The temporal or spatial variability in species population sizes and interaction strength of animal and plant communities has a strong impact on aggregate community properties (for instance biomass), community composition, and species richness (Kokkoris et al. 2002). Early work on spatial and temporal variability strongly indicated that asynchronous population and environmental fluctuations tend to stabilise community structures and diversity (e.g. Holt 1984, Tilman and Pacala 1993, McCann et al. 1998, Amarasekare and Nisbet 2001). Similarly, trophic networks might be stabilised by spatial heterogeneity (Hastings 1977) and an asymmetry of energy flows along food chains (Rooney et al. 2006). The interplay between temporal, spatial, and trophic heterogeneity within the meta-community concept has got much less interest. In the recent preprint in PCI Ecology, Quévreux et al. (2023) report that Spatial heterogeneity of interaction strength has contrasting effects on synchrony and stability in trophic metacommunities. These authors rightly notice that the interplay between trophic and spatial heterogeneity might induce contrasting effects depending on the internal dynamics of the system. Their contribution builds on prior work (Quévreux et al. 2021a, b) on perturbed trophic cascades.

I found this paper particularly interesting because it is in the, now century-old, tradition to show that ecological things are not so easy. Since the 1930th, when Nicholson and Baily and others demonstrated that simple deterministic population models might generate stability and (pseudo-)chaos ecologists have realised that systems triggered by two or more independent processes might be intrinsically unpredictable and generate different outputs depending on the initial parameter settings. This resembles the three-body problem in physics. The present contribution of Quévreux et al. (2023) extends this knowledge to an example of a spatially explicit trophic model. Their main take-home message is that asymmetric energy flows in predator–prey relationships might have contrasting effects on the stability of metacommunities receiving localised perturbations. Stability is context dependent.

Of course, the work is merely a theoretical exercise using a simplistic trophic model. It demands verification with field data. Nevertheless, we might expect even stronger unpredictability in more realistic multitrophic situations. Therefore, it should be seen as a proof of concept. Remember that increasing trophic connectance tends to destabilise food webs (May 1972). In this respect, I found the final outlook to bioconservation ambitious but substantiated. Biodiversity management needs a holistic approach focusing on all aspects of ecological functioning. I would add the need to see stability and biodiversity within an evolutionary perspective.        

References

Amarasekare P, Nisbet RM (2001) Spatial Heterogeneity, Source‐Sink Dynamics, and the Local Coexistence of Competing Species. The American Naturalist, 158, 572–584. https://doi.org/10.1086/323586

Hastings A (1977) Spatial heterogeneity and the stability of predator-prey systems. Theoretical Population Biology, 12, 37–48. https://doi.org/10.1016/0040-5809(77)90034-X

Holt RD (1984) Spatial Heterogeneity, Indirect Interactions, and the Coexistence of Prey Species. The American Naturalist, 124, 377–406. https://doi.org/10.1086/284280

Kokkoris GD, Jansen VAA, Loreau M, Troumbis AY (2002) Variability in interaction strength and implications for biodiversity. Journal of Animal Ecology, 71, 362–371. https://doi.org/10.1046/j.1365-2656.2002.00604.x

May RM (1972) Will a Large Complex System be Stable? Nature, 238, 413–414. https://doi.org/10.1038/238413a0

McCann K, Hastings A, Huxel GR (1998) Weak trophic interactions and the balance of nature. Nature, 395, 794–798. https://doi.org/10.1038/27427

Quévreux P, Barbier M, Loreau M (2021) Synchrony and Perturbation Transmission in Trophic Metacommunities. The American Naturalist, 197, E188–E203. https://doi.org/10.1086/714131

Quévreux P, Pigeault R, Loreau M (2021) Predator avoidance and foraging for food shape synchrony and response to perturbations in trophic metacommunities. Journal of Theoretical Biology, 528, 110836. https://doi.org/10.1016/j.jtbi.2021.110836

Quévreux P, Haegeman B, Loreau M (2023) Spatial heterogeneity of interaction strength has contrasting effects on synchrony and stability in trophic metacommunities. hal-03829838, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://hal.science/hal-03829838

Rooney N, McCann K, Gellner G, Moore JC (2006) Structural asymmetry and the stability of diverse food webs. Nature, 442, 265–269. https://doi.org/10.1038/nature04887

Tilman D, Pacala S (1993) The maintenance of species richness in plant communities. In: Ricklefs, R.E., Schluter, D. (eds) Species Diversity in Ecological Communities: Historical and Geographical Perspectives. University of Chicago Press, pp. 13–25.

Consistent individual differences in habitat use are found across species and can play a role in who an individual mates with, their risk of predation, and their ability to compete with others (Stuber et al. 2022). However, the data informing such hypotheses come primarily from temperate regions (Stroud & Thompson 2019, Titley et al. 2017). This calls into question the generalizability of the conclusions from this research until further investigations can be conducted in tropical regions.

Giacomini and colleagues (2023) tackled this task in an investigation of consistent individual differences in habitat use in the Central American tropics. They explored whether Spix’s disc-winged bats form positional hierarchies in roosts, which is an excellent start to learning more about the social behavior of this species - a species that is difficult to directly observe. They found that individual bats use their roosting habitat in predictable ways by positioning themselves consistently either in the bottom, middle, or top of the roost leaf. Individuals chose the same positions across time and across different roost sites. They also found that age and sex play a role in which sections individuals are positioned in.

Their research shows that consistent individual differences in habitat use are present in a tropical system, and sets the stage for further investigations into social behavior in this species, particularly whether there is a dominance hierarchy among individuals and whether some positions in the roost are more protective and sought after than others.

References

Giacomini G, Chaves-Ramirez S, Hernandez-Pinson A, Barrantes JP, Chaverri G. (2023). Consistent individual positions within roosts in Spix's disc-winged bats. bioRxiv, https://doi.org/10.1101/2022.11.04.515223 

Stroud, J. T., & Thompson, M. E. (2019). Looking to the past to understand the future of tropical conservation: The importance of collecting basic data. Biotropica, 51(3), 293-299. https://doi.org/10.1111/btp.12665

Stuber, E. F., Carlson, B. S., & Jesmer, B. R. (2022). Spatial personalities: a meta-analysis of consistent individual differences in spatial behavior. Behavioral Ecology, 33(3), 477-486. https://doi.org/10.1093/beheco/arab147 

Titley, M. A., Snaddon, J. L., & Turner, E. C. (2017). Scientific research on animal biodiversity is systematically biased towards vertebrates and temperate regions. PloS one, 12(12), e0189577. https://doi.org/10.1371/journal.pone.0189577

Dispersal is a key element of the natural dynamics of meta-communities, and plays a central role in the success of populations colonizing new landscapes. Understanding how demographic processes may affect the speed at which alien species spread through environmentally-heterogeneous habitat fragments is therefore of key importance to manage biological invasions. This requires studying together the complex interplay of dispersal and population processes, two inextricably related phenomena that can produce many possible outcomes. Stochastic models offer an opportunity to describe this kind of process in a meaningful way, but to ensure that they are realistic (sensu Levins 1966) it is also necessary to combine model simulations with empirical data (Snäll et al. 2007).

Morel-Journel et al. (2023) put together stochastic models and experimental data to study how population density may affect the speed at which alien species spread through a heterogeneous landscape. They do it by focusing on what they call ‘colonisation debt’, which is merely the impact that population density at the invasion front may have on the speed at which the species colonizes patches of different carrying capacities. They investigate this issue through two largely independent approaches. First, a stochastic model of dispersal throughout the patches of a linear, 1-dimensional landscape, which accounts for different degrees of density-dependent growth. And second, a microcosm experiment of a parasitoid wasp colonizing patches with different numbers of host eggs. In both cases, they compare the velocity of colonization of patches with lower or higher carrying capacity than the previous one (i.e. what they call upward or downward gradients).

Their results show that density-dependent processes influence the speed at which new fragments are colonized is significantly reduced by positive density dependence. When either population growth or dispersal rate depend on density, colonisation debt limits the speed of invasion, which turns out to be dependent on the strength and direction of the gradient between the conditions of the invasion front, and the newly colonized patches. Although this result may be quite important to understand the meta-population dynamics of dispersing species, it is important to note that in their study the environmental differences between patches do not take into account eventual shifts in the scenopoetic conditions (i.e. the values of the environmental parameters to which species niches’ respond to; Hutchinson 1978, see also Soberón 2007). Rather, differences arise from variations in the carrying capacity of the patches that are consecutively invaded, both in the in silico and microcosm experiments. That is, they account for potential differences in the size or quality of the invaded fragments, but not on the costs of colonizing fragments with different environmental conditions, which may also determine invasion speed through niche-driven processes. This aspect can be of particular importance in biological invasions or under climate change-driven range shifts, when adaptation to new environments is often required (Sakai et al. 2001; Whitney & Gabler 2008; Hill et al. 2011).

The expansion of geographical distribution ranges is the result of complex eco-evolutionary processes where meta-community dynamics and niche shifts interact in a novel physical space and/or environment (see, e.g., Mestre et al. 2020). Here, the invasibility of native communities is determined by niche variations and how similar are the traits of alien and native species (Hui et al. 2023). Within this context, density-dependent processes will build upon and heterogeneous matrix of native communities and environments (Tischendorf et al. 2005), to eventually determine invasion success. What the results of Morel-Journel et al. (2023) show is that, when the invader shows density dependence, the invasion process can be slowed down by variations in the carrying capacity of patches along the dispersal front. This can be particularly useful to manage biological invasions; ongoing invasions can be at least partially controlled by manipulating the size or quality of the patches that are most adequate to the invader, controlling host populations to reduce carrying capacity. But further, landscape manipulation of such kind could be used in a preventive way, to account in advance for the effects of the introduction of alien species for agricultural exploitation or biological control, thereby providing an additional safeguard to practices such as the introduction of parasitoids to control plagues. These practical aspects are certainly worth exploring further, together with a more explicit account of the influence of the abiotic conditions and the characteristics of the invaded communities on the success and speed of biological invasions.

REFERENCES

Hill, J.K., Griffiths, H.M. & Thomas, C.D. (2011) Climate change and evolutionary adaptations at species' range margins. Annual Review of Entomology, 56, 143-159. https://doi.org/10.1146/annurev-ento-120709-144746

Hui, C., Pyšek, P. & Richardson, D.M. (2023) Disentangling the relationships among abundance, invasiveness and invasibility in trait space. npj Biodiversity, 2, 13. https://doi.org/10.1038/s44185-023-00019-1

Hutchinson, G.E. (1978) An introduction to population biology. Yale University Press, New Haven, CT.

Levins, R. (1966) The strategy of model building in population biology. American Scientist, 54, 421-431. 

Mestre, A., Poulin, R. & Hortal, J. (2020) A niche perspective on the range expansion of symbionts. Biological Reviews, 95, 491-516. https://doi.org/10.1111/brv.12574

Morel-Journel, T., Haond, M., Duan, L., Mailleret, L. & Vercken, E. (2023) Colonisation debt: when invasion history impacts current range expansion. bioRxiv, 2022.11.13.516255, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.11.13.516255

Snäll, T., B. O'Hara, R. & Arjas, E. (2007) A mathematical and statistical framework for modelling dispersal. Oikos, 116, 1037-1050. https://doi.org/10.1111/j.0030-1299.2007.15604.x

Sakai, A.K., Allendorf, F.W., Holt, J.S., Lodge, D.M., Molofsky, J., With, K.A., Baughman, S., Cabin, R.J., Cohen, J.E., Ellstrand, N.C., McCauley, D.E., O'Neil, P., Parker, I.M., Thompson, J.N. & Weller, S.G. (2001) The population biology of invasive species. Annual Review of Ecology and Systematics, 32, 305-332. https://doi.org/10.1146/annurev.ecolsys.32.081501.114037

Soberón, J. (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecology Letters, 10, 1115-1123. https://doi.org/10.1111/j.1461-0248.2007.01107.x

Tischendorf, L., Grez, A., Zaviezo, T. & Fahrig, L. (2005) Mechanisms affecting population density in fragmented habitat. Ecology and Society, 10, 7. https://doi.org/10.5751/ES-01265-100107

Whitney, K.D. & Gabler, C.A. (2008) Rapid evolution in introduced species, 'invasive traits' and recipient communities: challenges for predicting invasive potential. Diversity and Distributions, 14, 569-580. https://doi.org/10.1111/j.1472-4642.2008.00473.x

The symbiosis with autotrophic dinoflagellate algae has enabled heterotrophic Cnidaria to thrive in nutrient-poor tropical waters (Muscatine and Porter 1977; Stanley 2006). In particular, mixotrophy, i.e. the ability to acquire nutrients through both autotrophy and heterotrophy, confers a competitive edge in oligotrophic waters, allowing photosymbiotic Cnidaria to outcompete benthic organisms limited to a single diet (e.g., McCook 2001). However, the relative importance of autotrophy vs heterotrophy in sustaining symbiotic cnidarian’s nutrition is still the subject of intense research. In fact, figuring out the cellular mechanisms by which symbiotic Cnidaria acquire a balanced diet for their metabolism and growth is relevant to our understanding of their physiology under varying environmental conditions and in response to anthropogenic perturbations.

In this study's long-term starvation experiment, Radecker & Meibom (2023) investigated the survival of the photosymbiotic sea anemone Aiptasia in the absence of heterotrophic feeding. After one year of heterotrophic starvation, Apitasia anemones remained fully viable but showed an 85 % reduction in biomass. Using 13C-bicarbonate and 15N-ammonium labeling, electron microscopy and NanoSIMS imaging, the authors could clearly show that the contribution of algal-derived nutrients to the host metabolism remained unaffected as a result of increased algal photosynthesis and more efficient carbon translocation. At the same time, the absence of heterotrophic feeding caused severe nitrogen limitation in the starved Apitasia anemones.

Overall, this study provides valuable insights into nutrient exchange within the symbiosis between Cnidaria and dinoflagellate algae at the cellular level and sheds new light on the importance of heterotrophic feeding as a nitrogen acquisition strategy for holobiont growth in oligotrophic waters.

REFERENCES

McCook L (2001) Competition between corals and algal turfs along a gradient of terrestrial influence in the nearshore central Great Barrier Reef. Coral Reefs 19:419–425. https://doi.org/10.1007/s003380000119

Muscatine L, Porter JW (1977) Reef corals: mutualistic symbioses adapted to nutrient-poor environments. Bioscience 27:454–460. https://doi.org/10.2307/1297526

Radecker N, Meibom A (2023) Symbiotic nutrient cycling enables the long-term survival of Aiptasia in the absence of heterotrophic food sources. bioRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.12.07.519152

Stanley GD Jr (2006) Photosymbiosis and the evolution of modern coral reefs. Science 312:857–858. https://doi.org/10.1126/science.1123701

Species Distribution Models (SDMs) are one of the most commonly used tools to predict where species are, where they may be in the future, and, at times, what are the variables driving this prediction. As such, applying an SDM to a dataset is akin to making a bet: that the known occurrence data are informative, that the resolution of predictors is adequate vis-à-vis the scale at which their impact is expressed, and that the model will adequately capture the shape of the relationships between predictors and predicted occurrence.

In this contribution, Lambert & Virgili (2023) perform a comprehensive assessment of different sources of complications to this process, using replicated simulations of two synthetic species. Their experimental process is interesting, in that both the data generation and the data analysis stick very close to what would happen in "real life". The use of synthetic species is particularly relevant to the assessment of SDM robustness, as they enable the design of species for which the shape of the relationship is given: in short, we know what the model should capture, and can evaluate the model performance against a ground truth that lacks uncertainty.

Any simulation study is limited by the assumptions established by the investigators; when it comes to spatial data, the "shape" of the landscape, both in terms of auto-correlation and in where the predictors are available. Lambert & Virgili (2023) nicely circumvent these issues by simulating synthetic species against the empirical distribution of predictors; in other words, the species are synthetic, but the environment for which the prediction is made is real. This is an important step forward when compared to the use of e.g. neutral landscapes (With 1997), which can have statistical properties that are not representative of natural landscapes (see e.g. Halley et al., 2004).

A striking point in the study by Lambert & Virgili (2023) is that they reveal a deep, indeed deeper than expected, stochasticity in SDMs; whether this is true in all models remains an open question, but does not invalidate their recommendation to the community: the interpretation of outcomes is a delicate exercise, especially because measures that inform on the goodness of the model fit do not capture the predictive quality of the model outputs. This preprint is both a call to more caution, and a call to more curiosity about the complex behavior of SDMs, while also providing a sensible template to perform future analyses of the potential issues with predictive models.

References

Halley, J. M., et al. (2004) “Uses and Abuses of Fractal Methodology in Ecology: Fractal Methodology in Ecology.” Ecology Letters, vol. 7, no. 3, pp. 254–71. https://doi.org/10.1111/j.1461-0248.2004.00568.x.

Lambert, Charlotte, and Auriane Virgili (2023). Data Stochasticity and Model Parametrisation Impact the Performance of Species Distribution Models: Insights from a Simulation Study. bioRxiv, ver. 2 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2023.01.17.524386

With, Kimberly A. (1997) “The Application of Neutral Landscape Models in Conservation Biology. Aplicacion de Modelos de Paisaje Neutros En La Biologia de La Conservacion.” Conservation Biology, vol. 11, no. 5, pp. 1069–80. https://doi.org/10.1046/j.1523-1739.1997.96210.x.