Characterising the spatiotemporal dynamics of drought and wet events in Australia

Advancing diurnal analysis of vegetation responses to drought events in the Yangtze River Basin using next-generation satellite data

Extreme climate events, particularly droughts, pose significant threats to vegetation, severely impacting ecosystem functionality and resilience. However, the limited temporal resolution of current satellite data hinders accurate monitoring of vegetation's diurnal responses to these events. To address this challenge, we leveraged the advanced satellite ECOSTRESS, combining its high-resolution evapotranspiration (ET) data with a LightGBM model to generate the hourly continuous ECOSTRESS-based ET (HC-ETECO) for the middle and lower reaches of the Yangtze River Basin (YRB) from 2015 to 2022. This dataset showed strong agreement with both ground-based and satellite observations. Utilizing the SPEI, we identified the significant drought period: September to November 2019 and August to September 2022. By integrating hourly Solar-Induced Chlorophyll Fluorescence (SIF) data, we observed that during drought period, the typical afternoon peak in SIF was absent. In contrast to non-drought period, morning photosynthesis and SIF-based Water Use Efficiency (WUESIF) anomalies were primarily driven by high Vapor Pressure Deficit (VPD), while the afternoon reductions were influenced by both high VPD and low Soil Moisture (SM) as the drought progressed. Our simulated HC-ETECO data revealed that ET in the middle and lower reaches of the YRB was consistently lower than normal during drought period. Attribution analysis indicated that this reduction was primarily driven by midday temperature increases and high VPD, suggesting that vegetation in the region copes with drought stress predominantly by limiting water loss. These findings highlight the utility of the generated high-resolution ET dataset in advancing our understanding of vegetation dynamics under drought climate conditions. This work provides critical insights for enhancing climate adaptation strategies and enhancing ecosystem management practices in the face of increasing climate variability.

Spatiotemporal variability identification and analysis for non-stationary climatic trends for a tropical river basin of India

The non-stationary behavior of climatic variables has been increasingly recognized as a challenge that disrupts the equilibrium of human-defined climate-based stationary processes, including hydrological and agricultural practices, and irrigation systems. This study aims to investigate long-term trends and non-stationarity in climatic variables across 23 stations of the Krishna River basin, India. Prominent trends in rainfall, temperature, and their extreme indices were identified using the Modified Mann-Kendall (MMK), Bootstrapped Mann-Kendall (BMK), and Sen's Slope Estimator tests, while the Innovative Trend Analysis (ITA) test uncovered hidden trends and potential shifts in climatic patterns. This study addresses a critical research gap by exploring both significant and hidden trends in climatic variables, providing a better understanding of future dynamics. Traditional methods like MMK and Sen's Slope were insufficient to reveal these hidden trends, but ITA offered a more comprehensive analysis. The findings revealed an increase in total annual rainfall for almost 50% of the basin, which aligns with rising maximum temperatures, suggesting enhanced evaporation rates and subsequent fluctuations in rainfall patterns. Seasonal analysis indicated a shift towards decreased rainfall during winter and pre-monsoon seasons, contrasted by increased precipitation during the monsoon and post-monsoon periods, highlighting a clear alteration in rainfall distribution. The Simple Daily Intensity Index (SDII) and other indices suggest intensified rainfall events despite a decrease in the number of rainy days, indicating fewer but more intense events. Temperature analysis showed an overall increase in maximum temperatures, with the Diurnal Temperature Range (DTR) significantly increasing across all stations, implying greater daily temperature variations and potential for intensified water cycles and extreme climatic events. Furthermore, the study simplifies these trends by classifying them into two attributes: intensity and frequency, aiding policymakers in site-specific management of water resources and planning for future climatic scenarios. The presence of non-stationarity in extreme rainfall was confirmed by the Augmented Dickey-Fuller (ADF), Phillips-Perron (PP), and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests. These findings are significant as they conclude how climate change is altering hydrological patterns at each station. The study emphasizes the necessity for adaptive management strategies to mitigate the adverse impacts on agriculture, infrastructure, and human safety.

Boom-bust population dynamics drive rapid genetic change

Increasing environmental threats and more extreme environmental perturbations place species at risk of population declines, with associated loss of genetic diversity and evolutionary potential. While theory shows that rapid population declines can cause loss of genetic diversity, populations in some environments, like Australia's arid zone, are repeatedly subject to major population fluctuations yet persist and appear able to maintain genetic diversity. Here, we use repeated population sampling over 13 y and genotype-by-sequencing of 1903 individuals to investigate the genetic consequences of repeated population fluctuations in two small mammals in the Australian arid zone. The sandy inland mouse (Pseudomys hermannsburgensis) experiences marked boom-bust population dynamics in response to the highly variable desert environment. We show that heterozygosity levels declined, and population differentiation (FST) increased, during bust periods when populations became small and isolated, but that heterozygosity was rapidly restored during episodic population booms. In contrast, the lesser hairy-footed dunnart (Sminthopsis youngsoni), a desert marsupial that maintains relatively stable population sizes, showed no linear declines in heterozygosity. These results reveal two contrasting ways in which genetic diversity is maintained in highly variable environments. In one species, diversity is conserved through the maintenance of stable population sizes across time. In the other species, diversity is conserved through rapid genetic mixing during population booms that restores heterozygosity lost during population busts.

Antimicrobial resistance trends among canine Escherichia coli isolated at a New York veterinary diagnostic laboratory between 2007 and 2020

Dogs are a potential source of drug-resistant Escherichia coli, but very few large-scale antimicrobial resistance surveillance studies have been conducted in the canine population. Here, we assess the antimicrobial susceptibility patterns, identify temporal resistance and minimum inhibitory concentration (MIC) trends, and describe associations between resistance phenotypes among canine clinical E. coli isolates in the northeastern United States. Through a retrospective study design, we collected MICs from 7709 E. coli isolates from canine infections at the Cornell University Animal Health Diagnostic Center between 2007 and 2020. The available clinical data were limited to body site. Isolates were classified as resistant or susceptible to six (urinary) and 22 (non-urinary) antimicrobials based on Clinical and Laboratory Standards Institute breakpoints. We used the Mann-Kendall test (MKT) and Sen's slope to identify the presence of a significant trend in the percent of resistant isolates over the study period. Multivariable logistic regression (MLR) models were built with ceftiofur, enrofloxacin, or trimethoprim-sulfamethoxazole resistance as the outcome and either body site and isolation date, or resistance to other antimicrobials as predictors. MIC trends were characterized with survival analysis models, controlling for body site and year of isolation. Overall, 16.4% of isolates were resistant to enrofloxacin, 14.3% to ceftiofur, and 14% to trimethoprim-sulfamethoxazole. The MKT and Sen's slope revealed a significant decreasing temporal trend for gentamicin and trimethoprim-sulfamethoxazole resistance among non-urinary isolates. No significant temporal resistance trends were detected by MKT for other antimicrobials. However, controlling for body-site in MLR models identified a decrease in resistance rates to enrofloxacin and trimethoprim-sulfamethoxazole after 2010. Similarly, survival analysis data confirmed these findings and showed a decrease in MIC values after 2010 for gentamicin and trimethoprim-sulfamethoxazole, but an increase in cephalosporin MICs. MLR showed that non-urinary isolates were significantly more likely than urinary isolates to demonstrate in vitro resistance to ceftiofur, enrofloxacin, and trimethoprim-sulfamethoxazole after controlling for year of isolation. We identified a higher level of ceftiofur resistance among enrofloxacin resistant isolates from urinary and non-urinary origins. Our findings confirmed that dogs are still a non-negligeable reservoir of drug-resistant E. coli in the northeastern United States. The increase in extended-spectrum cephalosporin MIC values in 2018-2020 compared to 2007-2010 constitutes a particularly worrying issue; the relationship between ceftiofur and enrofloxacin resistance suggests that the use of fluoroquinolones could contribute to this trend. Trimethoprim-sulfamethoxazole may be a good first-line choice for empiric treatment of E. coli infections; it is already recommended for canine urinary tract infections.