Abstract
An estuary region is a complex environment with a transition from fresh to brackish to salt water, and in which some environmental factors change dramatically over small ranges. Therefore, it is important to understand the impact of the selection of spatial scale on the prediction of the distribution of estuarine species. As the largest estuary in China, the Changjiang River estuary is the spawning ground, feeding ground, and migration channel for many species. Based on Coilia nasus, an important economic fish species in the Changjiang River estuary, this study uses the two-stage generalized additive model (GAM) to investigate the potential differences in the response of species’ spatial distribution when environmental factors are assessed at different spatial scales (1′ × 1′, 2′ × 2′, 3′ × 3′, 4′ × 4′, 5′ × 5′). The results showed the following: (1) according to the analysis of the variance inflation factor (VIF), the values of all environmental factors were less than three and we found no correlation among the environmental variables selected. (2) The first stage GAM retained six variables, including year, month, latitude (Lat), water depth (Depth, m), bottom salinity (Sal, mg/L), and chemical oxygen demand (COD, mg/L). The second stage GAM retained four variables, including Year, Lat, pH, and chlorophyll a (Chl-a, μg/L). (3) The mean value of the Chla for the 3′ × 3′ spatial scale was significantly lower than that of the other spatial scales, and the mean value of Sal for the 5′ × 5′ spatial scale was higher than that of the other spatial scales. (4) In terms of the spatial distribution of abundance, the distribution patterns of C. nasus predicted by all scales were not very similar, and the distribution patterns predicted by the 5′ × 5′ scale, in the autumn of 2012, were significantly different from those at other scales. Therefore, the selection of spatiotemporal scales may affect predictions of the spatial distributions of species. We suggest that potential spatiotemporal scale effects should be evaluated in future studies.
Highlights
We compared the differences in the interpolation predictions of environmental factors at five different spatial scales, and used the interpolation results to predict the spatial distribution of the species to understand the impact of spatial scale selection on the prediction of the spatial and temporal distributions of migratory fish in the estuary
Based on the variance inflation factor (VIF) analysis, the VIF values of all explanatory variables were less than three, and no environmental factors needed to be deleted before the backward stepwise regression
Our results suggest that in the Changjiang River estuary region, for environmental factors that little in the estuary region, and with marginal difference between the highest and lowest values, the interpolation results on a small scale can well reflect the variation details of their spatial characteristics (Figure 3)
Summary
The selection of different spatial scales in the interpolation process may affect the prediction characteristics of some environmental factors [10], especially in waters such as estuaries, wherein the landscape is fragmented [11]. Changes in environmental characteristics can potentially affect the predicted distribution of organisms; it is very important to study the effects of environmental interpolation on the spatial and temporal distribution patterns of organisms at different spatial scales [12,13]. We compared the differences in the interpolation predictions of environmental factors at five different spatial scales, and used the interpolation results to predict the spatial distribution of the species to understand the impact of spatial scale selection on the prediction of the spatial and temporal distributions of migratory fish in the estuary
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