Integrating catchment properties in small scale species distribution models of stream macroinvertebrates

Kuemmerlen, Mathias; Schmalz, Britta; Guse, Björn; Cai, Qinghua; Fohrer, Nicola; Jähnig, Sonja C.

doi:10.1016/j.ecolmodel.2014.01.020

Cited by 75 publications

(82 citation statements)

References 60 publications

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“…However, one of the main limitations of studies on ecological newtorks is that the movement data of target speices are frequently unavailable. Therefore, there have been an increasing number of simulation-based studies on migration and biodiversity conservation in an attempt to address such defects171819202122. In particular, methods based on graph theory emphasize the functional connection between habitat patches, which is the effective relationship between components of an ecological object or process with corresponding characteristic scales16.…”

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confidence: 99%

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

Gao

Liu

et al. 2017

Sci Rep

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Fragmentation and reduced continuity of habitat patches threaten the environment and biodiversity. Recently, ecological networks are increasingly attracting the attention of researchers as they provide fundamental frameworks for environmental protection. This study suggests a set of procedures to construct an ecological network. First, we proposed a method to construct a landscape resistance surface based on the assessment of habitat quality. Second, to analyze the effect of the resistance surface on corridor simulations, we used three methods to construct resistance surfaces: (1) the method proposed in this paper, (2) the entropy coefficient method, and (3) the expert scoring method. Then, we integrated habitat patches and resistance surfaces to identify potential corridors using graph theory. These procedures were tested in Changzhou, China. Comparing the outputs of using different resistance surfaces demonstrated that: (1) different landscape resistance surfaces contribute to how corridors are identified, but only slightly affect the assessment of the importance of habitat patches and potential corridors; (2) the resistance surface, which is constructed based on habitat quality, is more applicable to corridor simulations; and (3) the assessment of the importance of habitat patches is fundamental for ecological network optimization in the conservation of critical habitat patches and corridors.

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confidence: 99%

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

Gao

Liu

et al. 2017

Sci Rep

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“…These functions are commonly estimated using a scatter plot smoother (e.g., cubic spline) as the basic building block (Hastie et al, 2009;Zuur, Ieno, Walker, Saveliev, & Smith, 2009 Holguin-Gonzalez, Everaert, et al, 2013;Kuemmerlen et al, 2014). Sui, Iwasaki, Saavedra Valeriano, and Yoshimura (2014) developed a predictive model employing a geomorphology-based hydrological model to determine ten flow indices.…”

Section: Linear Statistical Methodsmentioning

confidence: 99%

“…• Low predictive power • Model structure (distributions selection) must be defined a priori Low Low Damanik-Ambarita et al, 2016;Death et al, 2015;Donohue et al, 2006;Everaert et al, 2014;Gieswein et al, 2017;Holguin-Gonzalez, Everaert, et al, 2013;Jerves-Cobo et al, 2017;Kuemmerlen et al, 2014;Moya et al, 2011;Pont et al, 2009;Sauer, Domisch, Nowak, & Haase, 2011;Van Sickle et al, 2004Fukuda et al, 2013Gieswein et al, 2017;Grenouillet et al, 2011;Hermoso, Linke, Prenda, & Possingham, 2011;Kwon, Bae, Hwang, Kim, & Park, 2015;Leclere et al, 2011;Patrick & Yuan, 2017;Sui et al, 2014 Generalized additive models • Suitable for modelling nonlinear relationships • Uses nonparametric basis functions • Prone t...…”

Section: Knowledge Gap Analysismentioning

confidence: 99%

A review of macroinvertebrate‐ and fish‐based stream health modelling techniques

Hernandez‐Suarez

Nejadhashemi

2018

Ecohydrology

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During the last three decades, explaining cause-effect relationships between natural and anthropogenic disturbances with measures of stream health have motivated the growing application of statistical, machine learning, and soft computing methods.The aim of this review is to provide insight into the most widely used methods for predicting biological variables based on macroinvertebrate and fish species in riverine ecosystems. Therefore, we describe several methods including multiple linear regression, generalized linear models, generalized additive models, boosted regression trees, random forests, artificial neural networks, fuzzy logic-based, and Bayesian belief networks along with recent applications of these. Moreover, issues regarding variable selection, model interpretability, ensemble modelling, and model evaluation and overfitting are discussed. Recent advances have suggested the need for integrated modelling systems to enhance the predictive ability and improve interpretability.However, trade-offs between model complexity and accuracy demand research efforts in uncertainty quantification/propagation in model ensembles. Additionally, models should be perceived as complementary tools that require further validation with field measurements. Therefore, a consensus regarding monitoring and modelling practices for stream health applications is recommended.

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“…Some predictors were processed to optimally describe the freshwater ecosystem, such as calculating the relative proportion of land‐use and geology classes in the upper sub‐catchment (Kuemmerlen et al . , ). We used the ‘ randomForest ’ package in R (R Core Team ) to fit the models, keeping the default settings, with the number of trees increased to 10 000.…”

Section: Methodsmentioning

confidence: 99%

Accounting for biotic interactions through alpha‐diversity constraints in stacked species distribution models

et al. 2017

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and tend to overpredict the number of species that can coexist at a given location and time 32(hereafter, the alpha-capacity). We developed an extension of SDMs that integrates species-33 level and community-level modelling to account for the above drivers. 34 2. The alpha-adjusted SDM takes the Probabilities of Occurrence (PoO) for all species of a 35 community -capacity and adjusts the PoO, such that: a. their sum will equal 36 the alpha-capacity as predicted by probability theory; and b. the adjusted PoO are dependent 37 upon the relative suitability of each species for that site. The new method was tested using 38 community data comprising 87 freshwater invertebrate species in an LTER watershed in 39Germany. We explored the ability of the method to predict alpha and beta-diversity patterns. 40We further focused on the effect on model performance at the species-level of the error 41 associated with modelling alpha-capacity, of differences in gamma diversity (the size of the 42 community) and of the type of community (random or guild-based). 433. The models that predicted alpha-capacity contained considerable error, and thus adjusting the 44 PoO according to the modelled alpha-capacity resulted with decreased performance at the 45 species level. However, when using the observed alpha-capacity to mimic a good alpha-capacity 46 model, the alpha-adjusted SDMs usually resulted in increased performance. We further found 47 that the alpha-adjusted SDM was better than the original SDM at predicting beta-diversity 48 patterns, especially when using similarity indices that are sensitive to double absences. 49 4. Using the alpha-adjusted SDM approach may increase the predictive performance at the species 50 and community levels if alpha-capacity can be assessed or modelled with sufficient accuracy, 51 especially in relatively small communities of closely interacting species. With better models to 52 predict alpha-capacity being developed, alpha-adjusted SDM has considerable potential to 53 provide more realistic predictions of species-distribution patterns. 54 3

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Integrating catchment properties in small scale species distribution models of stream macroinvertebrates

Cited by 75 publications

References 60 publications

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

Constructing Ecological Networks Based on Habitat Quality Assessment: A Case Study of Changzhou, China

A review of macroinvertebrate‐ and fish‐based stream health modelling techniques

Accounting for biotic interactions through alpha‐diversity constraints in stacked species distribution models

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