Abstract
Comparing and evaluating global climate datasets and their effect on model performance in regions with limited data availability has received little attention in ecological modeling studies so far. In this study, we aim at comparing the interpolated climate dataset Worldclim 1.4, which is the most widely used in ecological modeling studies, and the quasi-mechanistical downscaled climate dataset Chelsa, as well as their latest versions Worldclim 2.1 and Chelsa 1.2, with regard to their suitability for modeling studies. To evaluate the effect of these global climate datasets at the meso-scale, the ecological niche of Betula utilis in Nepal is modeled under current and future climate conditions. We underline differences regarding methodology and bias correction between Chelsa and Worldclim versions and highlight potential drawbacks for ecological models in remote high mountain regions. Regarding model performance and prediction plausibility under current climatic conditions, Chelsa-based models significantly outperformed Worldclim-based models, however, the latest version of Chelsa contains partially inherent distorted precipitation amounts. This study emphasizes that unmindful usage of climate data may have severe consequences for modeling treeline species in high-altitude regions as well as for future projections, if based on flawed current model predictions. The results illustrate the inevitable need for interdisciplinary investigations and collaboration between climate scientists and ecologists to enhance climate-based ecological model quality at meso- to local-scales by accounting for local-scale physical features at high temporal and spatial resolution.
Highlights
The Himalayas are the largest mountain system in the world with a distinct threedimensional geoecological differentiation, with a high variation of altitude, temperature, precipitation, soils, and land use [1,2,3]
C HELSA 1.1 from 2016 and W ORLDCLIM 1.4 from 2005 are replaced by updated versions and their authors recommend using the most recent datasets, they are still included in this comparison as they were and to date still are widely used in ecological studies
The modeled potential distribution of Betula utilis stretches along the Himalayan mountain range, we found significant differences in the explained variance between the models using the different climate datasets (Friedmann X2 = 9.96, p ≤ 0.05), but not among respective versions (Figure 5)
Summary
The Himalayas are the largest mountain system in the world with a distinct threedimensional geoecological differentiation, with a high variation of altitude, temperature, precipitation, soils, and land use [1,2,3]. Compared to other regions of the world, anthropogenic influence is less pronounced, but even in the Himalayas, near-natural treeline sites can hardly be found [7]. Inspired by easy-to-use software and freely accessible data, analyzing underlying factors of treeline position and dynamics as well as forecasting future changes of treeline species composition, altered species phenology, and future species ranges represents an ongoing trend in recently published literature (e.g., References [10,11,12,13,14]). In contrast to other mountains of the world, the Himalayan region is still under-researched in this respect and is clearly underrepresented in scientific literature on climate change-induced species range shifts [7,15,16,17]. In a recent review on modeling studies in the Himalayan mountains, Bobrowski et al [18] pointed out numerous challenges for modeling species’ niches and their distributions in the Himalayas
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