of the future of scientific research: it includes conceptual models, alternative hypotheses and testable predictions along with a sound sampling and analysis plan and embraces the principles of Open Science. Overall, the research the authors propose is fascinating and of highest relevance, as it aims at bridging scales from the microscopic mechanisms that underlie animal behaviour to macroscopic, macroecological consequences (see also [3]). I am very much looking forward to the results the authors will report.

[1] Elith, J. & Leathwick, J. R. 2009. Species distribution models: ecological explanation and prediction across space and time. Annu. Rev. Ecol. Evol. Syst. 40: 677-697. doi: 10.1146/annurev.ecolsys.110308.120159
[2] Kubisch, A.; Degen, T.; Hovestadt, T. & Poethke, H. J. (2013) Predicting range shifts under global change: the balance between local adaptation and dispersal. Ecography 36: 873-882. doi: 10.1111/j.1600-0587.2012.00062.x
[3] Keith, S. A. & Bull, J. W. (2017) Animal culture impacts species' capacity to realise climate-driven range shifts. Ecography, 40: 296-304. doi: 10.1111/ecog.02481
[4] Sullivan, L. L.; Li, B.; Miller, T. E.; Neubert, M. G. & Shaw, A. K. (2017) Density dependence in demography and dispersal generates fluctuating invasion speeds. Proc. Natl. Acad. Sci. USA, 114: 5053-5058. doi: 10.1073/pnas.1618744114
[5] Fronhofer, E. A.; Nitsche, N. & Altermatt, F. (2017) Information use shapes the dynamics of range expansions into environmental gradients. Glob. Ecol. Biogeogr. 26: 400-411. doi: 10.1111/geb.12547

Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed gracklesAaron Blaisdell, Zoe Johnson-Ulrich, Luisa Bergeron, Carolyn Rowney, Benjamin Seitz, Kelsey McCune, Corina LoganThis PREREGISTRATION has undergone one round of peer reviews. We have now revised the preregistration and addressed reviewer comments. The DOI was issued by OSF and refers to the whole GitHub repository, which contains multiple files. The specific...Behaviour & Ethology, Preregistrations, ZoologyEmanuel A. Fronhofer2018-08-20 11:09:48 View
30 Mar 2021
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Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed grackles

From cognition to range dynamics – and from preregistration to peer-reviewed preprint

Recommended by based on reviews by Laure Cauchard and 1 anonymous reviewer

In 2018 Blaisdell and colleagues set out to study how causal cognition may impact large scale macroecological patterns, more specifically range dynamics, in the great-tailed grackle (Fronhofer 2019). This line of research is at the forefront of current thought in macroecology, a field that has started to recognize the importance of animal behaviour more generally (see e.g. Keith and Bull (2017)). Importantly, the authors were pioneering the use of preregistrations in ecology and evolution with the aim of improving the quality of academic research.

Now, nearly 3 years later, it is thanks to their endeavour of making research better that we learn that the authors are “[...] unable to speculate about the potential role of causal cognition in a species that is rapidly expanding its geographic range.” (Blaisdell et al. 2021; page 2). Is this a success or a failure? Every reader will have to find an answer to this question individually and there will certainly be variation in these answers as becomes clear from the referees’ comments. In my opinion, this is a success story of a more stringent and transparent approach to doing research which will help us move forward, both methodologically and conceptually.


Fronhofer (2019) From cognition to range dynamics: advancing our understanding of macroe-
cological patterns. Peer Community in Ecology, 100014. doi:

Keith, S. A. and Bull, J. W. (2017) Animal culture impacts species' capacity to realise climate-driven range shifts. Ecography, 40: 296-304. doi:

Blaisdell, A., Seitz, B., Rowney, C., Folsom, M., MacPherson, M., Deffner, D., and Logan, C. J. (2021) Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed grackles. PsyArXiv, ver. 5 peer-reviewed and recommended by Peer community in Ecology. doi:

Do the more flexible individuals rely more on causal cognition? Observation versus intervention in causal inference in great-tailed gracklesBlaisdell A, Seitz B, Rowney C, Folsom M, MacPherson M, Deffner D, Logan CJ<p>Behavioral flexibility, the ability to change behavior when circumstances change based on learning from previous experience, is thought to play an important role in a species’ ability to successfully adapt to new environments and expand its geo...PreregistrationsEmanuel A. Fronhofer2020-11-27 09:49:55 View