Assessing Biological Orders of river sites and biological structures of watercourses using ecological traits of aquatic insects

Verneaux, J.; Verneaux, Valérie; Schmitt, Aimé; Prouteau, C.

doi:10.1023/b:hydr.0000026483.41753.d3

Cited by 7 publications

(5 citation statements)

References 21 publications

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“…6c). Additionally, the diffusion map indicates potential clustering within the upper and lower halves of the river which may correspond with the salmonid and cyprinid regions previously identified by Verneaux et al (2003). While an upstreamdownstream pattern of compositional change is evident in the two-dimensional NMDS configuration, it does not as clearly indicate how strongly community composition is shaped by a single gradient.…”

Section: Resultsmentioning

confidence: 83%

“…Finally, we applied diﬀusion maps to a previously well‐characterized empirical dataset: ﬁsh assemblages along the Doubs river (Verneaux 1973, Verneaux et al 2003). The Doubs river and its tributaries span an 832 km network near the France–Switzerland border in the Jura mountains.…”

Section: Evaluation With Simulated and Empirical Datamentioning

confidence: 99%

“…The Doubs river and its tributaries span an 832 km network near the France–Switzerland border in the Jura mountains. Fish and insect communities have previously been shown to exhibit continuous compositional change along an upstream–downstream gradient in the river system (Verneaux et al 2003). This dataset therefore presents an ideal test for diﬀusion maps ability to recover the main dimensions of variation in compositional data.…”

Section: Evaluation With Simulated and Empirical Datamentioning

confidence: 99%

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Dissimilarity analysis based on diffusion maps

Gault,

Freund,

Hillebrand

et al. 2023

Oikos

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Compositional measurements from species assemblages define a high dimensional dataspace in which the data can form complex structures, termed manifolds. Comparing assemblages in this dataspace is difficult because the data is often sparse relative to its dimensionality and the complex structure of the manifold introduces bias and error in measurements of distance. Here, we apply diffusion maps, a manifold learning method, to find and characterize manifolds in high‐dimensional compositional data. We show that diffusion maps embed the data in reduced dimensions in which the Euclidean distance between data points approximates the distance between them along the manifold. This is especially useful when species turnover is high, as it provides a way to measure meaningful distances between assemblages even when they harbor disjoint sets of species. We anticipate diffusion maps will therefore be particularly useful for characterizing community change over large spatial and temporal scales.

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Section: Resultsmentioning

confidence: 83%

Section: Evaluation With Simulated and Empirical Datamentioning

confidence: 99%

Section: Evaluation With Simulated and Empirical Datamentioning

confidence: 99%

See 1 more Smart Citation

Dissimilarity analysis based on diffusion maps

Gault,

Freund,

Hillebrand

et al. 2023

Oikos

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“…At the Mouthier site of the Upper Loue River (French Jura; 374 m a.s.l. ), D. mixtus was recorded together with Rhyacophila tristis Pictet., Glossosoma conformis Neboiss, Agapetus fuscipes Curtis, Ecclisopteryx guttulata (Pictet), Chaetopteryx villosa (Fabricius), Halesus radiatus (Curtis) , Potamophylax cingulatus (Stephens) , Silo nigricornis (Pictet) , Odontocerum albicorne (Scopoli) and another 25 Trichoptera species (Verneaux et al, 2004). The distance to the spring of this karstic outlet was 5.4 km, its width 14 m, the mean low water discharge 4.6 m 3 s −1 , the slope 4‰ and the conductivity was 345 μS cm −1 (Verneaux et al, 2004).…”

Section: Resultsmentioning

confidence: 99%

Description of the larval stage of Drusus mixtus (Pictet, 1834) (Trichoptera: Limnephilidae: Drusinae) with notes on its ecology and zoogeography

et al. 2011

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In the Swiss Jura adults of Drusus mixtus and unknown Drusinae larvae which could not be identified with existing keys were sampled. Based on ripe pupae, the unknown larvae were identified as D. mixtus. The association was confirmed by specimen rearing in aquaria.Based on morphology, larvae of Drusus mixtus key out together with D. croaticus in existing keys. D. mixtus is separated from the latter species by the shape of the anteromedian metanotal sclerites which are broadly triangular, whereas in D. croaticus the sclerites are almost parallel-sided, resembling a stretched rectangle. In addition, the two species are geographically well separated: D. croaticus is restricted to the confines of Croatia and Slovenia, whereas D. mixtus is only present in Switzerland and eastern France. With this present paper, all Central European Drusinae species except Drusus chapmani MCL, 1901 (France, Switzerland) and D. noricus MALICKY, 1981, an endemic from the Saualpe (Carinthia, Austria), are known in the larval stage.

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“…We illustrate the functionalities of rdacca.hp using the Doubs River fish data available in the ade4 package (Thioulouse et al, 2018). The dataset consists of the distributions of 27 fish species described by abundance classes (ranging from 0 to 5) and 11 quantitative environmental variables describing river morphology and water quality across 30 sites along the Doubs River in the Jura Mountains, near the France–Switzerland border (also see Verneaux et al, 2003). We have excluded one environmental variable ( dfs , distance from the source) as it represents spatial positioning rather than an environmental variable per se.…”

Section: A Working Examplementioning

confidence: 99%

Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package

Zou

Zhang³

et al. 2022

Methods Ecol Evol

540

154

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1. Canonical analysis, a generalization of multiple regression to multiple-response variables, is widely used in ecology. Because these models often involve many parameters (one slope per response per predictor), they pose challenges to model interpretation. Among these challenges, we lack quantitative frameworks for estimating the overall importance of single predictors in multi-response regression models.2. Here we demonstrate that commonality analysis and hierarchical partitioning, widely used for both estimating predictor importance and improving the interpretation of single-response regression models, are related and complementary frameworks that can be expanded for the analysis of multiple-response models.3. In this application, we (a) demonstrate the mathematical links between commonality analysis, variation and hierarchical partitioning; (b) generalize these frameworks to allow the analysis of any number of predictor variables or groups of predictor variables as in the case of variation partitioning; and (c) introduce and demonstrate the implementation of these generalized frameworks in the R package rdacca.hp.

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Assessing Biological Orders of river sites and biological structures of watercourses using ecological traits of aquatic insects

Cited by 7 publications

References 21 publications

Dissimilarity analysis based on diffusion maps

Dissimilarity analysis based on diffusion maps

Description of the larval stage of Drusus mixtus (Pictet, 1834) (Trichoptera: Limnephilidae: Drusinae) with notes on its ecology and zoogeography

Generalizing hierarchical and variation partitioning in multiple regression and canonical analyses using the rdacca.hp R package

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