“Into and Out of” the Qinghai‐Tibet Plateau and the Himalayas: Centers of origin and diversification across five clades of Eurasian montane and alpine passerine birds

Encompassing some of the major hotspots of biodiversity on Earth, large mountain systems have long held the attention of evolutionary biologists. The region of the Qinghai‐Tibet Plateau (QTP) is considered a biogeographic source for multiple colonization events into adjacent areas including the northern Palearctic. The faunal exchange between the QTP and adjacent regions could thus represent a one‐way street (“out of” the QTP). However, immigration into the QTP region has so far received only little attention, despite its potential to shape faunal and floral communities of the QTP. In this study, we investigated centers of origin and dispersal routes between the QTP, its forested margins and adjacent regions for five clades of alpine and montane birds of the passerine superfamily Passeroidea. We performed an ancestral area reconstruction using BioGeoBEARS and inferred a time‐calibrated backbone phylogeny for 279 taxa of Passeroidea. The oldest endemic species of the QTP was dated to the early Miocene (ca. 20 Ma). Several additional QTP endemics evolved in the mid to late Miocene (12–7 Ma). The inferred centers of origin and diversification for some of our target clades matched the “out of Tibet hypothesis’ or the “out of Himalayas hypothesis” for others they matched the “into Tibet hypothesis.” Three radiations included multiple independent Pleistocene colonization events to regions as distant as the Western Palearctic and the Nearctic. We conclude that faunal exchange between the QTP and adjacent regions was bidirectional through time, and the QTP region has thus harbored both centers of diversification and centers of immigration.     

BCL(X)L and BCL2 increase mitochondrial dynamics in breast cancer cell: Evidence from functional and genetic studies

BCL2 family proteins are important regulators of mitochondrial outer membrane permeabilization (MOMP). In recent years, BCL2 family proteins have also been linked to the regulation of mitochondrial bioenergetics and dynamics. Given their overexpression in breast cancer cells, we sought to explore whether two key members of this family, BCL2 and BCL(X)L impacted on mitochondrial fusion/fission processes. By employing a single cell imaging and RNA sequencing we found that overexpression of BCL2 or BCL(X)L increases mitochondrial dynamics and alters the expression profile of genes involved in this process. Collectively, our data show that overexpression of BCL2 proteins regulates mitochondrial dynamics in breast cancer tumor cells.     

Local and landscape responses of biodiversity in calcareous grasslands

Biodiversity and Conservation - Across Europe, calcareous grasslands become increasingly fragmented and their quality deteriorates through abandonment and land use intensification, both affecting...     

Self-tuning serverless task farming using proactive elasticity control

Cluster Computing - The cloud evolved into an attractive execution environment for parallel applications, which make use of compute resources to speed up the computation of large problems in...     

Projected climate impacts to South African maize and wheat production in 2055: a comparison of empirical and mechanistic modeling approaches

Crop model‐specific biases are a key uncertainty affecting our understanding of climate change impacts to agriculture. There is increasing research focus on intermodel variation, but comparisons between mechanistic (MMs) and empirical models (EMs) are rare despite both being used widely in this field. We combined MMs and EMs to project future (2055) changes in the potential distribution (suitability) and productivity of maize and spring wheat in South Africa under 18 downscaled climate scenarios (9 models run under 2 emissions scenarios). EMs projected larger yield losses or smaller gains than MMs. The EMs’ median‐projected maize and wheat yield changes were ?3.6% and 6.2%, respectively, compared to 6.5% and 15.2% for the MM. The EM projected a 10% reduction in the potential maize growing area, where the MM projected a 9% gain. Both models showed increases in the potential spring wheat production region (EM = 48%, MM = 20%), but these results were more equivocal because both models (particularly the EM) substantially overestimated the extent of current suitability. The substantial water‐use efficiency gains simulated by the MMs under elevated CO₂ accounted for much of the EM?MM difference, but EMs may have more accurately represented crop temperature sensitivities. Our results align with earlier studies showing that EMs may show larger climate change losses than MMs. Crop forecasting efforts should expand to include EM?MM comparisons to provide a fuller picture of crop–climate response uncertainties.