Correction to: Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia - P. Rai; K. Ziegler; D. Abel; F. Pollinger; H. Paeth (Theoretical and Applied Climatology, 2022)

Performance of a regional climate model with interactive vegetation (REMO-iMOVE) over Central Asia - P. Rai; K. Ziegler; D. Abel; F. Pollinger; H. Paeth (Theoretical and Applied Climatology, 2022)
The current study evaluates the regional climate model REMO (v2015) and its new version REMO-iMOVE, including interactive vegetation and plant functional types (PFTs), over two Central Asian domains for the period of 2000–2015 at two different horizontal resolutions (0.44° and 0.11°). Various statistical metrices along with mean bias patterns for precipitation, temperature, and leaf area index have been used for the model evaluation. A better representation of the spatial pattern of precipitation is found at 0.11° resolution over most of Central Asia. Regarding the mean temperature, both model versions show a high level of agreement with the validation data, especially at the higher resolution. This also reduces the biases in maximum and minimum temperature. Generally, REMO-iMOVE shows an improvement regarding the temperature bias but produces a larger precipitation bias compared to the REMO conventional version with interannually static vegetation. Since the coupled version is capable to simulate the mean climate of Central Asia like its parent version, both can be used for impact studies and future projections. However, regarding the new vegetation scheme and its spatiotemporal representation exemplified by the leaf area index, REMO-iMOVE shows a clear advantage over REMO. This better simulation is caused by the implementation of more realistic and interactive vegetation and related atmospheric processes which consequently add value to the regional climate model.

Uncertainties in the simulation of precipitation in selected regions of humid and dry climate - C. Ring; B. Mannig; F. Pollinger; H. Paeth (International Journal of Climatology, 2016)
Choices of adaption strategies to climate change are often based on the knowledge summarized in the Intergovernmental Panel on Climate Change ( IPCC ) Assessment Reports. For climate impact research, precipitation is of high relevance and often used as a criterion for climate model evaluation. Therefore, we assess simulated precipitation of 24 models of Phase 3 and 26 models of Phase 5 of the Coupled Model Intercomparison Project ( CMIP ) of the latest Assessment Reports of the IPCC , altogether 149 individual simulations. These model simulations and the two multi‐model means are evaluated against five observational datasets from different sources over the late 20th century. Monthly, seasonal and annual means are analysed based on five selected study areas, leading to a comparative regional assessment of model quality. For the more recent CMIP ensemble mean, the overall bias has been reduced. Aside from some underestimation in summer and overestimation in winter in wet regions, there is still a considerable model bias (40–150% compared to observational data) especially in the arid areas of our study. None of the single models is superior in all five regions, although for all regions models can be identified that show excellent results. Additionally, the relationship between horizontal and vertical model resolution and the model bias is evaluated. Despite some tendencies, the results show no significant dependency of model performance on the range of resolution in CMIP3 and CMIP5 . Thus, more sophisticated metrics have to be applied to construct subensembles which have higher skill and lower spread of simulated precipitation.

Microsatellite records for volume 8, issue 1 - Maria Cristina Arias; Stéphane Aulagnier; Erin F. Baerwald; Robert M. R. Barclay; Jacqueline Silva Batista; Rochelle R. Beasley; Rodrigo A. Bezerra; Frédéric Blanc; Eli S. Bridge; Maria Teresa Cabria; Lívia Izabela Caputo; Jie Chen; et al. (Conservation Genetics Resources, 2016)

Evolutionary consequences of human disturbance in a rainforest bird species from Central Africa - THOMAS B. SMITH; BORJA MILÁ; GREGORY F. GRETHER; HANS SLABBEKOORN; IREM SEPIL; WOLFGANG BUERMANN; SASSAN SAATCHI; JOHN P. POLLINGER (Molecular Ecology, 2008)
Relatively little attention has been directed towards understanding the impacts of human disturbance on evolutionary processes that produce and maintain biodiversity. Here, we examine the influence of anthropogenic habitat changes on traits typically associated with natural and sexual selection in the little greenbul ( Andropadus virens ), an African rainforest bird species. Using satellite remote‐sensing and field survey data, we classified habitats into nonhuman‐altered mature and human‐altered secondary forest. Mature rainforest consisted of pristine rainforest, with little or no human influence, and secondary forest was characterized by plantations of coffee and cacao and high human impacts. Andropadus viren s abundance was higher in secondary forest, and populations inhabiting mature rainforest were significantly larger in wing and tarsus length and bill size; characters often correlated with fitness. To assess the extent to which characters important in sexual section and mate choice might be influenced by habitat change, we also examined differences in plumage colour and song. Plumage colour and the variance in plumage luminance were found to differ between forest types, and song duration was found to be significantly longer in mature forest. The possible adaptive significance of these differences in traits is discussed. Despite relatively high levels of gene flow across habitats, amplified fragment length polymorphism analysis revealed that a small proportion of high‐ F ST loci differentiated mature from secondary forest populations. These loci were significant outliers against neutral expectations in a simulation analysis, suggesting a role for divergent selection in differentiation across habitats. A distance‐based redundancy analysis further showed that forest type as defined by remote‐sensing variables was significantly associated with genetic dissimilarities between habitats, even when controlling for distance. The observed shifts in morphology, plumage and song were consistent with divergent selection on heritable variation, but a role for plasticity cannot be ruled out. Results suggest that anthropogenic habitat changes may have evolutionary consequences, with implications for conservation and restoration.