Synergistic and antagonistic interactions of future land use and climate change on river fish assemblages

Abstract

River ecosystems are threatened by future changes in land use and climatic conditions. However, little is known of the influence of interactions of these two dominant global drivers of change on ecosystems. Does the interaction amplify (synergistic interaction) or buffer (antagonistic interaction) the impacts and does their interaction effect differ in magnitude, direction and spatial extent compared to single independent pressures. In this study, we model the impact of single and interacting effects of land use and climate change on the spatial distribution of 33 fish species in the Elbe River. The varying effects were modeled using step-wise boosted regression trees based on 250 m raster grid cells. Species-specific models were built for both 'moderate' and 'extreme' future land use and climate change scenarios to assess synergistic, additive and antagonistic interaction effects on species losses, species gains and diversity indices and to quantify their spatial distribution within the Elbe River network. Our results revealed species richness is predicted to increase by 0.7-2.9 species by 2050 across the entire river network. Changes in species richness are likely to be spatially variable with significant changes predicted for 56-85% of the river network. Antagonistic interactions would dominate species losses and gains in up to 75% of the river network. In contrast, synergistic and additive effects would occur in only 20% and 16% of the river network, respectively. The magnitude of the interaction was negatively correlated with the magnitudes of the single independent effects of land use and climate change. Evidence is provided to show that future land use and climate change effects are highly interactive resulting in species range shifts that would be spatially variable in size and characteristic. These findings emphasize the importance of adaptive river management and the design of spatially connected conservation areas to compensate for these high species turnovers and range shifts.

The future distribution of river fish: The complex interplay of climate and land use changes, species dispersal and movement barriers

“…Second, the environmental variables might interact with each other and jointly buffer or amplify species responses. Third, although the applied future land use scenarios follow a gradient of human intervention (Baseline < BAMBU < GRAS), the changes in single land uses vary regionally and between the scenarios (see Figs S2–S5 in Radinger et al., ). For example, arable land is predicted to decrease in the northeastern areas and to increase in western areas of the catchment; Grassland in the River Elbe catchment is only predicted to decrease at the moderate scenario, but not at the extreme scenario.…”

“…The model river network was extracted from a digital elevation model (EU‐DEM in ETRS89‐LAEA coordinate reference system, EPSG code: 3035, http://www.eea.europa.eu/data-and-maps/data/eu-dem) at a spatial raster resolution of 250 m. For an improved representation of the river especially in topographically flat areas, the CCM2 river network (River and Catchment Database, version 2.1, http://ccm.jrc.ec.europa.eu, De Jager & Vogt, ) was burned into the DEM before extraction (cf. Radinger et al., ). The extracted river network comprised 24,284 grid cells corresponding to a total length of approx.…”

“…BRTs effectively select relevant variables, identify variable interactions and avoid overfitting (Elith et al., ). We used a four‐step analytical framework in the statistical software r based on the general guidelines on BRTs recommended by Elith and Leathwick () and already described in detail in a previous study (Radinger et al., ): First, we randomly split the occurrence (presence/absence) data for each species into a dataset for model fitting (80% of the sites) and a dataset for model validation (20% of the sites). Second, we built for each species an initial BRT global model ( r package dismo , gbm.step ) using the selected occurrence data for model fitting (Bernoulli distribution) and all 36 predictor variables (19 bioclimatic variables, 12 land use variables, 5 stream topological variables, Table S1).…”

“…In particular, riverine ecosystems, which are among the most diverse systems on our globe, are considered especially threatened by future global environmental changes (Palmer et al., ; Vörösmarty et al., ). Climate and land use change are expected to alter rivers by modifications to their flow, temperature, sediment regimes and water quality (e.g., Allan, Erickson, & Fay, ; Meyer, Sale, Muiholland, & Poff, ) with ultimate consequences for the distribution of river fishes (Comte, Buisson, Daufresne, & Grenouillet, ; Markovic et al., ; Radinger et al., ). Moreover, it has become clear that the interaction of climate and land use changes (cf.…”

“…While the impacts of climate and land use changes on the distribution of river fishes are increasingly studied (Comte & Grenouillet, ; Comte et al., ; Radinger et al., ), the interaction with species‐specific dispersal abilities and movement barriers have not yet been evaluated. Therefore, we coupled distribution models of 17 fish species with spatially explicit models of their dispersal in a large European river network while explicitly considering movement barriers.…”