Water striders are impervious to raindrop collision forces and submerged by collapsing craters.

Water striders are abundant in areas with high humidity and rainfall. Raindrops can weigh more than 40 times the adult water strider and some pelagic species spend their entire lives at sea, never contacting ground. Until now, researchers have not systematically investigated the survival of water striders when impacted by raindrops. In this experimental study, we use high-speed videography to film drop impacts on water striders. Drops force the insects subsurface upon direct contact. As the ensuing crater rebounds upward, the water strider is propelled airborne by a Worthington jet, herein called the first jet. We show the water strider's locomotive responses, low density, resistance to wetting when briefly submerged, and ability to regain a super-surface rest state, rendering it impervious to the initial impact. When pulled subsurface during a second crater formation caused by the collapsing first jet, water striders face the possibility of ejection above the surface or submersion below the surface, a fate determined by their position in the second crater. We identify a critical crater collapse acceleration threshold ∼ 5.7 gravities for the collapsing second crater which determines the ejection and submersion of passive water striders. Entrapment by submersion makes the water strider poised to penetrate the air-water interface from below, which appears impossible without the aid of a plastron and proper locomotive techniques. Our study is likely the first to consider second crater dynamics and our results translate to the submersion dynamics of other passively floating particles such as millimetric microplastics atop the world's oceans.

Eccentricity-paced geomagnetic field and monsoon rainfall variations over the last 870 kyr.

Whether there are links between geomagnetic field and Earth's orbital parameters remains unclear. Synchronous reconstructions of parallel long-term quantitative geomagnetic field and climate change records are rare. Here, we present 10Be-derived changes of both geomagnetic field and Asian monsoon (AM) rainfall over the last 870 kyr from the Xifeng loess-paleosol sequence on the central Chinese Loess Plateau. The 10BeGM flux (a proxy for geomagnetic field-induced 10Be production rate) reveals 13 consecutive geomagnetic excursions in the Brunhes chron, which are synchronized with the global records, providing key time markers for Chinese loess-paleosol sequences. The 10Be-derived rainfall exhibits distinct ~100 kyr glacial-interglacial cycles, and superimposed precessional (~23 kyr) cycles that match with those in Chinese speleothem δ18O record. We find that changes in the geomagnetic field and AM rainfall share a common ~100 kyr cyclicity, implying a likely eccentricity modulation of both the geomagnetic field and climate.

A weakened AMOC may prolong greenhouse gas-induced Mediterranean drying even with significant and rapid climate change mitigation.

The Mediterranean region has been identified as a climate hot spot, with models projecting a robust warming and rainfall decline in response to increasing greenhouse gases. The projected rainfall decline would have impacts on agriculture and water resources. Can such changes be reversed with significant reductions in greenhouse gases? To explore this, we examine large ensembles of a high-resolution climate model with various future radiative forcing scenarios, including a scenario with substantial reductions in greenhouse gas concentrations beginning in the mid-21st century. In response to greenhouse gas reductions, the Mediterranean summer rainfall decline is reversed, but the winter rainfall decline continues. This continued winter rainfall decline results from a persistent atmospheric anticyclone over the western Mediterranean. Using additional numerical experiments, we show that the anticyclone and continued winter rainfall decline are attributable to greenhouse gas-induced weakening of the Atlantic Meridional Overturning Circulation (AMOC) that continues throughout the 21st century. The persistently weak AMOC, in concert with greenhouse gas reductions, leads to rapid cooling and sea ice growth in the subpolar North Atlantic. This cooling leads to a strong cyclonic atmospheric circulation anomaly over the North Atlantic subpolar gyre and, via atmospheric teleconnections, to the anticyclonic circulation anomaly over the Mediterranean. The failure to reverse the winter rainfall decline, despite substantial climate change mitigation, is an example of a "surprise" in the climate system. In this case, a persistent AMOC change unexpectedly impedes the reversibility of Mediterranean climate change. Such surprises could complicate pathways toward full climate recovery.

"Late-stage" deforestation enhances storm trends in coastal West Africa.

Deforestation affects local and regional hydroclimate through changes in heating and moistening of the atmosphere. In the tropics, deforestation leads to warming, but its impact on rainfall is more complex, as it depends on spatial scale and synoptic forcing. Most studies have focused on Amazonia, highlighting that forest edges locally enhance convective rainfall, whereas rainfall decreases over drier, more extensive, deforested regions. Here, we examine Southern West Africa (SWA), an example of "late-stage" deforestation, ongoing since 1900 within a 300-km coastal belt. From three decades of satellite data, we demonstrate that the upward trend in convective activity is strongly modulated by deforestation patterns. The frequency of afternoon storms is enhanced over and downstream of deforested patches on length scales from 16 to 196 km, with greater increases for larger patches. The results are consistent with the triggering of storms by mesoscale circulations due to landscape heterogeneity. Near the coast, where sea breeze convection dominates the diurnal cycle, storm frequency has doubled in deforested areas, attributable to enhanced land-sea thermal contrast. These areas include fast-growing cities such as Freetown and Monrovia, where enhanced storm frequency coincides with high vulnerability to flash flooding. The proximity of the ocean likely explains why ongoing deforestation across SWA continues to increase storminess, as it favors the impact of mesoscale dynamics over moisture availability. The coastal location of deforestation in SWA is typical of many tropical deforestation hotspots, and the processes highlighted here are likely to be of wider global relevance.

Long-term rain exclusion in a Mediterranean forest: response of physiological and physico-chemical traits of Quercus pubescens across seasons.

With climate change, an aggravation in summer drought is expected in the Mediterranean region. To assess the impact of such a future scenario, we compared the response of Quercus pubescens, a drought-resistant deciduous oak species, to long-term amplified drought (AD) (partial rain exclusion in natura for 10 years) and natural drought (ND). We studied leaf physiological and physico-chemical trait responses to ND and AD over the seasonal cycle, with a focus on chemical traits including major groups of central (photosynthetic pigments and plastoquinones) and specialized (tocochromanols, phenolic compounds, and cuticular waxes) metabolites. Seasonality was the main driver of all leaf traits, including cuticular triterpenoids, which were highly concentrated in summer, suggesting their importance to cope with drought and thermal stress periods. Under AD, trees not only reduced CO2 assimilation (-42%) in summer and leaf concentrations of some phenolic compounds and photosynthetic pigments (carotenoids from the xanthophyll cycle) but also enhanced the levels of other photosynthetic pigments (chlorophylls, lutein, and neoxanthin) and plastochromanol-8, an antioxidant located in chloroplasts. Overall, the metabolomic adjustments across seasons and drought conditions reinforce the idea that Q. pubescens is highly resistant to drought although significant losses of antioxidant defenses and photoprotection were identified under AD.

The influence of climate change on the sesame yield in North Gondar, North Ethiopia: Application Autoregressive Distributed Lag (ARDL) time series model.

Sesame is a major annual oil crop that is grown practically everywhere in tropical and subtropical Asia, as well as Africa, for its very nutritious and tasty seeds. Rising temperatures, droughts, floods, desertification, and weather all have a significant impact on agricultural production, particularly in developing countries like Ethiopia. Therefore, the main objective of this study is to examine the influence of climate change on the sesame yield in North Gondar, North Ethiopia, by using the autoregressive distributed Lag (ARDL) time series model. This study employed climate data from the Bahirdar Agrometeorological Center and secondary data on sesame production from the Ethiopian Statistical Service, spanning 36 years, from 1987 to 2023. Autoregressive Distributed LAG (ARDL) includes diagnostic tests for both short- and long-term autoregressive models. The results for the long-run and short-run elastic coefficients show a significant positive association between temperatures and sesame yield. Sesame yield and rainfall have a significant negative long-run and short-run relationship in North Gondar, North Ethiopia. ARDL results confirm that temperature and rainfall have significant effects on sesame productivity. Temperature had a considerable favorable effect on sesamen production, but rainfall had a negative effect in North Gondar, Ethiopia. Based on the evidence acquired from our study, we made several policy recommendations and suggestions to government officials, policymakers, new technologies, researchers, policy development planners, and other stakeholders in order to develop or implement new technology to halt its production and direct adaptation measures in light of the certainty of global warming and the characteristics of climate-dependent agricultural production.

Will trees or grasses profit from changing rainfall regimes in savannas?

Increasing rainfall variability is widely expected under future climate change scenarios. How will savanna trees and grasses be affected by growing season dry spells and altered seasonality and how tightly coupled are tree-grass phenologies with rainfall? We measured tree and grass responses to growing season dry spells and dry season rainfall. We also tested whether the phenologies of 17 deciduous woody species and the Soil Adjusted Vegetation Index of grasses were related to rainfall between 2019 and 2023. Tree and grass growth was significantly reduced during growing season dry spells. Tree growth was strongly related to growing season soil water potentials and limited to the wet season. Grasses can rapidly recover after growing season dry spells and grass evapotranspiration was significantly related to soil water potentials in both the wet and dry seasons. Tree leaf flushing commenced before the rainfall onset date with little subsequent leaf flushing. Grasses grew when moisture became available regardless of season. Our findings suggest that increased dry spell length and frequency in the growing season may slow down tree growth in some savannas, which together with longer growing seasons may allow grasses an advantage over C3 plants that are advantaged by rising CO2 levels.

Genetics of phenological development and implications for seed yield in lentil.

Understanding phenology, its genetics and agronomic consequences, is critical for crop adaptation. Here we aim at (1) characterising lentil response to photoperiod with a focus on five loci: the lentil ELF3 ortholog Sn, two loci linked to clusters of lentil FT orthologs and two loci without candidates in chromosomes 2 and 5 (exp. 1: 36 lines, short and long day in phytotron); (2) establishing phenology-yield relationship (exp. 2: 25 lines, 11 field environments). A vintage perspective, where we quantify time trends in phenotype over three decades of breeding, links both experiments. Yield increased linearly from older to newer varieties at 29 kg ha-1 yr-1 or 1.5% yr-1, correlated negatively with flowering time in both winter- and summer-rainfall regimes, and decoupled from biomass in favourable environments. Time to flowering shortened from older to newer varieties at -0.56 % yr-1 in the field, and -0.42 % yr-1 (short day) and -0.99 % yr-1 (long day) in the phytotron. Early-flowering lines of diverse origin carried multiple early alleles for the five loci, indicating that at least some of these loci affect phenology additively. Current germplasm primarily features the early flowering haplotype for an FTb cluster region, hence the potential to increase phenological diversity with yield implications.

Effects of leaf silicon on drought performance of tropical tree seedlings.

Elevated leaf silicon (Si) concentrations improve drought resistance in cultivated plants, suggesting Si might also improve drought performance of wild species. Tropical tree species, for instance, take up substantial amounts of Si, and leaf Si varies markedly at local and regional scales, suggesting consequences for seedling drought resistance. Yet, whether elevated leaf Si improves seedling drought performance in tropical forests is unknown. To manipulate leaf Si concentrations, seedlings of seven tropical tree species were grown in Si-rich and -poor soil, before exposing them to drought in the forest understorey. Survival, growth and wilting were monitored. Elevated leaf Si did not improve drought survival and growth in any of the species. In one species, drought survival was reduced in seedlings previously grown in Si-rich soil, contrary to our expectation. Our results suggest that elevated leaf Si does not improve drought resistance of wild tropical tree species. Elevated leaf Si may even reduce drought performance, suggesting differences in soil conditions influencing leaf Si may contribute to soil-related variation of tropical seedling performance. Furthermore, our results are at odds with most studies on cultivated species and show that alleviative effects of Si in crops cannot be generalized to wild plants in natural systems.

Investigating the Associations between Drought, Poverty, High-Risk Sexual Behaviours, and HIV Incidence in Sub-Saharan Africa: A Cross-Sectional Study.

Climate change is increasing the likelihood of drought in sub-Saharan Africa, where HIV prevalence is high. Drought could increase HIV transmission through various mediating mechanisms; we investigated these associations. We used data on people aged 15-59 from Population-Based HIV Impact Assessment surveys from 2016 in Eswatini, Lesotho, Tanzania, Uganda, and Zambia. Survey data were geospatially linked to precipitation data for 2014-2016, with local droughts defined as cumulative rainfall between 2014 and 2016 being in < 15th percentile of all 2-year periods over 1981-2016. Using multivariable logistic regression, stratified by sex and rural/urban residence, we examined associations between (a) drought and poverty, (b) wealth quintiles and sexual behaviours (transactional, high-risk, and intergenerational sex), (c) sexual behaviours and recently acquiring HIV, and (d) drought and recent HIV. Among 102,081 people, 31.5% resided in areas affected by drought during 2014-2016. Experiencing drought was positively associated with poverty for women and men in rural, but not urban, areas. For each group, increasing wealth was negatively associated with transactional sex. For rural women, intergenerational sex was positively associated with wealth. Women reporting each sexual behaviour had higher odds of recent HIV, with strong associations seen for high-risk sex, and, for urban women, intergenerational sex, with weaker associations among men. Women in rural areas who had been exposed to drought had higher odds of having recently acquired HIV (2.10 [95%CI: 1.17-3.77]), but not women in urban areas, or men. Droughts could potentially increase HIV transmission through increasing poverty and then sexual risk behaviours, particularly among women in rural areas.

Exposure of protected areas in Central America to extreme weather events.

Central America and the Caribbean are regularly battered by megadroughts, heavy rainfall, heat waves, and tropical cyclones. Although 21st-century climate change is expected to increase the frequency, intensity, and duration of these extreme weather events (EWEs), their incidence in regional protected areas (PAs) remains poorly explored. We examined historical and projected EWEs across the region based on 32 metrics that describe distinct dimensions (i.e., intensity, duration, and frequency) of heat waves, cyclones, droughts, and rainfall and compared trends in PAs with trends in unprotected lands. From the early 21st century onward, exposure to EWEs increased across the region, and PAs were predicted to be more exposed to climate extremes than unprotected areas (as shown by autoregressive model coefficients at p < 0.05 significance level). This was particularly true for heat waves, which were projected to have a significantly higher average (tested by Wilcoxon tests at p < 0.01) intensity and duration, and tropical cyclones, which affected PAs more severely in carbon-intensive scenarios. PAs were also predicted to be significantly less exposed to droughts and heavy rainfall than unprotected areas (tested by Wilcoxon tests at p < 0.01). However, droughts that could threaten connectivity between PAs are increasingly common in this region. We estimated that approximately 65% of the study area will experience at least one drought episode that is more intense and longer lasting than previous droughts. Collectively, our results highlight that new conservation strategies adapted to threats associated with EWEs need to be tailored and implemented promptly. Unless urgent action is taken, significant damage may be inflicted on the unique biodiversity of the region.

Ciclones, olas de calor, sequías y lluvias intensas son eventos comunes en Centroamérica y el Caribe, cuya frecuencia, intensidad y duración se espera aumente durante el siglo XXI a causa del cambio climático. Sin embargo, en la actualidad, se desconoce cuál será la incidencia de estos eventos meteorológicos extremos (EME) dentro de las áreas protegidas. En este estudio examinamos la exposición histórica y futura a los extremos climáticos y comparamos el grado de exposición dentro y fuera de las áreas protegidas de toda la región por medio de 32 métricas que describen distintas dimensiones (intensidad, duración y frecuencia) de las olas de calor, los ciclones, las sequías y las precipitaciones. Los resultados indican que a medida que aumente el número de EME, las áreas protegidas estarán más expuestas a los extremos climáticos que las áreas no protegidas. Esto es especialmente cierto en el caso de las olas de calor, que, según las proyecciones, tendrán una intensidad y una duración medias significativamente mayores, y de los ciclones tropicales, que afectarán más gravemente a las zonas protegidas en los escenarios intensivos en carbono. Nuestros resultados también indican que las zonas protegidas estarán significativamente menos expuestas a sequías o lluvias torrenciales que las zonas no protegidas. Sin embargo, las sequías que podrían amenazar la conectividad entre áreas protegidas son cada vez más frecuentes en esta región. Se estima que aproximadamente el 65% del área de estudio experimentará al menos un episodio de sequía más intenso y duradero que las sequías anteriores. En conjunto, nuestros resultados ponen de relieve la necesidad de diseñar y aplicar con prontitud nuevas estrategias de conservación adaptadas a las amenazas asociadas a los EWE. A menos que se tomen medidas urgentes, la biodiversidad única de la región podría sufrir daños considerables.

Process-Informed Subsampling Improves Subseasonal Rainfall Forecasts in Central America.

Subseasonal rainfall forecast skill is critical to support preparedness for hydrometeorological extremes. We assess how a process-informed evaluation, which subsamples forecasting model members based on their ability to represent potential predictors of rainfall, can improve monthly rainfall forecasts within Central America in the following month, using Costa Rica and Guatemala as test cases. We generate a constrained ensemble mean by subsampling 130 members from five dynamic forecasting models in the C3S multimodel ensemble based on their representation of both (a) zonal wind direction and (b) Pacific and Atlantic sea surface temperatures (SSTs), at the time of initialization. Our results show in multiple months and locations increased mean squared error skill by 0.4 and improved detection rates of rainfall extremes. This method is transferrable to other regions driven by slowly-changing processes. Process-informed subsampling is successful because it identifies members that fail to represent the entire rainfall distribution when wind/SST error increases.

Avian responses to climate extremes: insights into abundance curves and species sensitivity using the UK Breeding Bird Survey.

Climate change remains one of the most urgent challenges for biodiversity conservation. Recent studies have highlighted that climate extremes (CLEXs) can lead to widespread and negative effects across all taxa and ecological levels, but most of these studies are based on short-term periods and small spatial scales and lack a multi-species approach. Here, using generalised additive models (GAMs) and the UK Breeding Bird Survey (BBS), we described response curves for the abundance of 100 resident bird species over large spatial and temporal scales and identified the species showing a greater sensitivity to CLEXs. We used five climatic indices computed at 1-km spatial resolution as proxies of CLEXs during the winter or breeding season and considered both 1- and 2-year lagged effects. The results demonstrated widespread and significant effects of CLEXs on bird abundances at both time lags and in both seasons. Winter frost days (FD0), summer days (SU25) during the breeding season and simple precipitation intensity index (SDII) during the breeding season mainly showed negative effects. Daily temperature range (DTR) in both winter and breeding season and dry days (DD) during the breeding season led to diversified responses across the species, with a prevalence of positive effects. A large proportion of species showed a high sensitivity to CLEXs, highlighting that these species may deserve attention in future studies aimed at biodiversity conservation. We demonstrated that CLEXs can represent a significant driver affecting population abundances over large spatial and temporal scales, emphasising the need for understanding mechanistic processes at the basis of the observed effects.

Inter-event and intra-event dynamics of microplastic emissions in an urban river during rainfall episodes.

Urban rivers represent the major conduits for land-sourced microplastics in the global oceans, yet the real-time dynamics of their emissions in rivers during rainfall (and runoff) events are poorly understood. Herein, we report the results of high-frequency sampling of microplastic particles (MPs) and fibers (MPFs) in the surface water of an urban river in Japan over the course of three rainfall events (i.e., light, moderate, and heavy rainfalls). The event mean concentrations (EMCs) of MPs amounted to 35,000 items/m3, 929,000 items/m3, and 331,000 items/m3; and the corresponding total loads were 0.5 kg, 19.8 kg, and 35.0 kg for light, moderate and heavy rainfalls, respectively. The inter-event total loads of MPs correlate well with the total rainfall, while the concentrations were linked with the number of antecedent dry days. The dynamic trends show that <2000 µm MPs displayed first flush effects during light to moderate rainfall events (>50% mass discharged with the initial 20-40% of flow). Small-sized MPs (10-40 µm) mobilized rapidly at lower rainfall intensities, whereas MPs over 2000 µm discharged immediately after the peak rainfall intensity. Moreover, <70 µm MPs depicted a surge following heavy rainfall events due to turbulent flow conditions reverting the deposited MPs into suspension. Overall, the three events increased the loads by 4-110 folds, and EMCs by 10-350 folds compared to the concentrations during dry weather while portraying a significant impact on 300-1000 µm MPs. The dynamics of MPs were correlated with those of suspended solids in river water, and the characteristics were comparable to the same of road dust sampled in Japan. Although the dynamic trends between MPs and MPFs in river water were comparable, MPFs were relatively less impacted by rain, likely due to the intervention of separate sewer systems in the study area.

Remote sensing-based drought hazard monitoring and assessment in a coastal plain: A principal component approach.

Accurate drought information is essential for preventing agricultural and societal losses. The indicators of how severe a drought is the deficiency in precipitation, soil moisture, and vegetation stress. The indicators were evaluated using the Precipitation Condition Index (PCI), Vegetation Condition Index (VCI), and Temperature Condition Index (TCI).The indices were combined using Principal Component Analysis to create the Synthetic Drought Index (SDI) for the evaluation of drought severity. The indices were estimated using multi-source remote sensing data from the Tropical Rainfall Measuring Mission (TRMM) and Operational Land Imager (OLI) of various years. Temporal analysis showed that the district is drought-prone and deficiency of 65% of precipitation in northeast monsoon of 2016 and below average non-monsoon rainfall in 2017, caused drought and affected 223.5 Km2 in 2017. Below average precipitation in northeast monsoon of 2018 and below average non-monsoon rainfall in 2019, caused drought and affected 423 Km2 in 2019. The northeast coastal regions of Ottapidaram, Thoothukudi, and Vilathikulam taluks of the district were more severely prone to drought. Failure of monsoon is the root cause of water deficit in water bodies. The semi-arid coastal climate accelerates the evaporation of water in water bodies and causes soil moisture deficit that leads to drought in the coastal district. A sequential evaluation of this index can be used to identify the onset of drought and mitigate the effect of drought.

Rainfall-induced changes in aquatic microbial communities and stability of dissolved organic matter: Insight from a Fen river analysis.

Microbial communities are pivotal in aquatic ecosystems, as they affect water quality, energy dynamics, nutrient cycling, and hydrological stability. This study explored the effects of rainfall on hydrological and photosynthetic parameters, microbial composition, and functional gene profiles in the Fen River. Our results demonstrated that rainfall-induced decreases in stream temperature, dissolved oxygen, pH, total phosphorus, chemical oxygen demand, and dissolved organic carbon concentrations. In contrast, rainfall increased total dissolved solids, salinity, and ammonia-nitrogen concentrations. A detailed microbial community structure analysis revealed that Cyanobacteria was the dominant microbial taxon in the Fen River, accounting for approximately 75% and 25% of the microalgal and bacterial communities, respectively. The abundance of Chlorophyta and Bacillariophyta increased by 47.66% and 29.92%, respectively, whereas the relative abundance of Bacteroidetes decreased by 37.55% under rainfall conditions. Stochastic processes predominantly affected the assembly of the bacterial community on rainy days. Functional gene analysis revealed variations in bacterial functions between sunny (Sun) and rainy (Rain) conditions, particularly in genes associated with the carbon cycle. The 3-oxoacyl-[acyl-carrier-protein] reductase gene was more abundant in the Fen River bacterial community. Particular genes involved in metabolism and environmental information processing, including the acetyl-CoA C-acetyltransferase (atoB), enoyl-CoA hydratase (paaF), and branched-chain amino acid transport system gene (livK), which are integral to environmental information processing, were more abundant in Sun than the Rain conditions. In contrast, the phosphate transport system gene, the galactose metabolic gene, and the pyruvate metabolic gene were more abundant in Rain. The excitation-emission matrix analysis with parallel factor analysis identified four fluorescence components (C1-C4) in the river, which were predominantly protein- (C1) and humic-like (C2-C4) substances. Rainfall affected organic matter production and transport, leading to changes in the degradation and stability of dissolved organic matter. Overall, this study offers insight into how rainfall affects aquatic ecosystems.

A Coupled Statistical and Deterministic Model for Forecasting Climate-Driven Dengue Incidence in Selangor, Malaysia.

The mosquito-borne dengue virus remains a major public health concern in Malaysia. Despite various control efforts and measures introduced by the Malaysian Government to combat dengue, the increasing trend of dengue cases persists and shows no sign of decreasing. Currently, early detection and vector control are the main methods employed to curb dengue outbreaks. In this study, a coupled model consisting of the statistical ARIMAX model and the deterministic SI-SIR model was developed and validated using the weekly reported dengue data from year 2014 to 2019 for Selangor, Malaysia. Previous studies have shown that climate variables, especially temperature, humidity, and precipitation, were able to influence dengue incidence and transmission dynamics through their effect on the vector. In this coupled model, climate is linked to dengue disease through mosquito biting rate, allowing real-time forecast of dengue cases using climate variables, namely temperature, rainfall and humidity. For the period chosen for model validation, the coupled model can forecast 1-2 weeks in advance with an average error of less than 6%, three weeks in advance with an average error of 7.06% and four weeks in advance with an average error of 8.01%. Further model simulation analysis suggests that the coupled model generally provides better forecast than the stand-alone ARIMAX model, especially at the onset of the outbreak. Moreover, the coupled model is more robust in the sense that it can be further adapted for investigating the effectiveness of various dengue mitigation measures subject to the changing climate.

Functional recovery of secondary tropical forests.

One-third of all Neotropical forests are secondary forests that regrow naturally after agricultural use through secondary succession. We need to understand better how and why succession varies across environmental gradients and broad geographic scales. Here, we analyze functional recovery using community data on seven plant characteristics (traits) of 1,016 forest plots from 30 chronosequence sites across the Neotropics. By analyzing communities in terms of their traits, we enhance understanding of the mechanisms of succession, assess ecosystem recovery, and use these insights to propose successful forest restoration strategies. Wet and dry forests diverged markedly for several traits that increase growth rate in wet forests but come at the expense of reduced drought tolerance, delay, or avoidance, which is important in seasonally dry forests. Dry and wet forests showed different successional pathways for several traits. In dry forests, species turnover is driven by drought tolerance traits that are important early in succession and in wet forests by shade tolerance traits that are important later in succession. In both forests, deciduous and compound-leaved trees decreased with forest age, probably because microclimatic conditions became less hot and dry. Our results suggest that climatic water availability drives functional recovery by influencing the start and trajectory of succession, resulting in a convergence of community trait values with forest age when vegetation cover builds up. Within plots, the range in functional trait values increased with age. Based on the observed successional trait changes, we indicate the consequences for carbon and nutrient cycling and propose an ecologically sound strategy to improve forest restoration success.

Variability of ecosystem carbon source from microbial respiration is controlled by rainfall dynamics.

Soil heterotrophic respiration (Rh) represents an important component of the terrestrial carbon cycle that affects whether ecosystems function as carbon sources or sinks. Due to the complex interactions between biological and physical factors controlling microbial growth, Rh is uncertain and difficult to predict, limiting our ability to anticipate future climate trajectories. Here we analyze the global FLUXNET 2015 database aided by a probabilistic model of microbial growth to examine the ecosystem-scale dynamics of Rh and identify primary predictors of its variability. We find that the temporal variability in Rh is consistently distributed according to a Gamma distribution, with shape and scale parameters controlled only by rainfall characteristics and vegetation productivity. This distribution originates from the propagation of fast hydrologic fluctuations on the slower biological dynamics of microbial growth and is independent of biome, soil type, and microbial physiology. This finding allows us to readily provide accurate estimates of the mean Rh and its variance, as confirmed by a comparison with an independent global dataset. Our results suggest that future changes in rainfall regime and net primary productivity will significantly alter the dynamics of Rh and the global carbon budget. In regions that are becoming wetter, Rh may increase faster than net primary productivity, thereby reducing the carbon storage capacity of terrestrial ecosystems.

Timing outweighs magnitude of rainfall in shaping population dynamics of a small mammal species in steppe grassland.

Climate change-induced shifts in species phenology differ widely across trophic levels, which may lead to consumer-resource mismatches with cascading population and ecosystem consequences. Here, we examined the effects of different rainfall patterns (i.e., timing and amount) on the phenological asynchrony of population of a generalist herbivore and their food sources in semiarid steppe grassland in Inner Mongolia. We conducted a 10-y (2010 to 2019) rainfall manipulation experiment in 12 0.48-ha field enclosures and found that moderate rainfall increases during the early rather than late growing season advanced the timing of peak reproduction and drove marked increases in population size through increasing the biomass of preferred plant species. By contrast, greatly increased rainfall produced no further increases in vole population growth due to the potential negative effect of the flooding of burrows. The increases in vole population size were more coupled with increased reproduction of overwintered voles and increased body mass of young-of-year than with better survival. Our results provide experimental evidence for the fitness consequences of phenological mismatches at the population level and highlight the importance of rainfall timing on the population dynamics of small herbivores in the steppe grassland environment.