Biotic interactions drive species occurrence and richness in dynamic beach environments

Nylén, Tua; Roux, Peter C. le; Luoto, Miska

doi:10.1007/s11258-013-0266-y

Cited by 36 publications

(11 citation statements)

References 34 publications

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“…Many studies have concluded that biotic interactions have an important role in improving species distribution predictions (Araújo & Luoto, 2007;Kissling et al, 2012;Nylén et al, 2013;le Roux et al, 2013); our results support this conclusion for macrophytes, particularly in the case of eutrophication that increased indirect facilitation among macrophytes. This finding suggests that the biotic interaction among macrophytes could be critical in predicting their occurrence.…”

Section: Discussionsupporting

confidence: 87%

“…The predicted occurrence probabilities were then converted to binary presence/absence predictions using a threshold that maximized the sensitivity and specificity of the model during cross‐validation, from which the true skill statistic (TSS) and kappa were calculated (Allouche, Tsoar, & Kadmon, ). The differences in the predictive power between null models and full models were tested using a Mann–Whitney test (Nylén et al., ; le Roux et al., ).…”

Section: Methodsmentioning

confidence: 99%

“…Few studies have considered horizontal interactions (i.e., the relation between submerged macrophytes) as explanatory factors. Recent studies have demonstrated that the incorporation of horizontal biotic interactions improves the accuracy of predictions on both a plot scale (Nylén, Le Roux, & Luoto, ; le Roux, Lenoir, Pellissier, Wisz, & Luoto, ) and a regional scale (Latimer, Banerjee, Sang, Mosher, & Silander, ) and have indicated that the interactions among plants play an important role in the spatial distribution of multispecies assemblages (Nylén et al., ; le Roux et al., ).…”

Section: Introductionmentioning

confidence: 99%

“…To this end, we analyzed the spatial presence/absence data of four common submerged macrophytes during two periods (1959 and 2009) in Dianshan Lake, which became eutrophic since the 1980s. We hypothesized that (H1) models with both abiotic and biotic variables would more accurately predict spatial distributions than models including only abiotic variables in each alternative regime state (Nylén et al., ; le Roux et al., ), and the improvement effects could enhance in eutrophication state. Moreover, we expected (H2) that the biotic interactions would be more positive (facilitation) due to the regime shift caused by eutrophication (Brooker et al., ; Le Bagousse‐Pinguet et al., ; McIntire & Fajardo, ).…”

Section: Introductionmentioning

confidence: 99%

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Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication

Song

Cui

Zhang

et al. 2017

Ecology and Evolution

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Water eutrophication creates unfavorable environmental conditions for submerged macrophytes. In these situations, biotic interactions may be particularly important for explaining and predicting the submerged macrophytes occurrence. Here, we evaluate the roles of biotic interactions in predicting spatial occurrence of submerged macrophytes in 1959 and 2009 for Dianshan Lake in eastern China, which became eutrophic since the 1980s. For the four common species occurred in 1959 and 2009, null species distribution models based on abiotic variables and full models based on both abiotic and biotic variables were developed using generalized linear model (GLM) and boosted regression trees (BRT) to determine whether the biotic variables improved the model performance. Hierarchical Bayesian‐based joint species distribution models capable of detecting paired biotic interactions were established for each species in both periods to evaluate the changes in the biotic interactions. In most of the GLM and BRT models, the full models showed better performance than the null models in predicting the species presence/absence, and the relative importance of the biotic variables in the full models increased from less than 50% in 1959 to more than 50% in 2009 for each species. Moreover, co‐occurrence correlation of each paired species interaction was higher in 2009 than that in 1959. The findings suggest biotic interactions that tend to be positive play more important roles in the spatial distribution of multispecies assemblages of macrophytes and should be included in prediction models to improve prediction accuracy when forecasting macrophytes’ distribution under eutrophication stress.

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Section: Discussionsupporting

confidence: 87%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication

Song

Cui

Zhang

et al. 2017

Ecology and Evolution

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“…Furthermore, yearly occurring sea ice is an important geomorphic factor. In this analysis, we included all those 39 natural sandy beaches that had clear successional zonation of vegetation and were not severely degraded by trampling or eutrophication (Figure ; Nylén et al ., ). The selected beaches cover a wide geographical area (c. 60° N–65° N) and have different climatic and openness characteristics as well as different land uplift rates (1.6–7.3 mm/a) and availability of sediment (Johansson et al ., ; Pirinen et al ., ; Figure ).…”

Section: Study Areamentioning

confidence: 99%

Determinants of sediment properties and organic matter in beach and dune environments based on boosted regression trees

Nylén

Hellemaa

Luoto

2015

Earth Surf Processes Landf

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Grain size properties and the variation of organic matter in coastal beach and dune environments are assumed to be controlled by the intensity of aeolian processes, time and the sediment source. However, assumptions are based on relatively limited empirical studies. In this study, we examined which environmental variables are the main predictors of multiple topsoil properties. To achieve this, we analysed an extensive dataset systematically collected across all beach zones and a large geographical area at the Finnish Baltic Sea coast characterized by post‐glacial land uplift. We included a comprehensive set of predictors in the analysis and applied boosted regression trees, a modern modelling technique particularly suited for analysis without prior assumptions of the data model. The results suggest that mean grain size and sorting are mainly determined by northing and fetch. Northing, disturbance and fetch predicted the variation of soil organic matter while litter cover was strongly related to disturbance. Based on the analyses, we were able to identify the main drivers of multiple topsoil properties on land uplift beaches. Parent material is suggested to determine sediment textural properties, which largely masks the effects of transient processes. Mean grain size and sorting are highly interdependent: grains become finer and sorting improves with increasing shore exposure. The intensity of momentary geomorphic processes controls the accumulation of litter whereas the slower accumulation of organic matter in the soil is influenced also by the static exposure setting. Skewness and kurtosis of the grain size distribution are mainly influenced by unmeasured processes, potentially relating to the geomorphological origin of the sediment. Copyright © 2014 John Wiley & Sons, Ltd.

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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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Biotic interactions drive species occurrence and richness in dynamic beach environments

Cited by 36 publications

References 34 publications

Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication

Enhanced effects of biotic interactions on predicting multispecies spatial distribution of submerged macrophytes after eutrophication

Determinants of sediment properties and organic matter in beach and dune environments based on boosted regression trees

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

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