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51.
Invertebrate communities of the tropical rain forest floor are highly diverse, characterized by patchy species distribution patterns and high variation in species density. Spatial variation in the foraging activity of swarm raiding army ants, prime invertebrate predators in tropical rain forests, is discussed as a mechanism contributing to these patterns, but highly resolved long‐term data on army ant raiding on the local and landscape scale are hitherto lacking. In this study, 196 positions in 11 study sites in a tropical rain forest in western Kenya were continuously monitored over ~4 mo for the occurrence of swarm raids of army ants. Using population simulation analyses, the consequences of army ant raiding for prey communities were assessed. We found an unexpectedly high variation in raid rates at the study site and landscape scale. The weekly chance of communities to become raided by army ants was on average 0.11, but ranged from 0 to 0.50 among the 196 positions. Simulating population developments of two Lotka–Volterra species—showing slight trade‐offs between competitive strength and resistance to army ant raids—in the real raiding landscapes showed that the observed spatial variation in raid rates may produce high prey diversity at larger spatial scales (due to high β‐diversity) and strong variation in species density. Our results indicate that high spatial variation in army ant swarm raiding is a mechanism capable of generating patchy species distribution patterns and maintaining the high biodiversity of invertebrate communities of the tropical rain forest floor.  相似文献   
52.
《Global Change Biology》2018,24(6):2416-2433
Sustained observations of marine biodiversity and ecosystems focused on specific conservation and management problems are needed around the world to effectively mitigate or manage changes resulting from anthropogenic pressures. These observations, while complex and expensive, are required by the international scientific, governance and policy communities to provide baselines against which the effects of human pressures and climate change may be measured and reported, and resources allocated to implement solutions. To identify biological and ecological essential ocean variables (EOVs) for implementation within a global ocean observing system that is relevant for science, informs society, and technologically feasible, we used a driver‐pressure‐state‐impact‐response (DPSIR) model. We (1) examined relevant international agreements to identify societal drivers and pressures on marine resources and ecosystems, (2) evaluated the temporal and spatial scales of variables measured by 100+ observing programs, and (3) analysed the impact and scalability of these variables and how they contribute to address societal and scientific issues. EOVs were related to the status of ecosystem components (phytoplankton and zooplankton biomass and diversity, and abundance and distribution of fish, marine turtles, birds and mammals), and to the extent and health of ecosystems (cover and composition of hard coral, seagrass, mangrove and macroalgal canopy). Benthic invertebrate abundance and distribution and microbe diversity and biomass were identified as emerging EOVs to be developed based on emerging requirements and new technologies. The temporal scale at which any shifts in biological systems will be detected will vary across the EOVs, the properties being monitored and the length of the existing time‐series. Global implementation to deliver useful products will require collaboration of the scientific and policy sectors and a significant commitment to improve human and infrastructure capacity across the globe, including the development of new, more automated observing technologies, and encouraging the application of international standards and best practices.  相似文献   
53.
No-till (NT) is a sustainable option because of its benefits in controlling erosion, saving labor, and mitigating climate change. However, a comprehensive assessment of soil pH response to NT is still lacking. Thus, a global meta-analysis was conducted to determine the effects of NT on soil pH and to identify the influential factors and possible consequences based on the analysis of 114 publications. When comparing tillage practices, the results indicated an overall significant decrease by 1.33 ± 0.28% in soil pH under NT than that under conventional tillage (p < .05). Soil texture, NT duration, mean annual temperature (MAT), and initial soil pH are the critical factors affecting soil pH under NT. Specifically, with significant variations among subgroups, when compared to conventional tillage, the soil under NT had lower relative changes in soil pH observed on clay loam soil (?2.44%), long-term implementation (?2.11% for more than 15 years), medium MAT (?1.87% in the range of 8–16℃), neutral soil pH (?2.28% for 6.5 < initial soil pH < 7.5), mean annual precipitation (?1.95% in the range of 600–1200 mm), in topsoil layers (?2.03% for 0–20 cm), with crop rotation (?1.98%), N fertilizer input (the same for NT and conventional tillage) of 100–200 kg N ha?1 (?1.83%), or crop residue retention (?1.52%). Changes in organic matter decomposition under undisturbed soil and with crop residue retention might lead to a higher concentration of H+ and lower of basic cations (i.e., calcium, magnesium, and potassium), which decrease the soil pH, and consequently, impact nutrient dynamics (i.e., soil phosphorus) in the surface layer under NT. Furthermore, soil acidification may be aggravated by NT within site-specific conditions and improper fertilizer and crop residue management and consequently leading to adverse effects on soil nutrient availability. Thus, there is a need to identify strategies to ameliorate soil acidification under NT to minimize the adverse consequences.  相似文献   
54.
Phytoplankton growth is controlled by multiple environmental drivers, which are all modified by climate change. While numerous experimental studies identify interactive effects between drivers, large-scale ocean biogeochemistry models mostly account for growth responses to each driver separately and leave the results of these experimental multiple-driver studies largely unused. Here, we amend phytoplankton growth functions in a biogeochemical model by dual-driver interactions (CO2 and temperature, CO2 and light), based on data of a published meta-analysis on multiple-driver laboratory experiments. The effect of this parametrization on phytoplankton biomass and community composition is tested using present-day and future high-emission (SSP5-8.5) climate forcing. While the projected decrease in future total global phytoplankton biomass in simulations with driver interactions is similar to that in control simulations without driver interactions (5%–6%), interactive driver effects are group-specific. Globally, diatom biomass decreases more with interactive effects compared with the control simulation (−8.1% with interactions vs. no change without interactions). Small-phytoplankton biomass, by contrast, decreases less with on-going climate change when the model accounts for driver interactions (−5.0% vs. −9.0%). The response of global coccolithophore biomass to future climate conditions is even reversed when interactions are considered (+33.2% instead of −10.8%). Regionally, the largest difference in the future phytoplankton community composition between the simulations with and without driver interactions is detected in the Southern Ocean, where diatom biomass decreases (−7.5%) instead of increases (+14.5%), raising the share of small phytoplankton and coccolithophores of total phytoplankton biomass. Hence, interactive effects impact the phytoplankton community structure and related biogeochemical fluxes in a future ocean. Our approach is a first step to integrate the mechanistic understanding of interacting driver effects on phytoplankton growth gained by numerous laboratory experiments into a global ocean biogeochemistry model, aiming toward more realistic future projections of phytoplankton biomass and community composition.  相似文献   
55.
Introduction: Defects in tissue repair or wound healing pose a clinical, economic and social problem worldwide. Despite decades of studies, there have been few effective therapeutic treatments.

Areas covered: We discuss the possible reasons for why growth factor therapy did not succeed. We point out the lack of human disorder-relevant animal models as another blockade for therapeutic development. We summarize the recent discovery of secreted heat shock protein-90 (Hsp90) as a novel wound healing agent.

Expert commentary: Wound healing is a highly complex and multistep process that requires participations of many cell types, extracellular matrices and soluble molecules to work together in a spatial and temporal fashion within the wound microenvironment. The time that wounds remain open directly correlates with the clinical mortality associated with wounds. This time urgency makes the healing process impossible to regenerate back to the unwounded stage, rather forces it to take many shortcuts in order to protect life. Therefore, for therapeutic purpose, it is crucial to identify so-called ‘driver genes’ for the life-saving phase of wound closure. Keratinocyte-secreted Hsp90α was discovered in 2007 and has shown the promise by overcoming several key hurdles that have blocked the effectiveness of growth factors during wound healing.  相似文献   

56.
Next-generation sequencing has allowed identification of millions of somatic mutations in human cancer cells.A key challenge in interpreting cancer genomes is to distinguish drivers of cancer development among available genetic mutations.To address this issue,we present the first webbased application,consensus cancer driver gene caller(C~3),to identify the consensus driver genes using six different complementary strategies,i.e.,frequency-based,machine learning-based,functional bias-based,clustering-based,statistics model-based,and network-based strategies.This application allows users to specify customized operations when calling driver genes,and provides solid statistical evaluations and interpretable visualizations on the integration results.C~3 is implemented in Python and is freely available for public use at http://drivergene.rwebox.com/c~3.  相似文献   
57.
《Cell Stem Cell》2020,26(3):403-419.e4
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58.
《Cell》2023,186(2):287-304.e26
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59.
60.
《Cell》2023,186(18):3921-3944.e25
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