Spatio-Temporal Heterogeneity of Climate Warming in the Chinese Tianshan Mountainous Region

The Chinese Tianshan mountainous region (CTMR) is a typical alpine region with high topographic heterogeneity, characterized by a large altitude span, complex topography, and diverse landscapes. A significant increase in air temperature had occurred in the CTMR during the last five decades. However, the detailed, comprehensive, and systematical characteristics of climate warming, such as its temporal and spatial heterogeneity, remain unclear. In this study, the temporal and spatial heterogeneity of climate warming across the CTMR had been comprehensively analyzed based on the 10-day air temperature data gathered during 1961–2020 from 26 meteorological stations. The results revealed local cooling in the context of general warming in the CTMR. The amplitude of variation (AV) varied from −0.57 to 3.64 °C, with the average value of 1.19 °C during the last six decades. The lapse rates of the elevation-dependent warming that existed annually, and in spring, summer, and autumn are −0.5 °C/100 m, −0.5 °C/100 m, −0.7 °C/100 m, and −0.4 °C/100 m, respectively. The warming in the CTMR is characteristic of high temporal heterogeneity, as represented by the amplified warming at 10-d scale for more than half a year, and the values of AV were higher than 1.09 °C of the global warming during 2011–2020 (GWV2011–2020). Meanwhile, the amplitudes of warming differed greatly on a seasonal scale, with the rates in spring, autumn, and winter higher than that in summer. The large spatial heterogeneity of climate warming also occurred across the CTMR. The warming pole existed in the warm part, the Turpan-Hami basin (below 1000 m asl) where the air temperature itself was high. That is, the warm places were warmer across the CTMR. The cooling pole was also found in the Kuqa region (about 1000 m asl). This study could greatly improve the understanding of the spatio-temporal dynamics, patterns, and regional heterogeneity of climate warming across the CTMR and even northwest China.

Effect of Deadwood Decomposition on the Restoration of Soil Cover in Landslide Areas of the Karpaty Mountains, Poland

Disturbances play an essential role in the shaping of temporal and spatial heterogeneity in natural community structures. The aim of this study was to provide an assessment of the deadwood influence on the chemical and biochemical properties of soils in a landslide area. The samples used to determine soil properties were collected from the entire landslide area, with locations distributed on a regular grid (50 × 50 m). The soil samples were collected from directly under the logs, and background soil samples were taken 1 m from the deadwood logs. The effect of the deadwood decomposition process was visible in the total organic carbon (C) and nitrogen (N) content and microbial activity of the soil. An increase in the enzyme activity and microbial biomass of the soil from directly beneath the deadwood was noted. In this study, it was found that a greater stock of deadwood was present in the accumulation zone, which resulted in a stronger effect of the released components on the soil cover. In order to restore landslide soils, microbial activity can be effectively stimulated by leaving deadwood on the landslide surface.

The Multifaceted Glioblastoma: From Genomic Alterations to Metabolic Adaptations

Glioblastoma multiforme (GBM) develops on glial cells and is the most common as well as the deadliest form of brain cancer. As in other cancers, distinct combinations of genetic alterations in GBM subtypes induce a diversity of metabolic phenotypes, which explains the variability of GBM sensitivity to current therapies targeting its reprogrammed metabolism. Therefore, it is becoming imperative for cancer researchers to account for the temporal and spatial heterogeneity within this cancer type before making generalized conclusions about a particular treatment’s efficacy. Standard therapies for GBM have shown little success as the disease is almost always lethal; however, researchers are making progress and learning how to combine therapeutic strategies most effectively. GBMs can be classified initially into two subsets consisting of primary and secondary GBMs, and this categorization stems from cancer development. GBM is the highest grade of gliomas, which includes glioma I (low proliferative potential), glioma II (low proliferative potential with some capacity for infiltration and recurrence), glioma III (evidence of malignancy), and glioma IV (GBM) (malignant with features of necrosis and microvascular proliferation). Secondary GBM develops from a low-grade glioma to an advanced-stage cancer, while primary GBM provides no signs of progression and is identified as an advanced-stage glioma from the onset. The differences in prognosis and histology correlated with each classification are generally negligible, but the demographics of individuals affected and the accompanying genetic/metabolic properties show distinct differentiation [3].

Trait-based ecological and eco-evolutionary theory

Trait-based approaches focus on the functional traits that define how organisms interact with the environment and each other. They represent an efficient way to capture different aspects of diversity in ecological models, which is essential for understanding community structure and ecosystem functioning, both now and in the future. There is an extensive history of trait-based approaches in theoretical ecology, enriched by an expanding array of complementary frameworks. In this chapter, we give a pedagogical introduction to one such framework—adaptive dynamics—explaining how to both set up and analyse models and surveying a range of applications. Then we show how adaptive dynamics relates to other frameworks, including species sorting, ecological quantitative genetics, and moment methods, highlighting the differences and connections between them. We then consider how these basic theories can be extended to incorporate temporal and spatial heterogeneity and multiple traits. Finally, we outline some frontiers of trait-based theory, including connections with empirical systems, linking trait- and species-based approaches, and embedding trait-based approaches in Earth system models.

The Responses of the Ecosystems in the Tianshan North Slope under Multiple Representative Concentration Pathway Scenarios in the Middle of the 21st Century

The arid ecosystem is fragile and sensitive to the changes in climate and CO2 concentration. Exploring the responses of the arid ecosystem to the changes under different representative concentration pathways (RCPs) is of particular significance for the sustainable development of the ecosystem. In this study, the dynamics of net primary productivity (NPP), evapotranspiration (ET), and water use efficiency (WUE) for arid ecosystems in Tianshan North Slope are explored by running the arid ecosystem model at 25 km resolution under RCP2.6, RCP4.5, and RCP8.5. The climate in Tianshan North Slope presents a wet-warming trend during 2006–2055 under each RCP scenario with temporal and spatial heterogeneity. In response to the changes in climate and CO2, the regional annual NPP and ET increased during 2006–2055 by a respectively maximum rate of 2.15 g C m−2 year−1 and 0.52 mm year−1 under RCP8.5. Both the NPP and ET share a similar temporal and spatial heterogeneity with climate change. Different vegetation types respond differently to the changes under different RCP scenarios with increasing WUE. Under each RCP, the non-phreatophyte, phreatophyte, and grass are more sensitive to the changes than in the others, and the broadleaf forest and cropland are less sensitive to the changes.