Browsing by Subject "Community ecology"

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  • Becker-Scarpitta, Antoine; Auberson-Lavoie, Diane; Aussenac, Raphael; Vellend, Mark (2022)
    Despite many studies showing biodiversity responses to warming, the generality of such responses across taxonomic groups remains unclear. Very few studies have tested for evidence of bryophyte community responses to warming, even though bryophytes are major contributors to diversity and functioning in many ecosystems. Here, we report an empirical study comparing long-term change in bryophyte and vascular plant communities in two sites with contrasting long-term warming trends, using "legacy" botanical records as a baseline for comparison with contemporary resurveys. We hypothesized that ecological changes would be greater in sites with a stronger warming trend and that vascular plant communities, with narrower climatic niches, would be more sensitive than bryophyte communities to climate warming. For each taxonomic group in each site, we quantified the magnitude of changes in species' distributions along the elevation gradient, species richness, and community composition. We found contrasted temporal changes in bryophyte vs. vascular plant communities, which only partially supported the warming hypothesis. In the area with a stronger warming trend, we found a significant increase in local diversity and dissimilarity (beta-diversity) for vascular plants, but not for bryophytes. Presence-absence data did not provide sufficient power to detect elevational shifts in species distributions. The patterns observed for bryophytes are in accordance with recent literature showing that local diversity can remain unchanged despite strong changes in composition. Regardless of whether one taxon is systematically more or less sensitive to environmental change than another, our results suggest that vascular plants cannot be used as a surrogate for bryophytes in terms of predicting the nature and magnitude of responses to warming. Thus, to assess overall biodiversity responses to global change, abundance data from different taxonomic groups and different community properties need to be synthesized.
  • Heino, Jani; Grönroos, Mira (2017)
    It was recently suggested that beta diversity can be partitioned into contributions of single sites to overall beta diversity (LCBD) or into contributions of individual species to overall beta diversity (SCBD). We explored the relationships of LCBD and SCBD to site and species characteristics, respectively, in stream insect assemblages. We found that LCBD was mostly explained by variation in species richness, with a negative relationship being detected. SCBD was strongly related to various species characteristics, such as occupancy, abundance, niche position and niche breadth, but was only weakly related to biological traits of species. In particular, occupancy and its quadratic terms showed a very strong unimodal relationship with SCBD, suggesting that intermediate species in terms of site occupancy contribute most to beta diversity. Our findings of unravelling the contributions of sites or species to overall beta diversity are of high importance to community ecology, conservation and bioassessment using stream insect assemblages, and may bear some overall generalities to be found in other organism groups.
  • Sgarbi, Luciano F.; Bini, Luis M.; Heino, Jani; Jyrkankallio-Mikkola, Jenny; Landeiro, Victor L.; Santos, Edineusa P.; Schneck, Fabiana; Siqueira, Tadeu; Soininen, Janne; Tolonen, Kimmo T.; Melo, Adriano S. (2020)
    Reliable biological assessments are essential to answer ecological and management questions but require well-designed studies and representative sample sizes. However, large sampling effort is rarely possible, because it demands large financial resources and time, restricting the number of sites sampled, the duration of the study and the sampling effort at each site. In this context, we need methods and protocols allowing cost-effective surveys that would, consequently, increase the knowledge about how biodiversity is distributed in space and time. Here, we assessed the minimal sampling effort required to correctly estimate the assemblage structure of stream insects sampled in near-pristine boreal and subtropical regions. We used five methods grouped into two different approaches. The first approach consisted of the removal of individuals 1) randomly or 2) based on a count threshold. The second approach consisted of simplification in terms of 1) sequential removal from rare to common species; 2) sequential removal from common to rare species; and 3) random species removal. The reliability of the methods was assessed using Procrustes analysis, which indicated the correlation between a reduced matrix (after removal of individuals or species) and the complete matrix. In many cases, we found a strong relationship between ordination patterns derived from presence/absence data (the extreme count threshold of a single individual) and those patterns derived from abundance data. Also, major multivariate patterns derived from the complete data matrices were retained even after the random removal of more than half of the individuals. Procrustes correlation was generally high ( > 0.8), even with the removal of 50% of the species. Removal of common species produced lower correlation than removal of rare species, indicating higher importance of the former to estimate resemblance between assemblages. Thus, we conclude that sampling designs can be optimized by reducing the sampling effort at a site. We recommend that such efforts saved should be redirected to increase the number of sites studied and the duration of the studies, which is essential to encompass larger spatial, temporal and environmental extents, and increase our knowledge of biodiversity.
  • Dallas, T.A.; Carlson, C.J.; Poisot, T. (2019)
    Predicting disease emergence and outbreak events is a critical task for public health professionals and epidemiologists. Advances in global disease surveillance are increasingly generating datasets that are worth more than their component parts for prediction-oriented work. Here, we use a trait-free approach which leverages information on the global community of human infectious diseases to predict the biogeography of pathogens through time. Our approach takes pairwise dissimilarities between countries’ pathogen communities and pathogens’ geographical distributions and uses these to predict country–pathogen associations. We compare the success rates of our model for predicting pathogen outbreak, emergence and re-emergence potential as a function of time (e.g. number of years between training and prediction), pathogen type (e.g. virus) and transmission mode (e.g. vector-borne). With only these simple predictors, our model successfully predicts basic network structure up to a decade into the future. We find that while outbreak and re-emergence potential are especially well captured by our simple model, prediction of emergence events remains more elusive, and sudden global emergences like an influenza pandemic are beyond the predictive capacity of the model. However, these stochastic pandemic events are unlikely to be predictable from such coarse data. Together, our model is able to use the information on the existing country–pathogen network to predict pathogen outbreaks fairly well, suggesting the importance in considering information on co-occurring pathogens in a more global view even to estimate outbreak events in a single location or for a single pathogen. © 2019 The Authors. Published by the Royal Society under the terms of the Creative Commons Attribution License, which permits unrestricted use, provided the original author and source are credited.