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13 May 2023
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Symbiotic nutrient cycling enables the long-term survival of Aiptasia in the absence of heterotrophic food sources

Constraining the importance of heterotrophic vs autotrophic feeding in photosymbiotic cnidarians

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

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

Symbiotic nutrient cycling enables the long-term survival of Aiptasia in the absence of heterotrophic food sourcesNils Radecker, Anders Meibom<p style="text-align: justify;">Phototrophic Cnidaria are mixotrophic organisms that can complement their heterotrophic diet with nutrients assimilated by their algal endosymbionts. Metabolic models suggest that the translocation of photosynthates...Eco-evolutionary dynamics, Microbial ecology & microbiology, SymbiosisUlisse Cardini2022-12-12 10:50:55 View
02 Jun 2021
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Identifying drivers of spatio-temporal variation in survival in four blue tit populations

Blue tits surviving in an ever-changing world

Recommended by ORCID_LOGO based on reviews by Ana Sanz-Aguilar and Vicente García-Navas

How long individuals live has a large influence on a number of biological processes, both for the individuals themselves as well as for the populations they live in. For a given species, survival is often summarized in curves showing the probability to survive from one age to the next. However, these curves often hide a large amount of variation in survival. Variation can occur from chance, or if individuals have different genotypes or phenotypes that can influence how long they might live, or if environmental conditions are not the same across time or space. Such spatiotemporal variations in the conditions that individuals experience can lead to complex patterns of evolution (Kokko et al. 2017) but because of the difficulties to obtain the relevant data they have not been studied much in natural populations.
 
In this manuscript, Bastianelli and colleagues (2021) identify which environmental and population conditions are associated with variation in annual survival of blue tits. The analyses are based on an impressive dataset, tracking a total of almost 5500 adults in four populations studied for at least 19 years. The authors describe two core results. First, average annual survival is lower in deciduous forests compared to evergreen forests. The differences in average annual survival between the forest types link with previously described differences, with individuals having larger clutches (Charmantier et al. 2016) and higher aggression (Dubuc-Messier et al. 2017) in the populations where adult survival is lower. Second, there are huge fluctuations from one year to the next in the percentage of individuals surviving which occur similarly in all populations. Even though survival covaried across the four populations, this variation was not associated with any of the local or global climate indices the authors investigated.
 
Studies like these are fundamental to our understanding of population change. They are important from an applied side as they can reveal the sustainability of populations and inform potential management options. On a basic research side, they reveal how evolution operates in populations. Theoretical studies predict that individuals are often not adapted to average conditions they experience, but either selected to balance the extremes they encounter  or to make the best during harsh conditions when it really matters (Lewontin & Cohen 1969).
 
This study also opens the door to new research, highlighting that demographic studies should pay attention to variation in survival and other life history traits. For blue tits specifically, the study shows that in order to understand the demography of populations we need a better mechanistic understanding of the environmental and physiological pressures influencing whether individuals die or not to make predictions whether and how climate or other ecological effects shape variation in survival.
 
References
 
Bastianelli O, Robert A, Doutrelant C, Franceschi C de, Giovannini P, Charmantier A (2021) Identifying drivers of spatio-temporal variation in survival in four blue tit populations. bioRxiv, 2021.01.28.428563, ver. 4 peer-reviewed and recommended by Peer community in Ecology. https://doi.org/10.1101/2021.01.28.428563

Charmantier A, Doutrelant C, Dubuc-Messier G, Fargevieille A, Szulkin M (2016) Mediterranean blue tits as a case study of local adaptation. Evolutionary Applications, 9, 135–152. https://doi.org/10.1111/eva.12282

Dubuc-Messier G, Réale D, Perret P, Charmantier A (2017) Environmental heterogeneity and population differences in blue tits personality traits. Behavioral Ecology, 28, 448–459. https://doi.org/10.1093/beheco/arw148

Kokko H, Chaturvedi A, Croll D, Fischer MC, Guillaume F, Karrenberg S, Kerr B, Rolshausen G, Stapley J (2017) Can Evolution Supply What Ecology Demands? Trends in Ecology & Evolution, 32, 187–197. https://doi.org/10.1016/j.tree.2016.12.005

Lewontin RC, Cohen D (1969) On Population Growth in a Randomly Varying Environment. Proceedings of the National Academy of Sciences, 62, 1056–1060. https://doi.org/10.1073/pnas.62.4.1056

Identifying drivers of spatio-temporal variation in survival in four blue tit populationsOlivier Bastianelli, Alexandre Robert, Claire Doutrelant, Christophe de Franceschi, Pablo Giovannini, Anne Charmantier<p style="text-align: justify;">In a context of rapid climate change, the influence of large-scale and local climate on population demography is increasingly scrutinized, yet studies are usually focused on one population. Demographic parameters, i...Climate change, Demography, Evolutionary ecology, Life history, Population ecologyDieter Lukas2021-01-29 15:24:23 View
26 Apr 2021
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Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) during its recent rapid colonization on its cultivated apple host (Malus domestica) in Europe

A planned experiment on local adaptation in a host-parasite system: is adaptation to the host linked to its recent domestication?

Recommended by ORCID_LOGO based on reviews by Sharon Zytynska, Alex Stemmelen and 1 anonymous reviewer

Local adaptation shall occur whenever selective pressures vary across space and overwhelm the effects of gene flow and local extinctions (Kawecki and Ebert 2004). Because the intimate interaction that characterizes their relationship exerts a strong selective pressure on both partners, host-parasite systems represent a classical example in which local adaptation is expected from rapidly evolving parasites adapting to more evolutionary constrained hosts (Kaltz and Shykoff 1998). Such systems indeed represent a large proportion of the study-cases in local adaptation research (Runquist et al. 2020). Biotic interactions intervene in many environment-related societal challenges, so that understanding when and how local adaptation arises is important not only for understanding evolutionary dynamics but also for more applied questions such as the control of agricultural pests, biological invasions, or pathogens (Parker and Gilbert 2004).

The exact conditions under which local adaptation does occur and can be detected is however still the focus of many theoretical, methodological and empirical studies (Blanquart et al. 2013, Hargreaves et al. 2020, Hoeksema and Forde 2008, Nuismer and Gandon 2008, Richardson et al. 2014). A recent review that evaluates investigations that examined the combined influence of biotic and abiotic factors on local adaptation reaches partial conclusions about their relative importance in different contexts and underlines the many traps that one has to avoid in such studies (Runquist et al. 2020). The authors of this review emphasize that one should evaluate local adaptation using wild-collected strains or populations and over multiple generations, on environmental gradients that span natural ranges of variation for both biotic and abiotic factors, in a theory-based hypothetico-deductive framework that helps interpret the outcome of experiments. These multiple targets are not easy to reach in each local adaptation experiment given the diversity of systems in which local adaptation may occur. Improving research practices may also help better understand when and where local adaptation does occur by adding controls over p-hacking, HARKing or publication bias, which is best achieved when hypotheses, date collection and analytical procedures are known before the research begins (Chambers et al. 2014). In this regard, the route taken by Olvera-Vazquez et al. (2021) is interesting. They propose to investigate whether the rosy aphid (Dysaphis plantaginea) recently adapted to its cultivated host, the apple tree (Malus domestica), and chose to pre-register their hypotheses and planned experiments on PCI Ecology (Peer Community In 2020). Though not fulfilling all criteria mentioned by Runquist et al. (2020), they clearly state five hypotheses that all relate to the local adaptation of this agricultural pest to an economically important fruit tree, and describe in details a powerful, randomized experiment, including how data will be collected and analyzed. The experimental set-up includes comparisons between three sites located along a temperature transect that also differ in local edaphic and biotic factors, and contrasts wild and domesticated apple trees that originate from the three sites and were both planted in the local, sympatric site, and transplanted to allopatric sites. Beyond enhancing our knowledge on local adaptation, this experiment will also test the general hypothesis that the rosy aphid recently adapted to Malus sp. after its domestication, a question that population genetic analyses was not able to answer (Olvera-Vazquez et al. 2020).

References

Blanquart F, Kaltz O, Nuismer SL, Gandon S (2013) A practical guide to measuring local adaptation. Ecology Letters, 16, 1195–1205. https://doi.org/10.1111/ele.12150

Briscoe Runquist RD, Gorton AJ, Yoder JB, Deacon NJ, Grossman JJ, Kothari S, Lyons MP, Sheth SN, Tiffin P, Moeller DA (2019) Context Dependence of Local Adaptation to Abiotic and Biotic Environments: A Quantitative and Qualitative Synthesis. The American Naturalist, 195, 412–431. https://doi.org/10.1086/707322

Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells PJ, Chambers CD, Feredoes E, Muthukumaraswamy SD, Etchells PJ (2014) Instead of “playing the game” it is time to change the rules: Registered Reports at <em>AIMS Neuroscience</em> and beyond. AIMS Neuroscience, 1, 4–17. https://doi.org/10.3934/Neuroscience.2014.1.4

Hargreaves AL, Germain RM, Bontrager M, Persi J, Angert AL (2019) Local Adaptation to Biotic Interactions: A Meta-analysis across Latitudes. The American Naturalist, 195, 395–411. https://doi.org/10.1086/707323

Hoeksema JD, Forde SE (2008) A Meta‐Analysis of Factors Affecting Local Adaptation between Interacting Species. The American Naturalist, 171, 275–290. https://doi.org/10.1086/527496

Kaltz O, Shykoff JA (1998) Local adaptation in host–parasite systems. Heredity, 81, 361–370. https://doi.org/10.1046/j.1365-2540.1998.00435.x

Kawecki TJ, Ebert D (2004) Conceptual issues in local adaptation. Ecology Letters, 7, 1225–1241. https://doi.org/10.1111/j.1461-0248.2004.00684.x

Nuismer SL, Gandon S (2008) Moving beyond Common‐Garden and Transplant Designs: Insight into the Causes of Local Adaptation in Species Interactions. The American Naturalist, 171, 658–668. https://doi.org/10.1086/587077

Olvera-Vazquez SG, Remoué C, Venon A, Rousselet A, Grandcolas O, Azrine M, Momont L, Galan M, Benoit L, David G, Alhmedi A, Beliën T, Alins G, Franck P, Haddioui A, Jacobsen SK, Andreev R, Simon S, Sigsgaard L, Guibert E, Tournant L, Gazel F, Mody K, Khachtib Y, Roman A, Ursu TM, Zakharov IA, Belcram H, Harry M, Roth M, Simon JC, Oram S, Ricard JM, Agnello A, Beers EH, Engelman J, Balti I, Salhi-Hannachi A, Zhang H, Tu H, Mottet C, Barrès B, Degrave A, Razmjou J, Giraud T, Falque M, Dapena E, Miñarro M, Jardillier L, Deschamps P, Jousselin E, Cornille A (2020) Large-scale geographic survey provides insights into the colonization history of a major aphid pest on its cultivated apple host in Europe, North America and North Africa. bioRxiv, 2020.12.11.421644. https://doi.org/10.1101/2020.12.11.421644

Olvera-Vazquez S.G., Alhmedi A., Miñarro M., Shykoff J. A., Marchadier E., Rousselet A., Remoué C., Gardet R., Degrave A. , Robert P. , Chen X., Porcher J., Giraud T., Vander-Mijnsbrugge K., Raffoux X., Falque M., Alins, G., Didelot F., Beliën T., Dapena E., Lemarquand A. and Cornille A. (2021) Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) to its host (Malus domestica) and to its climate in Europe. In principle recommendation by Peer Community In Ecology. https://forgemia.inra.fr/amandine.cornille/local_adaptation_dp, ver. 4.

Parker IM, Gilbert GS (2004) The Evolutionary Ecology of Novel Plant-Pathogen Interactions. Annual Review of Ecology, Evolution, and Systematics, 35, 675–700. https://doi.org/10.1146/annurev.ecolsys.34.011802.132339

Peer Community In. (2020, January 15). Submit your preregistration to Peer Community In for peer review. https://peercommunityin.org/2020/01/15/submit-your-preregistration-to-peer-community-in-for-peer-review/

Richardson JL, Urban MC, Bolnick DI, Skelly DK (2014) Microgeographic adaptation and the spatial scale of evolution. Trends in Ecology & Evolution, 29, 165–176. https://doi.org/10.1016/j.tree.2014.01.002

Experimental test for local adaptation of the rosy apple aphid (Dysaphis plantaginea) during its recent rapid colonization on its cultivated apple host (Malus domestica) in EuropeOlvera-Vazquez S.G., Alhmedi A., Miñarro M., Shykoff J. A., Marchadier E., Rousselet A., Remoué C., Gardet R., Degrave A. , Robert P. , Chen X., Porcher J., Giraud T., Vander-Mijnsbrugge K., Raffoux X., Falque M., Alins, G., Didelot F., Beliën T.,...<p style="text-align: justify;">Understanding the extent of local adaptation in natural populations and the mechanisms enabling populations to adapt to their environment is a major avenue in ecology research. Host-parasite interaction is widely se...Evolutionary ecology, PreregistrationsEric Petit2020-07-26 18:31:42 View
24 Jan 2023
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Four decades of phenology in an alpine amphibian: trends, stasis, and climatic drivers

Alpine ecology and their dynamics under climate change

Recommended by based on reviews by Nigel Yoccoz and 1 anonymous reviewer

​​Research about the effects of climate change on ecological communities has been abundant in the last decades. In particular, studies about the effects of climate change on mountain ecosystems have been key for understanding and communicating the consequences of this global phenomenon. Alpine regions show higher increases in warming in comparison to low-altitude ecosystems and this trend is likely to continue. This warming has caused reduced snowfall and/or changes in the duration of snow cover. For example, Notarnicola (2020) reported that 78% of the world’s mountain areas have experienced a snow cover decline since 2000. In the same vein, snow cover has decreased by 10% compared with snow coverage in the late 1960s (Walther et al., 2002) and snow cover duration has decreased at a rate of 5 days/decade (Choi et al., 2010). These changes have impacted the dynamics of high-altitude plant and animal populations. Some impacts are changes in the hibernation of animals, the length of the growing season for plants and the soil microbial composition (Chávez et al. 2021).

Lenzi et al. (2023), give us an excellent study using long-term data on alpine amphibian populations. Authors show how climate change has impacted the reproductive phenology of Bufo bufo, especially the breeding season starts 30 days earlier than ~40 years ago. This earlier breeding is associated with the increasing temperatures and reduced snow cover in these alpine ecosystems. However, these changes did not occur in a linear trend but a marked acceleration was observed until mid-1990s with a later stabilization. Authors associated these nonlinear changes with complex interactions between the global trend of seasonal temperatures and site-specific conditions. 

Beyond the earlier breeding season, changes in phenology can have important impacts on the long-term viability of alpine populations. Complex interactions could involve positive and negative effects like harder environmental conditions for propagules, faster development of juveniles, or changes in predation pressure. This study opens new research opportunities and questions like the urgent assessment of the global impact of climate change on animal fitness. This study provides key information for the conservation of these populations.

References

Chávez RO, Briceño VF, Lastra JA, Harris-Pascal D, Estay SA (2021) Snow Cover and Snow Persistence Changes in the Mocho-Choshuenco Volcano (Southern Chile) Derived From 35 Years of Landsat Satellite Images. Frontiers in Ecology and Evolution, 9. https://doi.org/10.3389/fevo.2021.643850

Choi G, Robinson DA, Kang S (2010) Changing Northern Hemisphere Snow Seasons. Journal of Climate, 23, 5305–5310. https://doi.org/10.1175/2010JCLI3644.1

Lenzi O, Grossenbacher K, Zumbach S, Lüscher B, Althaus S, Schmocker D, Recher H, Thoma M, Ozgul A, Schmidt BR (2022) Four decades of phenology in an alpine amphibian: trends, stasis, and climatic drivers.bioRxiv, 2022.08.16.503739, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.08.16.503739

Notarnicola C (2020) Hotspots of snow cover changes in global mountain regions over 2000–2018. Remote Sensing of Environment, 243, 111781. https://doi.org/10.1016/j.rse.2020.111781

Four decades of phenology in an alpine amphibian: trends, stasis, and climatic driversOmar Lenzi, Kurt Grossenbacher, Silvia Zumbach, Beatrice Luescher, Sarah Althaus, Daniela Schmocker, Helmut Recher, Marco Thoma, Arpat Ozgul, Benedikt R. Schmidt<p style="text-align: justify;">Strong phenological shifts in response to changes in climatic conditions have been reported for many species, including amphibians, which are expected to breed earlier. Phenological shifts in breeding are observed i...Climate change, Population ecology, ZoologySergio EstayAnonymous, Nigel Yoccoz2022-08-18 08:25:21 View
29 Sep 2023
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MoveFormer: a Transformer-based model for step-selection animal movement modelling

A deep learning model to unlock secrets of animal movement and behaviour

Recommended by ORCID_LOGO based on reviews by Jacob Davidson and 1 anonymous reviewer

The study of animal movement is essential for understanding their behaviour and how ecological or global changes impact their routines [1]. Recent technological advancements have improved the collection of movement data [2], but limited statistical tools have hindered the analysis of such data [3–5]. Animal movement is influenced not only by environmental factors but also by internal knowledge and memory, which are challenging to observe directly [6,7]. Routine movement behaviours and the incorporation of memory into models remain understudied.

Researchers have developed ‘MoveFormer’ [8], a deep learning-based model that predicts future movements based on past context, addressing these challenges and offering insights into the importance of different context lengths and information types. The model has been applied to a dataset of over 1,550 trajectories from various species, and the authors have made the MoveFormer source code available for further research.

Inspired by the step-selection framework and efforts to quantify uncertainty in movement predictions, MoveFormer leverages deep learning, specifically the Transformer architecture, to encode trajectories and understand how past movements influence current and future ones – a critical question in movement ecology. The results indicate that integrating information from a few days to two or three weeks before the movement enhances predictions. The model also accounts for environmental predictors and offers insights into the factors influencing animal movements.

Its potential impact extends to conservation, comparative analyses, and the generalisation of uncertainty-handling methods beyond ecology, with open-source code fostering collaboration and innovation in various scientific domains. Indeed, this method could be applied to analyse other kinds of movements, such as arm movements during tool use [9], pen movements, or eye movements during drawing [10], to better understand anticipation in actions and their intentionality.

References

1.           Méndez, V.; Campos, D.; Bartumeus, F. Stochastic Foundations in Movement Ecology: Anomalous Diffusion, Front Propagation and Random Searches; Springer Series in Synergetics; Springer: Berlin, Heidelberg, 2014; ISBN 978-3-642-39009-8.
https://doi.org/10.1007/978-3-642-39010-4
 
2.           Fehlmann, G.; King, A.J. Bio-Logging. Curr. Biol. 2016, 26, R830-R831.
https://doi.org/10.1016/j.cub.2016.05.033
 
3.           Jacoby, D.M.; Freeman, R. Emerging Network-Based Tools in Movement Ecology. Trends Ecol. Evol. 2016, 31, 301-314.
https://doi.org/10.1016/j.tree.2016.01.011
 
4.           Michelot, T.; Langrock, R.; Patterson, T.A. moveHMM: An R Package for the Statistical Modelling of Animal Movement Data Using Hidden Markov Models. Methods Ecol. Evol. 2016, 7, 1308-1315.
https://doi.org/10.1111/2041-210X.12578
 
5.           Wang, G. Machine Learning for Inferring Animal Behavior from Location and Movement Data. Ecol. Inform. 2019, 49, 69-76.
https://doi.org/10.1016/j.ecoinf.2018.12.002
 
6.           Noser, R.; Byrne, R.W. Change Point Analysis of Travel Routes Reveals Novel Insights into Foraging Strategies and Cognitive Maps of Wild Baboons. Am. J. Primatol. 2014, 76, 399-409.
https://doi.org/10.1002/ajp.22181
 
7.           Fagan, W.F.; Lewis, M.A.; Auger‐Méthé, M.; Avgar, T.; Benhamou, S.; Breed, G.; LaDage, L.; Schlägel, U.E.; Tang, W.; Papastamatiou, Y.P. Spatial Memory and Animal Movement. Ecol. Lett. 2013, 16, 1316-1329.
https://doi.org/10.1111/ele.12165
 
8.           Cífka, O.; Chamaillé-Jammes, S.; Liutkus, A. MoveFormer: A Transformer-Based Model for Step-Selection Animal Movement Modelling. bioRxiv 2023, ver. 4 peer-reviewed and recommended by Peer Community in Ecology.
https://doi.org/10.1101/2023.03.05.531080
 
9.           Ardoin, T.; Sueur, C. Automatic Identification of Stone-Handling Behaviour in Japanese Macaques Using LabGym Artificial Intelligence. 2023, https://doi.org/10.13140/RG.2.2.30465.02402
 
10.         Martinet, L.; Pelé, M. Drawing in Nonhuman Primates: What We Know and What Remains to Be Investigated. J. Comp. Psychol. Wash. DC 1983 2021, 135, 176-184, doi:10.1037/com0000251.
https://doi.org/10.1037/com0000251

MoveFormer: a Transformer-based model for step-selection animal movement modellingOndřej Cífka, Simon Chamaillé-Jammes, Antoine Liutkus<p style="text-align: justify;">The movement of animals is a central component of their behavioural strategies. Statistical tools for movement data analysis, however, have long been limited, and in particular, unable to account for past movement i...Behaviour & Ethology, Habitat selectionCédric Sueur2023-03-22 16:32:14 View
30 Oct 2024
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General mechanisms for a top-down origin of the predator-prey power law

Rethinking Biomass Scaling in Predators-Preys ecosystems

Recommended by based on reviews by Samraat Pawar and 1 anonymous reviewer

The study titled “General mechanisms for a top-down origin of the predator-prey power law” provides a fresh perspective on the classic predator-prey biomass relationship often observed in ecological communities. Traditionally, predator-prey dynamics have been examined through a bottom-up lens, where prey biomass and energy availability dictate predator populations. However, this study, which instead explores the possibility of a top-down origin for predator-prey power laws, offers a new dimension to our understanding of ecosystem regulation and raises questions about how predator-driven interactions might influence biomass scaling laws independently of prey abundance.

Ecologists have long noted that ecosystems often exhibit sublinear scaling between predator and prey biomasses. This pattern implies that predator biomass does not increase proportionally with prey biomass but at a slower rate, leading to a power-law relationship. Traditional explanations, such as those discussed by Peters (1983) and McGill (2006), have linked this to bottom-up processes, suggesting that increases in prey availability support, but do not fully translate to, larger predator populations due to energy losses in the trophic cascade. However, these explanations assume prey abundance as the principal driver. This new work raises an intriguing question: could density-dependent predator interactions, such as competition and interference, be equally or more important in creating this observed power law?

The authors hypothesized that density-dependent predator interactions might independently control predator biomass, even when prey is abundant. To test this, they combined predator and prey biomass dynamics equation based on a modified Lotka-Volterra model with agent-based models (ABMs) on a spatial grid, simulating predator-prey populations under varying environmental gradients and density-dependent conditions. These models allowed them to incorporate predator-specific factors, such as intraspecific competition (predator self-regulation) and predation interference, offering a quantitative framework to observe whether these top-down dynamics could indeed explain the observed biomass scaling independently of prey population changes.

Their results show that density-dependent predator dynamics, particularly at high predator densities, can yield sublinear scaling in predator-prey biomass relationships. This aligns well with empirical data, such as African mammalian ecosystems where predators seem to self-regulate under high prey availability by competing amongst themselves rather than expanding in direct proportion to prey biomass. Such findings support a shift from bottom-up perspectives to a model where top-down processes drive population regulation and biomass scaling.

I think that the work by Mazzarisi and collaborators (2024) offers a thought-provoking twist on predator-prey dynamics and suggests that our traditional frameworks may benefit from a broader, more predator-centered focus.

References

1. Onofrio Mazzarisi, Matthieu Barbier, Matteo Smerlak (2024) General mechanisms for a top-down origin of the predator-prey power law. bioRxiv, ver.2 peer-reviewed and recommended by PCI Ecology https://doi.org/10.1101/2024.04.04.588057

2. Peters, R. H. (1986). The ecological implications of body size (Vol. 2). Cambridge university press.

3. McGill, B. J. (2006). “A renaissance in the study of abundance.” Science, 314(5801), 770-772. https://doi.org/10.1126/science.1134920

General mechanisms for a top-down origin of the predator-prey power lawOnofrio Mazzarisi, Matthieu Barbier, Matteo Smerlak<p style="text-align: justify;">The ratio of predator-to-prey biomass density is not constant along ecological gradients: denser ecosystems tend to have fewer predators per prey, following a scaling relation known as the ``predator-prey power law'...Allometry, Community ecology, Food webs, Macroecology, Theoretical ecologySamir Simon Suweis2024-04-06 21:04:59 View
30 Mar 2020
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Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America

Catching the fly in dystopian times

Recommended by based on reviews by 4 anonymous reviewers

Host-parasite interactions are ubiquitous on Earth. They are present in almost every conceivable ecosystem and often result from a long history of antagonist coevolution [1,2]. Recent studies on climate change have revealed, however, that modification of abiotic variables are often accompanied by shifts in the distributional range of parasites to habitats far beyond their original geographical distribution, creating new interactions in novel habitats with unpredictable consequences for host community structure and organization [3,4]. This situation may be especially critical for endangered host species having small population abundance and restricted distribution range. The infestation of bird species with larvae of the muscid fly genus Philornis is a case in point. At least 250 bird species inhabiting mostly Central and South America are infected by Philornis flies [5,6]. Fly larval development occurs in bird faeces, nesting material, or inside nestlings, affecting the development and nestling survival.
Recent reports indicate significant reduction of bird numbers associated with recent Philornis infection, the most conspicuous being Galapagos finches [7,8]. One way to prevent this potential effect consists in to examine the expected geographical shift of Philornis fly species under future climate change scenarios so that anticipatory conservation practices become implemented for endangered bird species. In this regard, Ecological Niche Modeling (ENM) techniques have been increasingly used as a useful tool to predict disease transmission as well as the species becoming infected under different climate change scenarios [9-11]. The paper of Cuervo et al. [12] is an important advance in this regard. By identifying for the first time the macro-environmental variables influencing the abiotic niche of species of the Philornis torquans complex in southern South America, the authors perform a geographical projection model that permits identification of the areas susceptible to be colonized by Philornis species in Argentina, Brazil, and Chile, including habitats where the parasitic fly is still largely absent at present. Their results are promissory for conservation studies and contribute to the still underdeveloped issue of the way climate change impacts on antagonistic ecological relationships.

References

[1] Thompson JN (1994) The Coevolutionary Process. University of Chicago Press.
[2] Poulin R (2007) Evolutionary Ecology of Parasites: (Second Edition). Princeton University Press. doi: 10.2307/j.ctt7sn0x
[3] Pickles RSA, Thornton D, Feldman R, Marques A, Murray DL (2013) Predicting shifts in parasite distribution with climate change: a multitrophic level approach. Global Change Biology, 19, 2645–2654. doi: 10.1111/gcb.12255
[4] Marcogliese DJ (2016) The distribution and abundance of parasites in aquatic ecosystems in a changing climate: More than just temperature. Integrative and Comparative Biology, 56, 611–619. doi: 10.1093/icb/icw036
[5] Dudaniec RY, Kleindorfer S (2006) Effects of the parasitic flies of the genus Philornis (Diptera: Muscidae) on birds. Emu - Austral Ornithology, 106, 13–20. doi: 10.1071/MU04040
[6] Antoniazzi LR, Manzoli DE, Rohrmann D, Saravia MJ, Silvestri L, Beldomenico PM (2011) Climate variability affects the impact of parasitic flies on Argentinean forest birds. Journal of Zoology, 283, 126–134. doi: 10.1111/j.1469-7998.2010.00753.x
[7] Fessl B, Sinclair BJ, Kleindorfer S (2006) The life-cycle of Philornis downsi (Diptera: Muscidae) parasitizing Darwin’s finches and its impacts on nestling survival. Parasitology, 133, 739–747. doi: 10.1017/S0031182006001089
[8] Kleindorfer S, Peters KJ, Custance G, Dudaniec RY, O’Connor JA (2014) Changes in Philornis infestation behavior threaten Darwin’s finch survival. Current Zoology, 60, 542–550. doi: 10.1093/czoolo/60.4.542
[9] Johnson EE, Escobar LE, Zambrana-Torrelio C (2019) An ecological framework for modeling the geography of disease transmission. Trends in Ecology and Evolution, 34, 655–668. doi: 10.1016/j.tree.2019.03.004
[10] Carvalho BM, Rangel EF, Ready PD, Vale MM (2015) Ecological niche modelling predicts southward expansion of Lutzomyia (Nyssomyia) flaviscutellata (Diptera: Psychodidae: Phlebotominae), vector of Leishmania (Leishmania) amazonensis in South America, under climate change. PLOS ONE, 10, e0143282. doi: 10.1371/journal.pone.0143282
[11] Garrido R, Bacigalupo A, Peña-Gómez F, Bustamante RO, Cattan PE, Gorla DE, Botto-Mahan C (2019) Potential impact of climate change on the geographical distribution of two wild vectors of Chagas disease in Chile: Mepraia spinolai and Mepraia gajardoi. Parasites and Vectors, 12, 478. doi: 10.1186/s13071-019-3744-9
[12] Cuervo PF, Percara A, Monje L, Beldomenico PM, Quiroga MA (2020) Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South America. bioRxiv, 839589, ver. 5 peer-reviewed and recommended by PCI Ecology. doi: 10.1101/839589

Environmental variables determining the distribution of an avian parasite: the case of the Philornis torquans complex (Diptera: Muscidae) in South AmericaPablo F. Cuervo, Alejandro Percara, Lucas Monje, Pablo M. Beldomenico, Martín A. Quiroga<p>*Philornis* flies are the major cause of myasis in altricial nestlings of neotropical birds. Its impact ranges from subtle to lethal, being of major concern in endangered bird species with geographically-restricted, fragmented and small-sized p...Biogeography, Macroecology, Parasitology, Species distributionsRodrigo Medel2019-11-26 21:31:33 View
19 Mar 2024
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How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach

Gene flow in the city. Unravelling the mechanisms behind the variability in urbanization effects on genetic patterns.

Recommended by ORCID_LOGO based on reviews by 2 anonymous reviewers

Worldwide, city expansion is happening at a fast rate and at the same time, urbanists are more and more required to make place for biodiversity. Choices have to be made regarding the area and spatial arrangement of suitable spaces for non-human living organisms, that will favor the long-term survival of their populations. To guide those choices, it is necessary to understand the mechanisms driving the effects of land management on biodiversity.

Research results on the effects of urbanization on genetic diversity have been very diverse, with studies showing higher genetic diversity in rural than in urban populations (e.g. Delaney et al. 2010), the contrary (e.g. Miles et al. 2018) or no difference (e.g. Schoville et al. 2013). The same is true for studies investigating genetic differentiation. The reasons for these differences probably lie in the relative intensities of gene flow and genetic drift in each case study, which are hard to disentangle and quantify in empirical datasets.

In their paper, Savary et al. (2024) used an elegant and powerful simulation approach to better understand the diversity of observed patterns and investigate the effects of dispersal limitation on genetic patterns (diversity and differentiation). Their simulations involved the landscapes of 325 real European cities, each under three different scenarios mimicking 3 virtual urban tolerant species with different abilities to move within cities while genetic drift intensity was held constant across scenarios. The cities were chosen so that the proportion of artificial areas was held constant (20%) but their location and shape varied. This design allowed the authors to investigate the effect of connectivity and spatial configuration of habitat on the genetic responses to spatial variations in dispersal in cities. 

The main results of this simulation study demonstrate that variations in dispersal spatial patterns, for a given level of genetic drift, trigger variations in genetic patterns. Genetic diversity was lower and genetic differentiation was larger when species had more difficulties to move through the more hostile components of the urban environment. The increase of the relative importance of drift over gene flow when dispersal was spatially more constrained was visible through the associated disappearance of the pattern of isolation by resistance. Forest patches (usually located at the periphery of the cities) usually exhibited larger genetic diversity and were less differentiated than urban green spaces. But interestingly, the presence of habitat patches at the interface between forest and urban green spaces lowered those differences through the promotion of gene flow. 

One other noticeable result, from a landscape genetic method point of view, is the fact that there might be a limit to the detection of barriers to genetic clusters through clustering analyses because of the increased relative effect of genetic drift. This result needs to be confirmed, though, as genetic structure has only been investigated with a recent approach based on spatial graphs. It would be interesting to also analyze those results with the usual Bayesian genetic clustering approaches. 

Overall, this study addresses an important scientific question about the mechanisms explaining the diversity of observed genetic patterns in cities. But it also provides timely cues for connectivity conservation and restoration applied to cities.  
 
References

Delaney, K. S., Riley, S. P., and Fisher, R. N. (2010). A rapid, strong, and convergent genetic response to urban habitat fragmentation in four divergent and widespread vertebrates. PLoS ONE, 5(9):e12767.
https://doi.org/10.1371/journal.pone.0012767
 
Miles, L. S., Dyer, R. J., and Verrelli, B. C. (2018). Urban hubs of connectivity: Contrasting patterns of gene flow within and among cities in the western black widow spider. Proceedings of the Royal Society B, 285(1884):20181224. https://doi.org/10.1098/rspb.2018.1224
 
Savary P., Tannier C., Foltête J.-C., Bourgeois M., Vuidel G., Khimoun A., Moal H., and Garnier S. (2024). How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach. EcoEvoRxiv, ver. 3 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.32942/X2JS41.
 
Schoville, S. D., Widmer, I., Deschamps-Cottin, M., and Manel, S. (2013). Morphological clines and weak drift along an urbanization gradient in the butterfly, Pieris rapae. PLoS ONE, 8(12):e83095.
https://doi.org/10.1371/journal.pone.0083095

How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approachPaul Savary, Cécile Tannier, Jean-Christophe Foltête, Marc Bourgeois, Gilles Vuidel, Aurélie Khimoun, Hervé Moal, Stéphane Garnier<p><em>Context and objectives</em></p> <p>Although urbanization is a major driver of biodiversity erosion, it does not affect all species equally. The neutral genetic structure of populations in a given species is affected by both genetic drift a...Biodiversity, Conservation biology, Dispersal & Migration, Eco-evolutionary dynamics, Human impact, Landscape ecology, Molecular ecology, Population ecology, Spatial ecology, Metacommunities & Metapopulations, Terrestrial ecologyAurélie Coulon2023-07-25 19:09:16 View
25 Nov 2022
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Positive fitness effects help explain the broad range of Wolbachia prevalences in natural populations

Population dynamics of Wolbachia symbionts playing Dr. Jekyll and Mr. Hyde

Recommended by based on reviews by 3 anonymous reviewers

"Good and evil are so close as to be chained together in the soul"
Robert Louis Stevenson, Dr. Jekyll and Mr. Hyde


Maternally inherited symbionts—microorganisms that pass from a female host to her progeny—have two main ways of increasing their own fitness. First, they can increase the fecundity or viability of infected females. This “positive fitness effects” strategy is the one commonly used by mutualistic symbionts, such as Buchnera aphidicola—the bacterial endosymbiont of the pea aphid, Acyrthosiphon pisum [4]. Second, maternally inherited symbionts can manipulate the reproduction of infected females in a way that enhances symbiont transmission at the expense of host fitness. A famous example of this “reproductive parasitism” strategy is the cytoplasmic incompatibility (CI) [3] induced by bacteria of the genus Wolbachia in their arthropod and nematode hosts. CI works as a toxin-antidote system, whereby the sperm of infected males is modified in a lethal way (toxin) that can only be reverted if the egg is also infected (antidote) [1]. As a result, CI imposes a kind of conditional sterility on their hosts: while infected females are compatible with both infected and uninfected males, uninfected females experience high offspring mortality if (and only if) they mate with infected males [7].

These two symbiont strategies (positive fitness effects versus reproductive parasitism) have been traditionally studied separately, both empirically and theoretically. However, it has become clear that the two strategies are not mutually exclusive, and that a reproductive parasite can simultaneously act as a mutualist—an infection type that has been dubbed “Jekyll and Hyde” [6], after the famous novella by Robert Louis Stevenson about kind scientist Dr. Jekyll and his evil alter ego, Mr. Hyde. In important previous work, Zug and Hammerstein [7] analyzed the consequences of positive fitness effects on the dynamics of different kind of infections, including “Jekyll and Hyde” infections characterized by CI and other reproductive parasitism strategies. Building on this and related modeling framework, Karisto et al. [2] re-investigate and expand on the interplay between positive fitness effects and reproductive parasitism in Wolbachia infections by focusing on CI in both diplodiploid and haplodiploid populations, and by paying particular attention to the mathematical assumption structure underlying their results.

Karisto et al. begin by reviewing classic models of Wolbachia infections in diplodiploid populations that assume a “negative fitness effect” (modeled as a fertility penalty on infected females), characteristic of a pure strategy of reproductive parasitism. Together with the positive frequency-dependent effects due to CI (whereby the fitness benefits to symbionts infecting females increase with the proportion of infected males in the population) this results in population dynamics characterized by two stable equilibria (the Wolbachia-free state and an interior equilibrium with a high frequency of Wolbachia-carrying hosts) separated by an unstable interior equilibrium. Wolbachia can then spread once the initial frequency is above a threshold or an invasion barrier, but is prevented from fixing by a proportion of infections failing to be passed on to offspring. Karisto et al. show that, given the assumption of negative fitness effects, the stable interior equilibrium can never feature a Wolbachia prevalence below one-half. Moreover, they convincingly argue that a prevalence greater than but close to one-half is difficult to maintain in the presence of stochastic fluctuations, as in these cases the high-prevalence stable equilibrium would be too close to the unstable equilibrium signposting the invasion barrier.

Karisto et al. then relax the assumption of negative fitness effects and allow for positive fitness effects (modeled as a fertility premium on infected females) in a diplodiploid population. They show that positive fitness effects may result in situations where the original invasion threshold is now absent, the bistable coexistence dynamics are transformed into purely co-existence dynamics, and Wolbachia symbionts can now invade when rare. Karisto et al. conclude that positive fitness effects provide a plausible and potentially testable explanation for the low frequencies of symbiont-carrying hosts that are sometimes observed in nature, which are difficult to reconcile with the assumption of negative fitness effects. 

Finally, Karisto et al. extend their analysis to haplodiploid host populations (where all fertilized eggs develop as females). Here, they investigate two types of cytoplasmic incompatibility: a female-killing effect, similar to the CI effect studied in diplodiploid populations (the “Leptopilina type” of Vavre et al. [5]) and a masculinization effect, where CI leads to the loss of paternal chromosomes and to the development of the offspring as a male (the “Nasonia type” of Vavre et al. [5]). The models are now two-sex, which precludes a complete analytical treatment, in particular regarding the stability of fixed points. Karisto et al. compensate by conducting large numerical analyses that support their claims. Importantly, all main conclusions regarding the interplay between positive fitness effects and reproductive parasitism continue to hold under haplodiploidy. 

All in all, the analysis and results by Karisto et al. suggest that it is not necessary to resort to classical (but depending on the situation, unlikely) mechanisms, such as ongoing invasion or source-sink dynamics, to explain arthropod populations featuring low-prevalent Wolbachia infections. Instead, low-frequency equilibria might be simply due to reproductive parasites conferring beneficial fitness effects, or Wolbachia symbionts playing Dr. Jekyll (positive fitness effects) and Mr. Hyde (cytoplasmatic incompatibility). 

References

[1] Beckmann JF, Bonneau M, Chen H, Hochstrasser M, Poinsot D, Merçot H, Weill M, Sicard M, Charlat S (2019) The Toxin–Antidote Model of Cytoplasmic Incompatibility: Genetics and Evolutionary Implications. Trends in Genetics, 35, 175–185. https://doi.org/10.1016/j.tig.2018.12.004

[2] Karisto P, Duplouy A, Vries C de, Kokko H (2022) Positive fitness effects help explain the broad range of Wolbachia prevalences in natural populations. bioRxiv, 2022.04.11.487824, ver. 5 peer-reviewed and recommended by Peer Community in Ecology. https://doi.org/10.1101/2022.04.11.487824

[3] Laven H (1956) Cytoplasmic Inheritance in Culex. Nature, 177, 141–142. https://doi.org/10.1038/177141a0

[4] Perreau J, Zhang B, Maeda GP, Kirkpatrick M, Moran NA (2021) Strong within-host selection in a maternally inherited obligate symbiont: Buchnera and aphids. Proceedings of the National Academy of Sciences, 118, e2102467118. https://doi.org/10.1073/pnas.2102467118

[5] Vavre F, Fleury F, Varaldi J, Fouillet P, Bouletreau M (2000) Evidence for Female Mortality in Wolbachia-Mediated Cytoplasmic Incompatibility in Haplodiploid Insects: Epidemiologic and Evolutionary Consequences. Evolution, 54, 191–200. https://doi.org/10.1111/j.0014-3820.2000.tb00019.x

[6] Zug R, Hammerstein P (2015) Bad guys turned nice? A critical assessment of Wolbachia mutualisms in arthropod hosts. Biological Reviews, 90, 89–111. https://doi.org/10.1111/brv.12098

[7] Zug R, Hammerstein P (2018) Evolution of reproductive parasites with direct fitness benefits. Heredity, 120, 266–281. https://doi.org/10.1038/s41437-017-0022-5

Positive fitness effects help explain the broad range of Wolbachia prevalences in natural populationsPetteri Karisto, Anne Duplouy, Charlotte de Vries, Hanna Kokko<p style="text-align: justify;">The bacterial endosymbiont <em>Wolbachia</em> is best known for its ability to modify its host’s reproduction by inducing cytoplasmic incompatibility (CI) to facilitate its own spread. Classical models predict eithe...Host-parasite interactions, Population ecologyJorge Peña2022-04-12 12:52:55 View
27 Jan 2023
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Spatial heterogeneity of interaction strength has contrasting effects on synchrony and stability in trophic metacommunities

How does spatial heterogeneity affect stability of trophic metacommunities?

Recommended by ORCID_LOGO based on reviews by Phillip P.A. Staniczenko, Ludek Berec and Diogo Provete

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.

Spatial heterogeneity of interaction strength has contrasting effects on synchrony and stability in trophic metacommunitiesPierre Quévreux, Bart Haegeman and Michel Loreau<p>&nbsp;Spatial heterogeneity is a fundamental feature of ecosystems, and ecologists have identified it as a factor promoting the stability of population dynamics. In particular, differences in interaction strengths and resource supply between pa...Dispersal & Migration, Food webs, Interaction networks, Spatial ecology, Metacommunities & Metapopulations, Theoretical ecologyWerner Ulrich2022-10-26 13:38:34 View