Summer Wet Season Research Articles

Nitrate Loads From Land to Stream Are Balanced by In‐Stream Nitrate Uptake Across Seasons in a Dryland Stream Network

AbstractExploring nitrogen dynamics in stream networks is critical for understanding how these systems attenuate nutrient pollution while maintaining ecological productivity. We investigated Oak Creek, a dryland watershed in central Arizona, USA, to elucidate the relationship between terrestrial nitrate (NO3−) loading and stream NO3− uptake, highlighting the influence of land cover and hydrologic connectivity. We conducted four seasonal synoptic sampling campaigns along the 167‐km network combined with stream NO3− uptake experiments (in 370–710‐m reaches) and integrated the data in a mass‐balance model to scale in‐stream uptake and estimate NO3− loading from landscape to the stream network. Stream NO3− concentrations were low throughout the watershed (<5–236 μg N/L) and stream NO3− vertical uptake velocity was high (5.5–18.0 mm/min). During the summer dry (June), summer wet (September), and winter dry (November) seasons, the lower mainstem exhibited higher lateral NO3− loading (10–51 kg N km−2 d−1) than the headwaters and tributaries (<0.001–0.086 kg N km−2 d−1), likely owing to differences in irrigation infrastructure and near‐stream land cover. In contrast, during the winter wet season (February) lateral NO3− loads were higher in the intermittent headwaters and tributaries (0.008–0.479 kg N km−2 d−1), which had flowing surface water only in this season. Despite high lateral NO3− loading in some locations, in‐stream uptake removed >81% of NO3− before reaching the watershed outlet. Our findings highlight that high rates of in‐stream uptake maintain low nitrogen export at the network scale, even with high fluxes from the landscape and seasonal variation in hydrologic connectivity.

Southern African precipitation changes in a warmer world: insights from the PlioMIP2 mid-Pliocene Warm Period (∼3.3–3.0 Ma) ensemble

Near-modern geography and atmospheric carbon dioxide concentrations (∼400 ppmv) coupled with temperatures ∼3°C warmer than the pre-Industrial era are suggested to make the mid-Pliocene warm period (mPWP; 3.264–3.025 Ma) an important near-future climate change analogue. To date, however, few studies explore mPWP hydroclimatic characteristics for the full southern Africa area using proxy records and/or Pliocene Model Intercomparison Project (PlioMIP) climate projections. Hence, we analyse precipitation outputs from 17 PlioMIP phase 2 models to explore southern African mPWP precipitation changes compared to pre-Industrial outputs. Despite diverse inter-model changes, robust signals exist. Most models project annual precipitation declines, up to 0.5 mm/day in the ensemble median. Drying of a similar magnitude for the summer (October-March) and winter (April-September) half-year periods contribute to this change, with models more consistently projecting winter drying. Consequently, the summer and winter precipitation zones (SRZ and WRZ) are projected to shift poleward by ∼1°. For WRZ regions, relatively stable summer precipitation and reduced winter precipitation is projected to result in reduced seasonality. Over SRZ regions, early (late) summer precipitation declines (increases) projected for October–December (January–March) re-organise the summer wet-season to be more concentrated in late summer. Qualitatively good consistency with future projections highlights the mPWPs relevance considering southern Africa’s future climate changes, however, limited model-proxy agreement suggests a need to further (re)assess Pliocene (mPWP) proxy records and/or the PlioMIP2 model boundary conditions towards better capturing mechanisms driving mPWP climatic changes.

On the characterization of Cloud occurrence and its impact on solar radiation in Mbour, Senegal

The objective of this study is to evaluate the clouds seasonal occurrence characteristics, and to estimate their impact on solar radiation in Mbour, Senegal, West Africa. Here, we use datasets from various sources including: i) observations from the Clouds and Earth's Radiant Energy System satellite sensors, ii) in situ shortwave radiation measurement obtained from the Mbour station, and iii) the outgoing longwave radiation (OLR) obtained from the National Centers for Environmental Prediction reanalysis data. Results show a marked seasonality, associated with high spatial variation in terms of cloud occurrence over Senegal. The maximum cloud occurrences are observed during the wet summer season (June–October), whilst the minimum cloud occurrences are recorded during the long-dry season from November to May. During the monsoon season the cloud activity becomes more intense with a total cloud cover of about 80%, a cloud optical depth of around 7, and a high convective activity illustrated by a low OLR (below 240 W/m2). Likewise, across Senegal a strong north-south gradient of the cloud characteristics is observed. Based on quantitative comparison between cloud occurrence and radiation measurement, results show an important seasonal impact on available solar potential in Mbour. Conversely to the cloud occurrence, the maximum of both direct normal and global solar potentials is recorded during the dry season, coinciding with the period with clean sky. An investigation of the cloud influence on solar radiation on selected study cases indicates a decrease of 60% (80%) for the total (direct normal) radiation during the peak of the summer monsoon season.

Drought Offsets the Controls on Colored Dissolved Organic Matter in Lakes

The concentration of colored dissolved organic matter (CDOM) in lakes is strongly influenced by climate, land cover, and topographic settings, but it is not known how drought may affect the relative importance of these controls. Here, we evaluate the controls of CDOM during two summers with strongly contrasting values of the Palmer drought index (PDI), indicating wet vs. dry conditions. We hypothesized that lake CDOM during a wet summer season is regulated mainly by the surrounding land cover to which the lakes are hydrologically connected, while, during drought, the lakes are disconnected from the catchment and CDOM is regulated by climatic and morphometric factors that govern the internal turnover of CDOM in the lakes. A suite of climate, land cover, and morphometric variables was assembled and used to explain remotely sensed CDOM values for 255 boreal lakes distributed across broad environmental and geographic gradients in Sweden and Norway. We found that PDI explained the variability in CDOM among lakes in a dry year, but not in a wet year, and that severe drought strongly decreased CDOM during the dry year. Large lakes, especially, with a presumed high degree of catchment uncoupling, showed low CDOM during the dry year. However, in disagreement with our hypothesis, climate, land cover, and morphometry all showed a stronger impact on lake CDOM in wet vs. dry years. Thus, drought systematically weakened the predictability of CDOM variations at the same time as CDOM was offset toward lower values. Our results show that drought not only has a direct effect on CDOM, but also acts indirectly by changing the spatial regulation of CDOM in boreal lakes.

Wetness severity increases abrupt shifts in ecosystem functioning in arid savannas.

The accelerating pace of climate change has led to unprecedented shifts in surface temperature and precipitation patterns worldwide, with African savannas being among the most vulnerable regions. Understanding the impacts of these extreme changes on ecosystem health, functioning and stability is crucial. This paper focuses on the detection of breakpoints, indicative of shifts in ecosystem functioning, while also determining relevant ecosystem characteristics and climatic drivers that increase susceptibility to these shifts within the semi-arid to arid savanna biome. Utilising a remote sensing change detection approach and rain use efficiency (RaUE) as a proxy for ecosystem functioning, spatial and temporal patterns of breakpoints in the savanna biome were identified. We then employed a novel combination of survival analysis and remote sensing time series analysis to compare ecosystem characteristics and climatic drivers in areas experiencing breakpoints versus areas with stable ecosystem functioning. Key ecosystem factors increasing savanna breakpoint susceptibility were identified, namely higher soil sand content, flatter terrain and a cooler long-term mean temperature during the wet summer season. Moreover, the primary driver of changes in ecosystem functioning in arid savannas, as opposed to wetter tropical savannas, was found to be the increased frequency and severity of rainfall events, rather than drought pressures. This research highlights the importance of incorporating wetness severity metrics alongside drought metrics to comprehensively understand climate-ecosystem interactions leading to abrupt shifts in ecosystem functioning in arid biomes. The findings also emphasise the need to consider the underlying ecosystem characteristics, including soil, topography and vegetation composition, in assessing ecosystem responses to climate change. While this research primarily concentrated on the southern African savanna as a case study, the methodological robustness of this approach enables its application to diverse arid and semi-arid biomes for the assessment of climate-ecosystem interactions that contribute to abrupt shifts.

Spatiotemporal analysis of heavy summer rainfall events across the Free State Province, South Africa: 1981–2022

ABSTRACT Heavy rainfall events negatively impact agricultural productivity (e.g. crop damage) and human health (e.g. waterborne disease outbreaks). Under anthropogenically induced warming, South Africa may experience more frequent and heavier rainfall events during the summer wet-season. Evidence from point-based rainfall records suggests that such changes may already be occurring across many summer rainfall zone regions; however, the understanding thereof is spatially unresolved. Therefore, focusing on the summer rainfall zone Free State Province, we used the CHIRPS rainfall dataset for 1981/82–2021/22 to explore trends and interannual variability in the magnitude and frequency of heavy rainfall events for summer months (October–April). Interannually, the El Niño-Southern Oscillation had a predictable influence, with positive (negative) anomalies for the frequencies and magnitudes of heavy rainfall events during La Niña (El Niño) years. Despite few statistically significant trends, the results broadly depict increases (decreases) by up to 0.4 days/decade (−0.2 days/decade) in the frequency of smaller (larger) heavy rainfall events. More consistent trend results were evident for heavy rainfall event magnitude indices, with declining (increasing) trends, up to −2 mm/decade (5 mm/decade), evident over central (northeastern and southwestern) regions. Our results highlight regions vulnerable to changes and interannual variations in heavy rainfall characteristics, which can inform adaptation strategies.

Season of prescribed burns and management of an early successional species affect flower density and pollinator activity in a pine savanna ecosystem.

In the age of changing fire regimes, land managers often rely on prescribed burns to promote high diversity of herbaceous plants. Yet, little is known about how the timing of prescribed burns interacts with other ecological factors to maintain biodiversity while restoring fire-adapted ecosystems. We examined how timing of prescribed burns and removal of a dominant, early successional weedy plant yankeeweed (Eupatorium compositifolium) affect flower density and pollinator activity in an early-successional longleaf pine savanna restored from a timber plantation. During the first year of this study, plots received seasonal burn treatments, including unburned control, winter-dry, spring, and summer-wet season burns. During the second year of the study, data on flowers and pollinators were sampled across all plots. In the third year, these seasonal burn treatments were again applied to plots, and data were again collected on flowers and pollinators. In each burn treatment plot, we manipulated the presence of yankeeweed, including one control subplot (no removal) in which yankeeweed was not manipulated and one removal subplot in which yankeeweed was removed, and flowers and pollinators were measured. During the year between burns, flower density was highest in the summer-wet season burn treatment, significantly higher than in the unburned control, while pollinator activity was highest in the summer-wet and spring season burn treatments, significantly higher than the unburned control. During the year in which plots were burned again, flower density was highest in the spring season burn treatment, and pollinators most frequent in both spring and winter-dry season burn treatments, significantly higher than the unburned control. Removing yankeeweed enhanced pollinator activity but only in the year between fire applications. We conclude that prescribed burning enhances floral resource availability and pollinator activity, but the magnitude of these effects depends on when fires are applied. Additionally, removal of yankeeweed can enhance pollinator activity during years between prescribed burns.

An Unusual Resurgence of Human Metapneumovirus in Western Australia Following the Reduction of Non-Pharmaceutical Interventions to Prevent SARS-CoV-2 Transmission.

Non-pharmaceutical interventions (NPIs) to reduce SARS-CoV-2 transmission disrupted respiratory virus seasonality. We examined the unusual return of human metapneumovirus (hMPV) in Western Australia following a period of absence in 2020. We analysed hMPV laboratory testing data from 1 January 2017 to 31 December 2021. Whole-genome sequencing of selected hMPV-positive samples was performed using a tiled-amplicon approach. Following an absence in spring 2020, an unusual hMPV surge was observed during the wet summer season in the tropical Northern region in late 2020. Following a six-month delay, an intense winter season occurred in the subtropical/temperate Southern and Metropolitan regions. Compared to 2017–2019, hMPV incidence in 2021 increased by 3-fold, with a greater than 4-fold increase in children aged 1–4 years. There was a collapse in hMPV diversity in 2020, with the emergence of a single subtype. NPIs contributed to an absent 2020 season and a clonal hMPV resurgence. The summer surge and delayed winter season suggest that prevailing temperature and humidity are keys determinant of hMPV transmission. The increased incidence in 2021 was linked to an expanded cohort of hMPV-naïve 1–4-year-old children and waning population immunity. Further intense and unusual respiratory virus seasons are expected as COVID-19 associated NPIs are removed.

Characterisation of Selected Mungbean Genotypes for Tolerance to Waterlogging Stress at Pod Filling Stage

Mungbean is susceptible to waterlogging stress; therefore, breeding tolerant varieties would provide Australian growers with management options for wet summer season planting. Selection for waterlogging tolerance could be improved using vegetative indices that correlate to yield. Five mungbean genotypes were exposed to waterlogging stress at the pod-filling stage and characterised for various morphological and physiological traits governing seed yield. Waterlogging during pod filling decreased stomatal conductance (gs) and photosynthetic rate (Asat) to ~27% and 25% compared to control, respectively, resulting in a decline in effective quantum yield of PSII (ФPSII) and maximum efficiency of PSII of dark-adapted leaves (Fv/Fm) and leaf chlorophyll while increasing excitation pressure (1-qP) significantly. Waterlogging at pod filling reduced leaf count (19%), plant height (23%), leaf dry weight (38%), stem dry weight (33%), pod dry weight (36%), above-ground biomass (34%), root biomass (26%), and 100-seed weight (4%). Seed yield was highly positively correlated with Asat (0.86), gs (0.69), chlorophyll content (0.63), and ФPSII (0.59), with a highly negative correlation with 1-qP (−0.87) at 30 days of treatment imposition. A yield penalty of 32% was recorded under waterlogging stress compared to control plants, while the performance of all genotypes was found to be similar in terms of seed yield. Interestingly, genotype AVTMB#3 produced significantly larger seeds under waterlogging stress relative to other genotypes, including the leading Australian mungbean variety, Jade-AU. Based on a robust and significantly strong correlation with seed yield under waterlogging stress, 1-qP and photosynthetic rates (Asat) are recommended as potential indicators for the screening of mungbean genotypes. Thus, the current study presents a framework for screening waterlogging tolerance, which can provide a reasonable basis for the selection of various genotypes in future mungbean breeding programs.

Effects of climate change and water management on West Florida Shelf's dynamics

In the present study we evaluated, in a high-resolution simulation (1.5 km), the separate and combined effects of freshwater discharge management and climate warming by 1 °C on the Loop Current (LC) intrusions on the West Florida Shelf (WFS) and its dynamics in the subtropical western Atlantic. Based on a one-year simulation in which an LC and its eddy intruded on the WFS, either the increase of freshwater discharge or the climate warming led to a change in the stratification properties of the WFS significant enough to affect the type of LC intrusions. Increased freshwater discharge contributed to the intensification of shelf water mixing that favors surface intrusion of LC waters. On the contrary, 1 °C warming led to increased shelf waters stratification that favors bottom intrusions. Either type of intrusion leads to a different oceanographic regime on the shelf to which the ecosystem might respond differently. Our study suggests, however, that increased freshwater discharge could mitigate the effect of climate warming on the WFS by reducing shelf waters stratification. The WFS response to cold air outbreaks that are common in the fall and winter months was also analyzed. It showed that under a warmer climate, the increased stratification due to the freshwater discharge at the end of the boreal summer wet season is cancelled by the warmer climate and reduces the available potential energy on the shelf, limiting coastal upwelling, instabilities, and shelf convection.

Assessment of Porosity Defects in Ingot Using Machine Learning Methods during Electro Slag Remelting Process

The porosity defects in the ingot, which are caused by moisture absorption in slag during the electroslag remelting process, deserve the researcher’s attention in the summer wet season. The prediction of slag weight gain caused by moisture absorption is critical for developing slag baking and scheduling strategies and can assist workshop managers in making informed decisions during industrial production of electro slag remelting. The moisture absorption in slag under the conditions of different air humidity, experimental time, slag particle size, and CaO content in the slag are investigated by slag weight gain experiments. The purpose of this study is to predict the rate of weight gain in slag using observed weight gain data and machine learning (ML) models. The observation dataset includes features and rate of weight growth, which serve as independent and dependent variables, respectively, for ML models. Four machine learning models: linear regression, support vector regression, random forest regression, and multi-layer perceptron, were employed in this study. Additionally, parameters for machine learning models were selected using 5-fold cross-validation. Support vector regression outperformed the other three machine learning models in terms of root-mean-square errors, mean squared errors, and coefficients of determination. Thus, the ML-based model is a viable and significant method for forecasting the slag weight gain rate, whereas support vector regression can produce results that are competitive and satisfying. The results of slag weight gain data and ML models show that the slag weight gain increases with the increase of air humidity, experimental time, slag particle size, and CaO content in the slag. The porosity defect in the ingot during the ESR process often appears when the moisture in the slag exceeds 0.02%. Considering saving electric energy, the complexity of on-site scheduling, and 4 h of scheduling time, the slag T3 (CaF2:CaO:Al2O3:MgO = 37:28:30:5) is selected to produce H13 steel ESR ingot in the winter, and slag T2 (CaF2:CaO:Al2O3:MgO = 48:17:30:5) is selected to produce H13 steel ESR ingot in the summer.

The Establishment and Spread of a Newly Introduced Begomovirus in a Dry Tropical Environment Using Tomato Yellow Leaf Curl Virus as a Case Study.

Early detection of tomato yellow leaf curl virus (TYLCV) in a previously unaffected tomato production district in Australia allowed its spread to be evaluated spatially and temporally. The population dynamics of the TYLCV vector, Bemisia argentifolii (silverleaf whitefly, SLW), were also evaluated. The district is a dry tropical environment with a clear break to commercial production during the summer wet season. The incidence of TYLCV within crops and its prevalence through the district was influenced by weather, location, vector movements, and the use of Ty-1 virus-resistant hybrids. Rainfall had an important influence, with late summer and early autumn rain suppressing the levels of SLW and, by contrast, a dry summer supporting faster population growth. The use of Ty-1 hybrids appears to have reduced the incidence of TYLCV in this district. There was limited use of Ty-1 hybrids during 2013, and by season end, crops had moderate levels of SLW and high virus incidence. The 2015 and early 2016 season had high SLW populations, but TYLCV incidence was lower than in 2013, possibly due to the widespread adoption of the Ty-1 hybrids reducing virus spread. This study provides valuable epidemiology data for future incursions of begomoviruses, and other viruses spread by SLW.

A laboratory simulation to investigate effects of moistures on U distribution among solid phase components in army range soils

Uranium is a naturally occurring radioactive trace element found in rocks, soils, and coals. U may contaminate groundwater and soil from nuclear power plant operations, spent fuel reprocessing, high-level waste disposal, ore mining and processing, or manufacturing processes. Yuma Proving Ground in Arizona, USA has been used depleted uranium ballistics for 36 years where U has accumulated in this army testing site. The objective of this study is to develop a laboratory scheme on the effects of soil moisture regiments on the distribution and partitioning of U in army range soil among solid phase components to mimic U biogeochemical processes in the field. Three moisture regiments were saturated paste, field capacity, and wetting-drying cycle which covered major scenarios in fields from the wet summer season to the dry winter season. Uranium in soils with different forms of U (UO2, UO3, uranyl, and schoepite) was fractionated into 8 operationally defined solid components with sequential selective dissolution procedure. The essences of this new development were as following:•A scheme was developed for investigation of U distribution, partitioning and transformation among solid phase components in army weapon test range soils with various U forms under 3 soil moisture regimes.•Soil moisture was one of major environmental factors in controlling biogeochemical processes and fates of U in army weapon test site.

Using remote sensing to forecast forage quality for cattle in the dry savannas of northeast Australia

In the dry savannas of northeast Australia, forage quality is just as important for cattle production as forage quantity. The seasonal trend of forage quality is broadly predictable by land managers, but it is more difficult to predict the point when quality—which depends on local climate, management, and pasture condition—falls below the requirement for animal maintenance. In this study we use statistical modelling to forecast how forage quality might change at the crucial time of year, i.e., as the summer wet season transitions to the dry winter. We do this with the aid of historical information associated with a long-term cattle-grazing trial in the dry savannas. We combined multiple years of two measures of forage quality (dietary crude protein and in vivo dry-matter digestibility; respectively DCP and DMD) and ground cover information (specifically the ratio of ‘green grass’ cover to ‘dead (i.e., non-photosynthetic) grass’ cover, derived from an archive of Landsat satellite imagery) into a linear mixed model that explicitly considered the correlations with time and between variables. DCP and DMD were estimated by near-infrared spectroscopy of fresh faecal samples; values did not have to be temporally coincident with the satellite imagery. With the end of May considered a nominal decision-point, we forecast monthly averages of forage quality for June to August, over a 12-year period at the study site. Over all months and all years, the median absolute error of the forecasts was DCP = 0.86%, and DMD = 0.95%. The remote sensing information served as a correlated, oft-sampled covariate that helped to guide the forecasts of forage quality. We propose summarising the forecasts (and their uncertainty) as a near-real-time graphical tool for decision-support. Such a product could potentially benefit cattle-grazing enterprises in the northeast of Australia, enabling more timely management of herds through the dry season.

Characterizing Leaf Nutrients of Wetland Plants and Agricultural Crops with Nonparametric Approach Using Sentinel-2 Imagery Data

In arid environments of the world, particularly in sub-Saharan Africa and Asia, floodplain wetlands are a valuable agricultural resource. However, the water reticulation role by wetlands and crop production can negatively impact wetland plants. Knowledge on the foliar biochemical elements of wetland plants enhances understanding of the impacts of agricultural practices in wetlands. This study thus used Sentinel-2 multispectral data to predict seasonal variations in the concentrations of nine foliar biochemical elements in plant leaves of key floodplain wetland vegetation types and crops in the uMfolozi floodplain system (UFS). Nutrient concentrations in different floodplain plant species were estimated using Sentinel-2 multispectral data derived vegetation indices in concert with the random forest regression. The results showed a mean R2 of 0.87 and 0.86 for the dry winter and wet summer seasons, respectively. However, copper, sulphur, and magnesium were poorly correlated (R2 ≤ 0.5) with vegetation indices during the summer season. The average % relative root mean square errors (RMSE’s) for seasonal nutrient estimation accuracies for crops and wetland vegetation were 15.2 % and 26.8%, respectively. There was a significant difference in nutrient concentrations between the two plant types, (R2 = 0.94 (crops), R2 = 0.84 (vegetation). The red-edge position 1 (REP1) and the normalised difference vegetation index (NDVI) were the best nutrient predictors. These results demonstrate the usefulness of Sentinel-2 imagery and random forests regression in predicting seasonal, nutrient concentrations as well as the accumulation of chemicals in wetland vegetation and crops.

Differentiation of Hydrogen and Oxygen Isotopes in the Water Source Treatment Wetlands of Stream Networks

To explore the isotopic distribution and differentiation of water along the hydraulic flow gradients and plant-bed/ditch systems in constructed root-channel wetlands, surface and subsurface water samples were collected from four ecological wetlands, namely Shijiuyang and Guanjinggang in Jiaxing, as well as Changshuitang and Taishangang in Haining. All samples were collected along water flow pathways during the wet and rainy summer season in August 2019, except for those from Taishangang, which were collected within the plant-bed/ditch system during the dry and cold winter season in January 2020. The abundance of deuterium (δD) and δ18 O was determined in each functional area of the wetlands to assess the influence of wetlands on water differentiation. Stable isotope technology and mathematical statistics were used to analyze the distribution of δD and δ18 O in constructed root-channel wetlands and to reveal the influence of plant-bed/ditch systems on stable isotopes of water. A variety of data mining methods were used to examine the differentiation of stable isotopes of water, at various dimensions and scales, including nonparametric Kendall's tau-b correlation, stepwise regression, gray relational analysis, and machine learning (random forest) combined with scatter diagrams and model hypothesis diagnosis analysis. The main results were as follows:① The spatiotemporal variations in water isotopes of stream networks were largely affected by different water supply and evaporation enrichment effects. The slope and intercept of the wetland water line in Jiaxing were both significantly lower than the regional precipitation line of the adjacent Changshu Station (CHNIP). This showed that the wetlands area had undergone hydrogen and oxygen isotope enrichment. The δD values in Shijiuyang wetland water ranged from -52.2‰ to -49.4‰, and δ18 O values ranged from -7.6‰ to -6.9‰. In Guanjinggang wetland water samples, δD ranged from -48.1‰ to -45.1‰, and δ18 O ranged from -6.8‰ to -5.8‰. The δD values in Changshuitang wetland water ranged from -49.8‰ to -48.4‰, and δ18 O ranged from -7.2‰ to -6.6‰. The δD values in Taishangang wetland water ranged from -55.3‰ to -51.6‰, and δ18 O ranged from -7.8‰ to -7.2‰. ② Hydrogen and oxygen isotope abundance and composition of water showed complex nonlinear changes in the vertical and horizontal dimensions at different scales. At the regional scale, water level elevation in the vertical dimension had a greater impact on water isotope distribution than the length of the hydraulic flow pathway in the horizontal dimension. Water isotopes tended to be enriched in low-lying areas with low water levels. At the local scale, the influence of hydraulic process often played a greater role in determining water isotope distributions. The spatial variations of water isotopes were comprehensively determined by the evaporation of regional water and meandering hydraulic processes inside the wetland. ③ Compared with other wetland functional areas, the central constructed root-channel area (middle treatment zone) was more enriched in water isotopes. ④ The underground macropore network formed by plants with developed rhizomes or roots (e.g., Phragmites communis Trin. and Typha orientalis Presl), mineral-rich substrate soil, and aquatic plants in the plant bed had a significant influence on the abundance of hydrogen and oxygen isotopes in the plant-bed/ditch system. Therefore, when water passed through the plant-bed/ditch system, the values of δD and δ18 O in the lower ditch (outlet) were lower than those in the higher ditch (inlet). ⑤ The abrupt change in isotopic contents of the plant-bed/ditch system might indicate an inflection point in water quality purification. ⑥ The deuterium excess (d-excess) in subsurface water of the plant-bed/ditch system was significantly higher than that in ditch water, and the coefficient of variation in subsurface water was considerably greater than that in ditch water. The d-excess in the wetland root-channel ecological purification zone showed significant temporal differences and was negative in the summer and positive in the winter, which reflected the seasonal variation in water vapor sources and the spatial variation in isotope fractionation behavior in wetlands. These results provide some understanding of the distribution of water isotopes in constructed wetlands, which will strengthen their operation and management. This study also provides some ideas regarding new technologies for water quality improvement and shows that water isotope technology may be a reliable method for analyzing wetland hydrology.

Eutrophication increases deterministic processes and heterogeneity of co-occurrence networks of bacterioplankton metacommunity assembly at a regional scale in tropical coastal reservoirs

Understanding microbial metacommunity assembly and the underlying methanisms are fundamental objectives of aquatic ecology. However, little is known about how eutrophication, the primary water quality issue of aquatic ecosystems, regulates bacterioplankton metacommunity assembly at a regional scale in reservoirs. In this study, we applied a metacommunity framework to study bacterioplankton communities in 210 samples collected from 42 tropical coastal reservoirs in the wet summer season. We found that the spatial pattern of bacterioplankton community compositions (BCCs) at a regional scale was shaped mainly by species sorting. The reservoir trophic state index (TSI) was the key determinant of bacterioplankton metacommunity assembly. BCC turnover increased significantly with the TSI differences between sites (∆TSI) when ∆TSI was < 20, but remained at a level of about 80% when ∆TSI was > 20. Compared to oligo-mesotrophic and mesotrophic reservoirs, increased heterogeneity of co-occurrence bacterioplankton networks and bacterioplankton β-diversity were observed across eutrophic reservoirs. We propose that larger variation in phytoplankton community assembly may play directly or indirectly deterministic processes in controlling the bacterioplankton metacommunity assembly and became the potential mechanisms behind the observed higher BCC heterogeneity across the eutrophic reservoirs. Our research contributes to a broader understanding of the ecological effects of eutrophication on reservoir ecosystems and provides clues to the management of the tropical coastal reservoirs.

An in-depth analysis of self-reported cycling injuries in single and multiparty bicycle crashes in Denmark

Introduction: Cycling is one of the main forms of transportation in Denmark. However, while the number of traffic crash fatalities in the country has decreased over the past decade, the frequency of cyclists killed or seriously injured has increased. The high rate of serious injuries and fatalities associated with cycling emphasizes the increasing need for mitigating the severity of such crashes. Method: This study conducted an in-depth analysis of cyclist injury severity resulting from single and multiparty bicycle-involved crashes. Detailed information was collected using self-reporting data undertaken in Denmark for a 12-month period between 1 November 2012 and 31 October 2013. Separate multilevel logistic (MLL) regression models were applied to estimate cyclist injury severity for single and multiparty crashes. The goodness-of-fit measures favored the MLL models over the standard logistic models, capturing the intercorrelation among bicycle crashes that occurred in the same geographical area. Results: The results also showed that single bicycle-involved crashes resulted in more serious outcomes when compared to multiparty crashes. For both single and multiparty bicycle crash categories, non-urban areas were associated with more serious injury outcomes. For the single crashes, wet surface condition, autumn and summer seasons, evening and night periods, non-adverse weather conditions, cyclists aged between 45 and 64 years, male sex, riding for the purpose of work or educational activities, and bicycles with light turned-off were associated with severe injuries. For the multiparty crashes, intersections, bicycle paths, non-winter season, not being employed or retired, lower personal car ownership, and race bicycles were directly related to severe injury consequences. Practical Applications: The findings of this study demonstrated that the best way to promote cycling safety is the combination of improving the design and maintenance of cycling facilities, encouraging safe cycling behavior, and intensifying enforcement efforts.

Detection of seasonal changes in vegetation and morphology on coastal salt marshes using terrestrial laser scanning

Coastal salt marshes exhibit strong seasonal variations that may induce subsequent changes in their morphology. However, such changes are insufficiently understood due to a lack of data at seasonal timescales. Knowledge of the seasonal variability is essential for coastal management and ecosystem conservation. Terrestrial laser scanning (TLS) technology allows the rapid acquisition of high-resolution and large-scale vegetation and morphology data with an error of <3 cm. In this study, we used a TLS system to retrieve high-accuracy digital canopy models (DCM) for low vegetation species (approximately 20 cm) Suaeda salsa and digital terrain models (DTM) of a marsh in the Yellow River Delta. We conducted three TLS surveys on the same field on January 5, April 21, and November 20, 2019, which spanned from the dry to wet seasons. The centimeter-scale TLS data retrieved the seasonal variations of vegetation and elevation distributions. The DCMs of the study area showed that the percentages of vegetation-occupied regions were 13.5% and 22.5% in the dry and wet seasons, respectively. The DTMs indicated a net erosion of the study area throughout the year, but at a larger erosion rate in the dry than the wet season, that is, a rate of 2.5 and 0.2 cm/month, respectively. Spatially, regions with vegetation and zones adjacent to creeks underwent slight deposition. We inferred that the larger riverine sediment supply and higher vegetation density in the wet (summer) season mitigated erosion, while the influence of rich sediment supply was crucial. This work demonstrates the applicability of TLS in detecting the distribution of low-height vegetation species, and quantifying vegetation and morphological changes of marshes at seasonal timescales owing to its high resolution.

HEMATOLOGY, PLASMA BIOCHEMISTRY, AND PLASMA PROTEIN ELECTROPHORESIS REFERENCE INTERVALS FOR BLUE IGUANAS (CYCLURA LEWISI) FROM GRAND CAYMAN ISLAND.

The blue iguana (Cyclura lewisi) is an endangered rock iguana species native to Grand Cayman, in the Cayman Islands. Health assessments were conducted on captive and free-roaming iguanas in 2001 and 2003-2014 and were performed in the summer wet season (June-July) of 2003-2004 and 2010-2014 and in the winter dry season (November-December) of 2001 and 2005-2009. Morphometric data were recorded from iguanas when blood samples were collected: 903 samples were collected and data from 890 samples from 775 iguanas were included. Samples were analyzed for hematology, plasma biochemistry, protein electrophoresis, mineral panels, 25-hydroxyvitamin D, and testosterone. Reference intervals were created for captive subadults, captive adults, and free-roaming adults when data were sufficient. Significant differences among these groups were described, as were differences on the basis of sex, season, and origin (captive vs free-roaming). In captive iguanas, most analytes were significantly different between subadults and adults, mature heterophils and copper were significantly higher in the dry season, zinc levels were significantly higher in the wet season, and cholesterol and triglycerides were significantly higher in adult females than adult males. Testosterone in adult males was significantly higher in the dry season. These results will aid in future health assessments and disease investigations in wild and captive populations of blue iguanas and are of comparative value for other Cyclura species that are free-roaming, captive, and, especially, in similar conservation release programs.