Modeling species co‐occurrence by multivariate logistic regression generates new hypotheses on fungal interactions

Ovaskainen, Otso; Hottola, Jenni; Siitonen, Juha

doi:10.1890/10-0173.1

Cited by 246 publications

(185 citation statements)

References 23 publications

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“…As suggested by previous studies [13,14], the results of the simple model I used here reveal that non-random cooccurrence patterns can emerge even when species have no pre-determined interspecific interactions. In such cases, significant segregated patterns are expected to occur simply due to spatial turnover when species have sufficiently different niche requirements (or are affected by dispersal limitations) [18].…”

Section: Discussionsupporting

confidence: 75%

Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities

Bar‐Massada

2015

Proc. R. Soc. B.

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ResearchCite this article: Bar-Massada A. 2015 Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities. Proc. R. Soc. Species co-occurrence analysis is commonly used to assess how interspecific interactions dictate community assembly. Non-random co-occurrences, however, may also emerge from niche differences as well as environmental heterogeneity. The relationships between species co-occurrence patterns, environmental heterogeneity and species niches are not fully understood, due to complex interactions among them. To analyse the relationships among these patterns and processes, I developed synthetic community models and analysed a large dataset of tree species across the conterminous United States. Niche overlap and environmental heterogeneity had significant and contrasting effects on species co-occurrence patterns, in both modelled and real communities. Niche breadth, in turn, affected the effect sizes of both variables on species cooccurrence patterns. The effect of niche breadth on the relationship between co-occurrence and niche overlap was markedly consistent between modelled and real communities, while its effect on the relationship between co-occurrence and environmental heterogeneity was mostly consistent between real and modelled data. The results of this analysis highlight the complex and interactive effects of species niche overlap, niche breadth and environmental heterogeneity on species co-occurrence patterns. Therefore, inferring ecological processes from co-occurrence patterns without accounting for these fundamental characteristics of species and environments may lead to biased conclusions.

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Section: Discussionsupporting

confidence: 75%

Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities

Bar‐Massada

2015

Proc. R. Soc. B.

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“…Therefore, it would be interesting to compare this kind of community-level models with new promising approaches that consider more explicitly species interactions [54]. For instance, the use of multivariate logistic regressions based on spatial multispecies co-occurrence patterns [55] needs to be explored in a context of environmental change.…”

Section: Discussionmentioning

confidence: 99%

Assessing Community-Level and Single-Species Models Predictions of Species Distributions and Assemblage Composition after 25 Years of Land Cover Change

2013

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To predict the impact of environmental change on species distributions, it has been hypothesized that community-level models could give some benefits compared to species-level models. In this study we have assessed the performance of these two approaches. We surveyed 256 bird communities in an agricultural landscape in southwest France at the same locations in 1982 and 2007. We compared the ability of CQO (canonical quadratic ordination; a method of community-level GLM) and GLMs (generalized linear models) to i) explain species distributions in 1982 and ii) predict species distributions, community composition and species richness in 2007, after land cover change. Our results show that models accounting for shared patterns between species (CQO) slightly better explain the distribution of rare species than models that ignore them (GLMs). Conversely, the predictive performances were better for GLMs than for CQO. At the assemblage level, both CQO and GLMs overestimated species richness, compared with that actually observed in 2007, and projected community composition was only moderately similar to that observed in 2007. Species richness projections tended to be more accurate in sites where land cover change was more marked. In contrast, the composition projections tended to be less accurate in those sites. Both modelling approaches showed a similar but limited ability to predict species distribution and assemblage composition under conditions of land cover change. Our study supports the idea that our community-level model can improve understanding of rare species patterns but that species-level models can provide slightly more accurate predictions of species distributions. At the community level, the similar performance of both approaches for predicting patterns of assemblage variation suggests that species tend to respond individualistically or, alternatively, that our community model was unable to effectively account for the emergent community patterns.

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“…When using modelling approaches, it is, however, essential to incorporate all the influential predictors to the models to avoid a situation where species co-occurrence patterns only represent shared physiological tolerances and/or requirements of species (Ovaskainen et al 2010). …”

Section: Introductionmentioning

confidence: 99%

Contrasting effects of biotic interactions on richness and distribution of vascular plants, bryophytes and lichens in an arctic–alpine landscape

et al. 2015

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Biotic interactions may strongly affect the distribution of individual species and the resulting patterns of species richness. However, the impacts can vary depending on the species or taxa examined, suggesting that the influences of interactions on species distributions and diversity are not always straightforward and can be taxon-contingent. The aim of this study was therefore to examine how the importance of biotic interactions varies within a community. We incorporated three biotic predictors (cover of the dominant vascular species) into two correlative species richness modelling frameworks to predict spatial variation in the number of vascular plants, bryophytes and lichens in arctic-alpine Fennoscandia, in N Europe. In addition, predictions based on single-species distribution models were used to determine the nature of the impact (negative vs. positive outcome) of the three dominant species on individual vascular plant, bryophyte and lichen species. Our results suggest that biotic variables can be as important as abiotic variables, but their relative contributions in explaining the richness of sub-dominant species varies among dominant species, species group and the modelling framework implemented. Similarly, the impacts of biotic interactions on individual species varied among the three species groups and dominant species, with the observed patterns partly reflecting species' biogeographic range. Our study provides additional support for the importance of biotic interactions in modifying arctic-alpine biodiversity patterns, and highlights that the impacts of interactions are not constant across taxa or biotic drivers. The influence of biotic interactions, including the taxon-contingency and range-based impacts, should therefore be accounted for when developing biodiversity forecasts.

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Modeling species co‐occurrence by multivariate logistic regression generates new hypotheses on fungal interactions

Cited by 246 publications

References 23 publications

Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities

Complex relationships between species niches and environmental heterogeneity affect species co-occurrence patterns in modelled and real communities

Assessing Community-Level and Single-Species Models Predictions of Species Distributions and Assemblage Composition after 25 Years of Land Cover Change

Contrasting effects of biotic interactions on richness and distribution of vascular plants, bryophytes and lichens in an arctic–alpine landscape

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