The article by Legay et al. [1] addresses two main issues: the links between belowground and aboveground plant traits and the links between plant strategies (as defined by these traits) and the capacity to absorb nitrate and ammonium. I recommend this work because these are important and current issues. The literature on plant traits is extremely rich and the existence of a leaf economic spectrum linked to a gradient between conservative and acquisitive plants is now extremely well established [2-3]. Many teams are now working on belowground traits and possible links with the aboveground gradients [4-5]. It seems indeed that there is a root economic spectrum but this spectrum is apparently less pronounced than the leaf economic spectrum. The existence of links between the two spectrums are still controversial and are likely not universal as suggested by discrepant results and after all a plant could have a conservative strategy aboveground and an acquisitive strategy belowground (or vice-versa) because, indeed, constraints are different belowground and aboveground (for example because in given ecosystem/vegetation type light may be abundant but not water or mineral nutrients). The various results obtained also suggest that we do not full understand the diversity of belowground strategies, what is at stake with these strategies, and the links with root characteristics.
Each time I give a conference on the work we are carrying out on African grasses that likely absorb ammonium preferentially because they inhibit nitrification [6-7], somebody asks me a question about the fact that plant essentially absorb nitrate because ammonium is toxic and nitrate more available in the soil. The present article confirms that this is not the case and that, though there are currently some teams working on the subject, we do not really know for the moment whether plants absorb nitrate or ammonium, in which proportion, how plastic this proportion is within individuals and within species. This subject seems to me crucial because it is linked to (1) the capacity of ecosystems to conserve nitrogen [8], because nitrate, much more than ammonium, goes out of ecosystems through leaching and denitrification, (2) to carbon cycling and plant energy budget because absorbing nitrate requires spending mucho more energy than absorbing ammonium because nitrate must be reduced before being incorporated in plant biomass, which is very energy costly. These two issues are naturally very relevant to develop efficient cropping systems in terms of carbon and nitrogen.
Interestingly, the present article, comparing three grass species in different sites, suggests that there is no trade-off between the absorption of nitrate and ammonium: more acquisitive individuals tend to absorb more ammonium and nitrate. This is contrary to hypotheses we made to predict the outcome of competition between plants absorbing nitrate and ammonium in different proportions [9] but should be tested in the future comparing many different types of plants. The results also suggest that more conservative plants absorb relatively more ammonium, which makes sense because this allows them to spare the energy necessary to reduce nitrate. This leads to the question of the effect of these strategies on nitrogen retention within the ecosystem. If nitrification is high (low), absorbing ammonium is not efficient and likely leads to high (low) nitrogen losses. This should be tested in the future. Moreover, the authors have measured the absorption of nitrate and ammonium through measurements at the root scale on cut roots. This should be complemented by measurements at the whole plant scale.

References

[1] Legay, N., Grassein, F., Arnoldi, C., Segura, R., Laîné, P., Lavorel, S. and Clément, J.-C. (2020). Studies of NH4+ and NO3- uptake ability of subalpine plants and resource-use strategy identified by their functional traits. bioRxiv, 372235, ver. 4 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/372235
[2] Shipley, B., Lechowicz, M.J., Wright, I. & Reich, P.B. (2006) Fundamental trade-offs generating the worldwide leaf economics spectrum. Ecology, 87, 535-541. doi: 10.1890/05-1051
[3] Reich, P.B. (2014) The world-wide ‘fast-slow’ plant economics spectrum: a traits manifesto. J. Ecol., 102, 275-301. doi: 10.1111/1365-2745.12211
[4] Maire, V., Gross, N., Pontes, L.D.S., Picon-Cochard, C. & Soussana, J.F. (2009) Trade-off between root nitrogen acquisition and shoot nitrogen utilization across 13 co-occurring pasture grass species. Func. Ecol., 23, 668-679. doi: 10.1111/j.1365-2435.2009.01557.x
[5] Roumet, C., Birouste, M., Picon-Cochard, C., Ghestem, M., Osman, N., Vrignon-Brenas, S., Cao, K.F. & Stokes, A. (2016) Root structure-function relationships in 74 species: evidence of a root economics spectrum related to carbon economy. New. Phytol., 210, 815-826. doi: 10.1111/nph.13828
[6] Lata, J.-C., Degrange, V., Raynaud, X., Maron, P.-A., Lensi, R. & Abbadie, L. (2004) Grass populations control nitrification in savanna soils. Funct. Ecol., 18, 605-611. doi: 10.1111/j.0269-8463.2004.00880.x
[7] Srikanthasamy, T., Leloup, J., N’Dri, A.B., Barot, S., Gervaix, J., Koné, A.W., Koffi, K.F., Le Roux, X., Raynaud, X. & Lata, J.-C. (2018) Contrasting effects of grasses and trees on microbial N-cycling in an African humid savanna. Soil Biol. Biochem., 117, 153-163. doi: 10.1016/j.soilbio.2017.11.016
[8] Boudsocq, S., Lata, J.C., Mathieu, J., Abbadie, L. & Barot, S. (2009) Modelling approach to analyze the effects of nitrification inhibition on primary production. Func. Ecol., 23, 220-230. doi: 10.1111/j.1365-2435.2008.01476.x
[9] Boudsocq, S., Niboyet, A., Lata, J.-C., Raynaud, X., Loeuille, N., Mathieu, J., Blouin, M., Abbadie, L. & Barot, S. (2012) Plant preference for ammonium versus nitrate: a neglected determinant of ecosystem functioning? Am. Nat., 180, 60-69. doi: 10.1086/665997

The late eminent ecologist Gary Polis once stated that “most catalogued food-webs are oversimplified caricatures of actual communities” and are “grossly incomplete representations of communities in terms of both diversity and trophic connections.” Not content with that damning indictment, he went further by railing that “theorists are trying to explain phenomena that do not exist” [1]. The latter critique might have been push back for Robert May´s ground-breaking but ultimately flawed research on the relationship between food-web complexity and stability [2]. Polis was a brilliant ecologist, and his thinking was clearly influenced by his experiences researching desert food webs. Those food webs possess an uncommon combination of properties, such as frequent omnivory, cannibalism, and looping; high linkage density (L/S); and a nearly complete absence of apex consumers, since few species completely lack predators or parasites [3]. During my PhD studies, I was lucky enough to visit Joshua Tree National Park on the way to a conference in New England, and I could immediately see the problems posed by desert ecosystems. At the time, I was ruminating on the “harsh-benign” hypothesis [4], which predicts that the relative importance of abiotic and biotic forces should vary with changes in local environmental conditions (from harsh to benign). Specifically, in more “harsh” environments, abiotic factors should determine community composition whilst weakening the influence of biotic interactions. However, in the harsh desert environment I saw first-hand evidence that species interactions were not diminished; if anything, they were strengthened. Teddy-bear chollas possessed murderously sharp defenses to protect precious water, creosote bushes engaged in belowground “chemical warfare” (allelopathy) to deter potential competitors, and rampant cannibalism amongst scorpions drove temporal and spatial ontogenetic niche partitioning. Life in the desert was hard, but you couldn´t expect your competition to go easy on you.
If that experience colored my thinking about nature’s reaction to a capricious environment, then the seminal work by Robert Paine on the marine rocky shore helped further cement the importance of biotic interactions. The insights provided by Paine [5] brings us closer to the research reported in the preprint “The return of the trophic chain: fundamental vs realized interactions in a simple arthropod food web” [6], given that the authors in that study hold the environment constant and test the interactions between different permutations of a simple community. Paine [5] was able to elegantly demonstrate using the chief protagonist Pisaster ochraceus (a predatory echinoderm also known as the purple sea star) that a keystone consumer could exert strong top-down control that radically reshaped the interactions amongst other community members. What was special about this study was that the presence of Pisaster promoted species diversity by altering competition for space by sedentary species, providing a rare example of an ecological network experiment combining trophic and non-trophic interactions. Whilst there are increasing efforts to describe these interactions (e.g., competition and facilitation) in multiplex networks [7], the authors of “The return of the trophic chain: fundamental vs realized interactions in a simple arthropod food web” [6] have avoided strictly competitive interactions for the sake of simplicity. They do focus on two trophic forms of competition, namely intraguild predation and apparent competition. These two interaction motifs, along with prey switching are relevant to my own research on the influence of cross-ecosystem prey subsidies to receiving food webs [8]. In particular, the apparent competition motif may be particularly important in the context of emergent adult aquatic insects as prey subsidies to terrestrial consumers. This was demonstrated by Henschel et al. [9] where the abundances of emergent adult aquatic midges in riparian fields adjacent to a large river helped stimulate higher abundances of spiders and lower abundances of herbivorous leafhoppers, leading to a trophic cascade. The aquatic insects had a bottom-up effect on spiders and this subsidy facilitated a top-down effect that cascaded from spiders to leafhoppers to plants. The apparent competition motif becomes relevant because the aquatic midges exerted a negative indirect effect on leafhoppers mediated through their common arachnid predators.
In the preprint “The return of the trophic chain: fundamental vs realized interactions in a simple arthropod food web” [6], the authors have described different permutations of a simple mite community present in avocado orchards (Persea americana). This community comprises of two predators (Euseius stipulatus and Neoseiulus californicus), one herbivore as shared prey (Oligonychus perseae), and pollen of Carpobrotus edulis as alternative food resource, with the potential for the intraguild predation and apparent competition interaction motifs to be expressed. The authors determined that these motifs should be realized based off pairwise feeding trials. It is common for food-web researchers to depict potential food webs, which contain all species sampled and all potential trophic links based on laboratory feeding trials (as demonstrated here) or from observational data and literature reviews [10]. In reality, not all these potential feeding links are realized because species may partition space and time, thus driving alternative food-web architectures. In “The return of the trophic chain: fundamental vs realized interactions in a simple arthropod food web” [6], the authors are able to show that placing species in combinations that should yield more complex interaction motifs based off pairwise feeding trials fails to deliver – the predators revert to their preferred prey resulting in modular and simple trophic chains to be expressed. Whilst these realized interaction motifs may be stable, there might also be a tradeoff with function by yielding less top-down control than desirable when considering the potential for ecosystem services such as pest management. These are valuable insights, although it should be noted that here the fundamental niche is described in a strictly Eltonian sense as a trophic role [11]. Adding additional niche dimensions (sensu [12]), such as a thermal gradient could alter the observed interactions, although it might be possible to explain these contingencies through metabolic and optimal foraging theory combined with species traits. Nonetheless, the results of these experiments further demonstrate the need for ecologists to cross-validate theory with empirical approaches to develop more realistic and predictive food-web models, lest they invoke the wrath of Gary Polis´ ghost by “trying to explain phenomena that do not exist”.

References

[1] Polis, G. A. (1991). Complex trophic interactions in deserts: an empirical critique of food-web theory. The American Naturalist, 138(1), 123-155. doi: 10.1086/285208
[2] May, R. M. (1973). Stability and complexity in model ecosystems. Princeton University Press, Princeton, NJ, USA
[3] Dunne, J. A. (2006). The network structure of food webs. In Pascual, M., & Dunne, J. A. (eds) Ecological Networks: Linking Structure to Dynamics in Food Webs. Oxford University Press, New York, USA, 27-86
[4] Menge, B. A., & Sutherland, J. P. (1976). Species diversity gradients: synthesis of the roles of predation, competition, and temporal heterogeneity. The American Naturalist, 110(973), 351-369. doi: 10.1086/283073
[5] Paine, R. T. (1966). Food web complexity and species diversity. The American Naturalist, 100(910), 65-75. doi: 10.1086/282400
[6] Torres-Campos, I., Magalhães, S., Moya-Laraño, J., & Montserrat, M. (2018). The return of the trophic chain: fundamental vs realized interactions in a simple arthropod food web. bioRxiv, 324178, ver. 5 peer-reviewed and recommended by PCI Ecol. doi: 10.1101/324178
[7] Kéfi, S., Berlow, E. L., Wieters, E. A., Joppa, L. N., Wood, S. A., Brose, U., & Navarrete, S. A. (2015). Network structure beyond food webs: mapping non‐trophic and trophic interactions on Chilean rocky shores. Ecology, 96(1), 291-303. doi: 10.1890/13-1424.1
[8] Burdon, F. J., & Harding, J. S. (2008). The linkage between riparian predators and aquatic insects across a stream‐resource spectrum. Freshwater Biology, 53(2), 330-346. doi: 10.1111/j.1365-2427.2007.01897.x
[9] Henschel, J. R., Mahsberg, D., & Stumpf, H. (2001). Allochthonous aquatic insects increase predation and decrease herbivory in river shore food webs. Oikos, 93(3), 429-438. doi: 10.1034/j.1600-0706.2001.930308.x
[10] Brose, U., Pavao-Zuckerman, M., Eklöf, A., Bengtsson, J., Berg, M. P., Cousins, S. H., Mulder, C., Verhoef, H. A., & Wolters, V. (2005). Spatial aspects of food webs. In de Ruiter, P., Wolters, V., Moore, J. C., & Melville-Smith, K. (eds) Dynamic Food Webs. vol 3. Academic Press, Burlington, 463-469
[11] Elton, C. (1927). Animal Ecology. Sidgwick and Jackson, London, UK
[12] Hutchinson, G. E. (1957). Concluding Remarks. Cold Spring Harbor Symposia on Quantitative Biology, 22, 415-427. doi: 10.1101/sqb.1957.022.01.039

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). 

REFERENCES

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. https://doi.org/10.1093/icb/44.6.498

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. https://doi.org/10.1086/377187

Atkinson, D., 1994. Temperature and organism size – a biological law for ectotherms. Advances in Ecological Research 25:1-58. https://doi.org/10.1016/S0065-2504(08)60212-3

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 https://doi.org/10.1111/j.1525-142X.2006.00090.x

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 https://doi.org/10.1111/geb.12847

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. https://hal.inrae.fr/hal-03738584v3

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. https://doi.org/10.2307/3545787

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 https://doi.org/10.1073/pnas.0902080106

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. https://doi.org/10.1073/pnas.1210460109

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. https://doi.org/10.1016/j.tree.2009.08.004

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. https://doi.org/10.1093/icb/44.6.480

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. https://doi.org/10.1098/rstb.2019.0035

Ohlberger, J., 2013. Climate warming and ectotherm body szie - from individual physiology to community ecology. Functional Ecology 27:991-1001. https://doi.org/10.1111/1365-2435.12098

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. https://doi.org/10.1111/brv.12653

Woods, H. A., 1999. Egg-mass size and cell size: effects of temperature on oxygen distribution. American Zoologist 39:244-252. https://doi.org/10.1093/icb/39.2.244

Community ecology usually concerns itself with understanding the causes and consequences of diversity at a given taxonomic resolution, most classically at the species level. Yet there is no doubt that diversity exists at all scales, and phenotypic variability within a taxon can be comparable to differences between taxa, as observed from bacteria to fish and trees. The question that motivates an active and growing body of work (e.g. Raffard et al 2019) is not so much whether intraspecific variability matters, but what we get wrong by ignoring it and how to incorporate it into our understanding of communities. There is no established way to think about diversity at multiple nested taxonomic levels, and it is tempting to summarize intraspecific variability simply by measuring species mean and variance in any trait and metric.

In this study, Girard-Tercieux et al (2023a) propose that, to understand its impact on community-level outcomes and in particular on species coexistence, we should carefully distinguish between two ways of thinking about intraspecific variability:

-"unstructured" variation, where every individual's features are like an independent random draw from a species-specific distribution, for instance, due to genetic lottery and developmental accidents

-"structured" variation that is due to each individual encountering a different but enduring microenvironment.

The latter type of variability may still appear complex and random-like when the environment is high-dimensional (i.e. multifaceted, with many different factors contributing to each individual's performance and development). Thus, it is not necessarily "structured" in the sense of being easily understood -- we may need to measure more aspects of the environment than is practical if we want to fully predict these variations.

What distinguishes this "structured" variability is that it is, in a loose sense, inheritable: individuals from the same species that grow in the same microenvironment will have the same performance, in a repeatable fashion. Thus, if each species is best at exploiting at least a fraction of environmental conditions, it is likely to avoid extinction by competition, except in the unlucky case of no propagule reaching any of the favorable sites.
By contrast, drawing each individual's preferences and performance randomly at each generation (from its own species distribution, but independently from other and past individuals) leads to stochastic dynamics, so-called ecological drift, that easily induce a large number of species extinctions.

The core intuition, that the complex spatial structure and high-dimensional nature of the environment plays a key explanatory role in species coexistence, is a running thread through several of the authors' work (e.g. Clark et al 2010), clearly inspired by their focus on tropical forests. This study, by tackling the question of intraspecific determinants of interspecific outcomes, makes a compelling addition to this line of investigation, coming as a theoretical companion to a more data-oriented study (Girard-Tercieux et al 2023b). But I believe it raises a question that is even broader in scope.

This kind of intraspecific variability, due to different individuals growing in different microenvironments, is perhaps most relevant for trees and other sessile organisms, but the distinction made here between "unstructured" and "structured" variability can likely be extended to many other ecological settings.

In my understanding, what matters most in "structured" variability is not so much it stemming from a fixed environment, but rather it being maintained across generations, rather than possibly lost by drift. This difference between variability in the form of "frozen" randomness and in the form of stochastic drift over time is highly relevant in other theoretical fields (e.g. in physics, where it is the difference between a disordered solid and a liquid), and thus, I expect that it is a meaningful distinction to make throughout community ecology.

References

James S. Clark, David Bell, Chengjin Chu, Benoit Courbaud, Michael Dietze, Michelle Hersh, Janneke HilleRisLambers et al. (2010) "High‐dimensional coexistence based on individual variation: a synthesis of evidence." Ecological Monographs 80, no. 4 : 569-608. https://doi.org/10.1890/09-1541.1

Camille Girard-Tercieux, Ghislain Vieilledent, Adam Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Georges Kunstler, Raphaël Pélissier, Nadja Rüger, Isabelle Maréchaux (2023a) "Beyond variance: simple random distributions are not a good proxy for intraspecific variability in systems with environmental structure." bioRxiv, ver. 4 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.06.503032

Camille Girard‐Tercieux, Isabelle Maréchaux, Adam T. Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Joannès Guillemot et al. (2023b) "Rethinking the nature of intraspecific variability and its consequences on species coexistence." Ecology and Evolution 13, no. 3 : e9860. https://doi.org/10.1002/ece3.9860

Allan Raffard, Frédéric Santoul, Julien Cucherousset, and Simon Blanchet. (2019) "The community and ecosystem consequences of intraspecific diversity: A meta‐analysis." Biological Reviews 94, no. 2: 648-661. https://doi.org/10.1111/brv.12472

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
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