Analyzing the impact of agricultural BMPs on stream nutrient load and biotic health in the Susquehanna-Chemung basin of New York.

Despite the widespread use of agricultural best management practices (BMPs) to reduce watershed scale nutrient loads, there remain few studies that use directly observed data - instead of models - to evaluate BMP effectiveness at the watershed scale. In this study, we make use of extensive ambient water quality data, stream biotic health data, and BMP implementation data within the New York State portion of the Chesapeake Bay watershed to assess the role of BMPs on reducing nutrient loads and modifying biotic health in major rivers. The specific BMPs considered were riparian buffers and nutrient management planning. A simple mass balance approach was used to evaluate the role of wastewater treatment plant nutrient reductions, agricultural land use changes, and these two agricultural BMPs in matching observed downward trends in nutrient load. In the Eastern nontidal network (NTN) catchment - where BMPs have been more widely reported - the mass balance model suggested a small but discernible contribution of BMPs in matching the observed downward trend in total phosphorus. Contrastingly, BMP implementations did not show clear contributions towards total nitrogen reductions in the Eastern NTN catchment nor for the total nitrogen and phosphorus in the Western NTN catchment, where BMP implementation data are more limited. Assessment of the relationship between stream biotic health and BMP implementation using regression models found limited connection between extent of BMP implementation and biotic health. In this case, however, spatiotemporal mismatches between the datasets and the relatively stable biotic health, typically of moderate to good quality even before BMP implementation, may reflect the need for better monitoring design to assess BMP effects at the subwatershed scale. Additional studies, perhaps using citizen scientists, may be able to provide more suitable data within the existing frameworks of the long-term surveys. Given the preponderance of studies that rely only on modeling to understand nutrient loading reductions achieved by implementation of BMPs, it is essential to continue to collect empirical data to meaningfully evaluate whether there are actual measurable changes due to BMPs.

Water warming increases aggression in a tropical fish.

Our understanding of how projected climatic warming will influence the world's biota remains largely speculative, owing to the many ways in which it can directly and indirectly affect individual phenotypes. Its impact is expected to be especially severe in the tropics, where organisms have evolved in more physically stable conditions relative to temperate ecosystems. Lake Tanganyika (eastern Africa) is one ecosystem experiencing rapid warming, yet our understanding of how its diverse assemblage of endemic species will respond is incomplete. Herein, we conducted a laboratory experiment to assess how anticipated future warming would affect the mirror-elicited aggressive behaviour of Julidochromis ornatus, a common endemic cichlid in Lake Tanganyika. Given linkages that have been established between temperature and individual behaviour in fish and other animals, we hypothesized that water warming would heighten average individual aggression. Our findings support this hypothesis, suggesting the potential for water warming to mediate behavioural phenotypic expression through negative effects associated with individual health (body condition). We ultimately discuss the implications of our findings for efforts aimed at understanding how continued climate warming will affect the ecology of Lake Tanganyika fishes and other tropical ectotherms.

Optimization of extraction methods for quantification of microcystin-LR and microcystin-RR in fish, vegetable, and soil matrices using UPLC-MS/MS.

Human-driven environmental change has increased the occurrence of harmful cyanobacteria blooms in aquatic ecosystems. Concomitantly, exposure to microcystin (MC), a cyanobacterial toxin that can accumulate in animals, edible plants, and agricultural soils, has become a growing public health concern. For accurate estimation of health risks and timely monitoring, availability of reliable detection methods is imperative. Nonetheless, quantitative analysis of MCs in many types of biological and environmental samples has proven challenging because matrix interferences can hinder sample preparation and extraction procedures, leading to poor MC recovery. Herein, controlled experiments were conducted to enhance the use of ultra-performance liquid-chromatography tandem-mass spectrometry (UPLC-MS/MS) to recover MC-LR and MC-RR at a range of concentrations in seafood (fish), vegetables (lettuce), and environmental (soil) matrices. Although these experiments offer insight into detailed technical aspects of the MC homogenization and extraction process (i.e., sonication duration and centrifugation speed during homogenization; elution solvent to use during the final extraction), they centered on identifying the best (1) solvent system to use during homogenization (2-3 tested per matrix) and (2) single-phase extraction (SPE) column type (3 tested) to use for the final extraction. The best procedure consisted of the following, regardless of sample type: centrifugation speed = 4200 × g; elution volume = 8 mL; elution solvent = 80% methanol; and SPE column type = hydrophilic-lipophilic balance (HLB), with carbon also being satisfactory for fish. For sonication, 2 min, 5 min, and 10 min were optimal for fish, lettuce, and soil matrices, respectively. Using the recommended HLB column, the solvent systems that led to the highest recovery of MCs were methanol:water:butanol for fish, methanol:water for lettuce, and EDTA-Na4P2O7 for soils. Given that the recommended procedures resulted in average MC-LR and MC-RR recoveries that ranged 93 to 98%, their adoption for the preparation of samples with complex matrices before UPLC-MS/MS analysis is encouraged.