Browsing by Subject "species interactions"

Sort by: Order: Results:

Now showing items 1-8 of 8
  • Norberg, Anna; Abrego Antia, Nerea; Blanchet, F. Guillaume; Adler, Frederick R.; Anderson, Barbara J.; Anttila, Jani; Araújo, Miguel B.; Dallas, Tad Anthony; Dunson, David; Elith, Jane; Foster, Scott; Fox, Richard; Franklin, Janet; Godsoe, William; Guisan, Antoine; O'Hara, Bob; Hill, Nicole A.; Holt, Robert D.; Hui, Francis K.C; Husby, Magne; Kålås, John Atle; Lehikoinen, Aleksi; Luoto, Miska; Mod, Heidi K.; Newell, Graeme; Renner, Ian; Roslin, Tomas Valter; Soininen, Janne; Thuiller, Wilfried; Vanhatalo, Jarno Petteri; Warton, David; White, Matt; Zimmermann, Niklaus E.; Gravel, Dominique; Ovaskainen, Otso Tapio (2019)
    A large array of species distribution model (SDM) approaches has been developed for explaining and predicting the occurrences of individual species or species assemblages. Given the wealth of existing models, it is unclear which models perform best for interpolation or extrapolation of existing data sets, particularly when one is concerned with species assemblages. We compared the predictive performance of 33 variants of 15 widely applied and recently emerged SDMs in the context of multispecies data, including both joint SDMs that model multiple species together, and stacked SDMs that model each species individually combining the predictions afterward. We offer a comprehensive evaluation of these SDM approaches by examining their performance in predicting withheld empirical validation data of different sizes representing five different taxonomic groups, and for prediction tasks related to both interpolation and extrapolation. We measure predictive performance by 12 measures of accuracy, discrimination power, calibration, and precision of predictions, for the biological levels of species occurrence, species richness, and community composition. Our results show large variation among the models in their predictive performance, especially for communities comprising many species that are rare. The results do not reveal any major trade-offs among measures of model performance; the same models performed generally well in terms of accuracy, discrimination, and calibration, and for the biological levels of individual species, species richness, and community composition. In contrast, the models that gave the most precise predictions were not well calibrated, suggesting that poorly performing models can make overconfident predictions. However, none of the models performed well for all prediction tasks. As a general strategy, we therefore propose that researchers fit a small set of models showing complementary performance, and then apply a cross-validation procedure involving separate data to establish which of these models performs best for the goal of the study.
  • Kahilainen, Aapo; Oostra, Vicencio; Somervuo, Panu; Minard, Guillaume; Saastamoinen, Marjo (2022)
    Predicting how climate change affects biotic interactions poses a challenge. Plant-insect herbivore interactions are particularly sensitive to climate change, as climate-induced changes in plant quality cascade into the performance of insect herbivores. Whereas the immediate survival of herbivore individuals depends on plastic responses to climate change-induced nutritional stress, long-term population persistence via evolutionary adaptation requires genetic variation for these responses. To assess the prospects for population persistence under climate change, it is therefore crucial to characterize response mechanisms to climate change-induced stressors, and quantify their variability in natural populations. Here, we test developmental and transcriptomic responses to water limitation-induced host plant quality change in a Glanville fritillary butterfly (Melitaea cinxia) metapopulation. We combine nuclear magnetic resonance spectroscopy on the plant metabolome, larval developmental assays and an RNA sequencing analysis of the larval transcriptome. We observed that responses to feeding on water-limited plants, in which amino acids and aromatic compounds are enriched, showed marked variation within the metapopulation, with individuals of some families performing better on control and others on water-limited plants. The transcriptomic responses were concordant with the developmental responses: families exhibiting opposite developmental responses also produced opposite transcriptomic responses (e.g. in growth-associated transcripts). The divergent responses in both larval development and transcriptome are associated with differences between families in amino acid catabolism and storage protein production. The results reveal intrapopulation variability in plasticity, suggesting that the Finnish M. cinxia metapopulation harbours potential for buffering against drought-induced changes in host plant quality.
  • Byholm, Patrik; Burgas, Daniel; Virtanen, Tarmo; Valkama, Jari (2012)
  • Sandal, Lisa; Grotan, Vidar; Saether, Bernt-Erik; Freckleton, Robert P.; Noble, David G.; Ovaskainen, Otso (2022)
    Our knowledge of the factors affecting species abundances is mainly based on time-series analyses of a few well-studied species at single or few localities, but we know little about whether results from such analyses can be extrapolated to the community level. We apply a joint species distribution model to long-term time-series data on British bird communities to examine the relative contribution of intra- and interspecific density dependence at different spatial scales, as well as the influence of environmental stochasticity, to spatiotemporal interspecific variation in abundance. Intraspecific density dependence has the major structuring effect on these bird communities. In addition, environmental fluctuations affect spatiotemporal differences in abundance. In contrast, species interactions had a minor impact on variation in abundance. Thus, important drivers of single-species dynamics are also strongly affecting dynamics of communities in time and space.
  • Candolin, Ulrika; Bertell, Elina; Kallio, Jarkko (2018)
    1. Alien species are altering ecosystems around the globe. To predict and manage their impacts, the underlying mechanisms need to be understood. This is challenging in ecosystems undergoing multiple disturbances as unexpected interactions can alter the impact of individual disturbances. Such interactions are likely to be common in disturbed ecosystems, but have so far received little attention. 2. We investigated whether interactions between an invading shrimp Palaemon elegans and another human-induced disturbance, the population growth of a native mesopredator, the threespine stickleback, influences a third human-induced disturbance, the increase in biomass of filamentous algae. Increases in both the native mesopredator population and algal biomass have been promoted by eutrophication and a trophic cascade triggered by declining predatory fish stocks. 3. We used mesocosm and field enclosure experiments, combined with analyses of long-term trends in the abundance of the invader and the native mesopredator, to dissect the influence of the two species on algal biomass when alone and when co-occurring. 4. The impact of the invader on algal biomass depended on the native mesopredator; shrimp on their own had no effect on algal growth, but mitigated algae accumulation when competing with the stickleback for resources. Competition caused the shrimp to shift its diet from grazers to algae, and its habitat choice from open to vegetated habitats. The native mesopredator, in contrast, increased algal biomass irrespective of the presence of the invader, by preying on grazers and inducing a trophic cascade. 5. Our results show that the presence of a native mesopredator causes an invader to alter its behaviour and thereby its ecological impact. This demonstrates that interactions between invaders and other anthropogenic disturbances can alter the ecological impact of invaders, and, notably, that the impact of invaders can be positive and stabilize disturbed ecosystems. These results stress the importance of considering interactions among disturbances when investigating the ecological impact of alien species.
  • Opedal, Øystein H.; von Numers, Mikael; Tikhonov, Gleb; Ovaskainen, Otso (2020)
    Abstract Predicting the dynamics of biotic communities is difficult because species? environmental responses are not independent, but covary due to shared or contrasting ecological strategies and the influence of species interactions. We used latent-variable joint species distribution models to analyse paired historical and contemporary inventories of 585 vascular plant species on 471 islands in the south-west Finnish archipelago. Larger, more heterogeneous islands were characterized by higher colonisation rates and lower extinction rates. Ecological and taxonomical species groups explained small but detectable proportions of variance in species? environmental responses. To assess the potential influence of species interactions on community dynamics, we estimated species associations as species-to-species residual correlations for historical occurrences, for colonisations, and for extinctions. Historical species associations could to some extent predict joint colonisation patterns, but the overall estimated influence of species associations on community dynamics was weak. These results illustrate the benefits of considering metacommunity dynamics within a joint framework, but also suggest that any influence of species interactions on community dynamics may be hard to detect from observational data.
  • Cameron, Erin K.; Sundqvist, Maja K.; Keith, Sally A.; CaraDonna, Paul J.; Mousing, Erik A.; Nilsson, Karin A.; Metcalfe, Daniel B.; Classen, Aimée T. (2019)
    Abstract Trophic interactions within food webs affect species distributions, coexistence, and provision of ecosystem services but can be strongly impacted by climatic changes. Understanding these impacts is therefore essential for managing ecosystems and sustaining human well-being. Here, we conducted a global synthesis of terrestrial, marine, and freshwater studies to identify key gaps in our knowledge of climate change impacts on food webs and determine whether the areas currently studied are those most likely to be impacted by climate change. We found research suffers from a strong geographic bias, with only 3.5% of studies occurring in the tropics. Importantly, the distribution of sites sampled under projected climate changes was biased?areas with decreases or large increases in precipitation and areas with low magnitudes of temperature change were under-represented. Our results suggest that understanding of climate change impacts on food webs could be broadened by considering more than two trophic levels, responses in addition to species abundance and biomass, impacts of a wider suite of climatic variables, and tropical ecosystems. Most importantly, to enable better forecasts of biodiversity responses to climate change, we identify critically under-represented geographic regions and climatic conditions which should be prioritized in future research.