Abstract
Species distribution models (SDMs) are extensively used to project habitat suitability of species in stream ecological studies. Owing to complex sources of uncertainty, such models may yield projections with varying degrees of uncertainty. To better understand projected spatial distributions and the variability between habitat suitability projections, this study uses five SDMs that are based on the outputs of a two-dimensional hydraulic model to project the suitability of habitats and to evaluate the degree of variability originating from both differing model types and the split-sample procedure. The habitat suitability index (HSI) of each species is based on two stream flow variables, including current velocity (V), water depth (D), as well as the heterogeneity of these flow conditions as quantified by the information entropy of V and D. The six SDM approaches used to project fish abundance, as represented by HSI, included two stochastic models: the generalized linear model (GLM) and the generalized additive model (GAM); as well as three machine learning models: the support vector machine (SVM), random forest (RF) and the artificial neural network (ANN), and an ensemble model (where the latter is the average of the preceding five models). The target species Sicyopterus japonicas was found to prefer habitats with high current velocities. The relationship between mesohabitat diversity and fish abundance was indicated by the trends in information entropy and weighted usable area (WUA) over the study area. This study proposes a method for quantifying habitat suitability, and for assessing the uncertainties in HSI and WUA that are introduced by the various SDMs and samples. This study also demonstrated both the merits of the ensemble modeling approach and the necessity of addressing model uncertainty.
Highlights
Recognizing that the structure and functions of a stream ecosystem are significantly influenced by flow conditions, previous studies have provided valuable insights into the ecological modeling and assessment of stream habitats [1]
The flow rate was set to 0.5 m3/s, which was the average of a nearby flow meter. This model was calibrated and validated with the field measurements of flow conditions and its simulation performance are shown in terms of Coefficient of Determination (R2) and
In order to better understand the habitat preferences of S. japonicas within the Datuan tributary, six different species distribution models (SDMs) approaches were used to project habitat suitability in terms of current velocity (V) and water depth (D) as projected by a two-dimensional hydraulic model, River 2D
Summary
Recognizing that the structure and functions of a stream ecosystem are significantly influenced by flow conditions, previous studies have provided valuable insights into the ecological modeling and assessment of stream habitats [1]. Physical hydraulic models, such as the Physical Habitat Simulation system (PHABSIM) and the River 2D model [2], are useful tools for simulating changes in water depth and velocity at scales that are relevant to stream habitats [3,4,5]. These two variables are used in species distribution models (SDMs) to estimate HSI values for fish species
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