The sensitivity of ecosystem service models to choices of input data and spatial resolution

摘要: Abstract Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such drawn mixed conclusions about whether different choices yield divergent results. In this study, we compared results of models to address these questions at national, provincial, subwatershed scales Rwanda. We for carbon, water, sediment as modeled using InVEST WaSSI (1) land cover 30 300 m resolution (2) three input datasets. simpler (carbon storage annual water yield) were relatively insensitive choice spatial resolution, but complex (seasonal regulation) produced large differences when applied differing resolution. Six out nine ES metrics (InVEST seasonal WaSSI) gave similar predictions least two Despite mean values sources found significant highly correlated Spearman's rank correlation, indicating consistent patterns high low values. Our confirm extend past studies, showing that certain cases (e.g., national-scale analyses), can be robust choices. For models, those with output metrics, subnational site-based analyses heterogeneous environments, may strongly influence study findings.