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Global freshwater biodiversity is declining dramatically, and meeting the challenges of this crisis requires bold goals and the mobilisation of substantial resources. While the reasons are varied, investments in both research and conservation of freshwater biodiversity lag far behind those in the terrestrial and marine realms. Inspired by a global consultation, we identify 15 pressing priority needs, grouped into five research areas, in an effort to support informed stewardship of freshwater biodiversity. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated actions towards its sustainable management and conservation.

Freshwater biodiversity is declining dramatically, and the current biodiversity crisis requires defining bold goals and mobilizing substantial resources to meet the challenges. While the reasons are varied, both research and conservation of freshwater biodiversity lag far behind efforts in the terrestrial and marine realms. We identify fifteen pressing global needs to support informed global freshwater biodiversity stewardship. The proposed agenda aims to advance freshwater biodiversity research globally as a critical step in improving coordinated action towards its sustainable management and conservation.

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Crop models are useful tools to evaluate the effects of agricultural management on ecosystem services. However, before they can be applied with confidence, it is important to calibrate and validate crop models in the region of interest. In this study, the Environmental Policy Integrated Climate (EPIC) model was evaluated for its potential to simulate maize yield using limited data from field trials on two maize cultivars. Two independent fields at the Cradock Research Farm were used, one for calibration and one for validation. Before calibration, mean simulated yield was 8 t ha −1 while mean observed yield was 11.26 t ha −1 . Model calibration improved mean simulated yield to 11.23 t ha −1 with a coefficient of determination, (r 2 ) = 0.76 and a model efficiency (NSE) = 0.56. Validation with grain yield was satisfactory with r 2 = 0.85 and NSE = 0.61. Calibration of potential heat units (PHUs) and soil-carbon related parameters improved model simulations. Although the study only used grain yield to calibrate and evaluate the model, results show that the calibrated model can provide reasonably accurate simulations. It can be concluded that limited data sets from field trials on maize can be used to calibrate the EPIC model when comprehensive experimental data are not available.Agronomy 2019, 9, 494 2 of 16 used to test the effectiveness of alternative agricultural land management practices under varying climate change scenarios. However, to yield meaningful results, it is prudent to calibrate crop models in the region of intended use before their application [11].Model calibration is the procedure where model parameters are fine-tuned to increase the agreement between model simulations and real-world observations [12]. Calibration is important to increase model accurateness and decrease model prediction uncertainty [13]. Calibration is done by judiciously choosing model parameter values, adjusting them within recommended ranges, for example, from literature or expert opinions, and comparing the simulated outputs with observed data for a given set of conditions [14]. A successful calibration would be when the model reproduces observed data within a satisfactory degree of accuracy and precision for the intended model use [15,16]. Once calibrated and validated, the model can be reasonably applied in the area of interest. Calibrated crop growth models can, therefore, be useful tools to complement field experiments and support decision making for sustainable agricultural land management.The Environmental Policy Integrated Climate (EPIC) model [17], originally developed in the United States of America (USA), is a process-based, field-scale model with a daily time scale. It simulates the chemical processes occurring in the soil-water-plant interaction under different agricultural management regimes [18]. The main components of EPIC are weather simulation, crop growth, carbon and nutrient cycling, tillage, soil erosion, and hydrology [19]. Globally, the model has been applied to study crop yield responses to nutrients and...

Elevated instream fine sediment is one of the most important water quality stressors affecting both the structure and function of aquatic ecosystems. This study evaluates whether a predictable pattern of trait distribution of Ephemeroptera, Plecoptera, and Trichoptera (EPT) can be observed along a gradient of sediment stress in eight selected sites in the Tsitsa River and its tributaries. The sites were classified into four site groups according to their fine sediment loads. One-way analysis of variance was used to test differences in the relative abundance of traits across the site groups. A predictable pattern was observed in 13 of the 27 trait attributes tested, with most traits displaying low abundances in highly disturbed site groups. The relationship between EPT traits and fine sediment stress was analysed using the multivariate RLQ analysis, and the result showed that traits such as swimming, shredding, operculate gill, small body size, and sclerotized body were the dominant traits in the sediment influenced site groups. In the less disturbed site groups, filter feeding, crawling, filamentous gill, soft and exposed body, and large body size were the dominant trait attributes. These observed relationships between EPT traits and sediment stress provide support for the potential usefulness of EPT traits as indicators of fine sediment stress in riverine ecosystems.

Rivers suffer from multiple stressors acting simultaneously on their biota, but the consequences are poorly quantified at the global scale. We evaluated the biological condition of rivers globally, including the largest proportion of countries from the Global South published to date. We gathered macroinvertebrate‐ and fish‐based assessments from 72,275 and 37,676 sites, respectively, from 64 study regions across six continents and 45 nations. Because assessments were based on differing methods, different systems were consolidated into a 3‐class system: Good, Impaired, or Severely Impaired, following common guidelines. The proportion of sites in each class by study area was calculated and each region was assigned a Köppen‐Geiger climate type, Human Footprint score (addressing landscape alterations), Human Development Index (HDI) score (addressing social welfare), % rivers with good ambient water quality, % protected freshwater key biodiversity areas; and % of forest area net change rate. We found that 50% of macroinvertebrate sites and 42% of fish sites were in Good condition, whereas 21% and 29% were Severely Impaired, respectively. The poorest biological conditions occurred in Arid and Equatorial climates and the best conditions occurred in Snow climates. Severely Impaired conditions were associated (Pearson correlation coefficient) with higher HDI scores, poorer physico‐chemical water quality, and lower proportions of protected freshwater areas. Good biological conditions were associated with good water quality and increased forested areas. It is essential to implement statutory bioassessment programs in Asian, African, and South American countries, and continue them in Oceania, Europe, and North America. There is a need to invest in assessments based on fish, as there is less information globally and fish were strong indicators of degradation. Our study highlights a need to increase the extent and number of protected river catchments, preserve and restore natural forested areas in the catchments, treat wastewater discharges, and improve river connectivity.