Restoration of ditched and drained wetlands in the Lake Okeechobee basin, Florida, USA is currently under study for possible amelioration of anthropogenic phosphorus enrichment of the lake. Here we focus on the dynamic hydrology of these systems, with emphasis on understanding the interaction between wetland surface water and adjacent upland groundwater. Based on natural drawdown events observed over 2 years at four depressional wetlands, hydraulic conductivities (K) of the soils surrounding the wetlands were calculated at the wetland scale (approximately 2 ha) using the modified Dupuit equation under a constrained water budget framework. The drawdown-based average K=6.6 m/d (range 0.9 to 21.3 m/d) was about three times greater than slug test-based values (1.9±1.5 m/d), which is consistent with scale-dependent expectations. Net groundwater recharge rate at each depressional wetland, calculated based on the mean K, corresponded to approximately 40% of rainfall in the same period (10.0 m 3 /d). The average net groundwater recharge decreased by approximately 15% if ET was increased by 30%. Variability in estimated K and groundwater flow between the study wetlands was likely due to the relative difference of ditch bottom elevation controlling the surface outflow, as well as the spatial heterogeneity of the soils.
Although population models are recognized as necessary tools in the ecological risk assessment of pesticides, particularly for species listed under the Endangered Species Act, their application in this context is currently limited to very few cases. The authors developed a detailed, individual-based population model for a threatened plant species, the decurrent false aster (Boltonia decurrens), for application in pesticide risk assessment. Floods and competition with other plant species are known factors that drive the species' population dynamics and were included in the model approach. The authors use the model to compare the population-level effects of 5 toxicity surrogates applied to B. decurrens under varying environmental conditions. The model results suggest that the environmental conditions under which herbicide applications occur may have a higher impact on populations than organism-level sensitivities to an herbicide within a realistic range. Indirect effects may be as important as the direct effects of herbicide applications by shifting competition strength if competing species have different sensitivities to the herbicide. The model approach provides a case study for population-level risk assessments of listed species. Population-level effects of herbicides can be assessed in a realistic and species-specific context, and uncertainties can be addressed explicitly. The authors discuss how their approach can inform the future development and application of modeling for population-level risk assessments of listed species, and ecological risk assessment in general. Environ Toxicol Chem 2017;36:480-491. © 2016 SETAC.
Conceptually, imagine a vice where on one end there is demand for urban expansion (roads, buildings, industry/commerce, neighborhoods, etc.), on the other end there is societal demand for conservation (“listed” species protections, rewilding of farmlands, mitigations, etc.), and in the middle, being increasingly squeezed, exists the agricultural landscape of America. Conceptually, you can frame the shrinking land challenge. America’s farmland is shrinking while the urban landscape is expanding, and calls for preservation are growing increasingly louder. Land is finite, and once crops are converted to concrete the land is irrevocably changed. Technology has manifested an abundance of food; however, technology (e.g., genetically modified crops, pesticides, fertilizers, etc.) is also experiencing enhanced scrutiny as the frontier of agriculture inevitably converges with the aspirational boundaries of conservation. Unfortunately, few people are aware of the delicate policy intersection of food security, conservation, and population growth. Here we feature this conceptual challenge to provoke necessary discussion and debate.
Extrapolating from organism-level endpoints, as generated from standard pesticide toxicity tests, to populations is an important step in threatened and endangered species risk assessments. We apply a population model for a threatened herbaceous plant species, Boltonia decurrens, to estimate the potential population-level impacts of 3 herbicides. We combine conservative exposure scenarios with dose-response relationships for growth and survival of standard test species and apply those in the species-specific model. Exposure profiles applied in the B. decurrens model were estimated using exposure modeling approaches. Spray buffer zones were simulated by using corresponding exposure profiles, and their effectiveness at mitigating simulated effects on the plant populations was assessed with the model. From simulated exposure effects scenarios that affect plant populations, the present results suggest that B. decurrens populations may be more sensitive to exposures from herbicide spray drift affecting vegetative stages than from runoff affecting early seedling survival and growth. Spray application buffer zones were shown to be effective at reducing effects on simulated populations. Our case study demonstrates how species-specific population models can be applied in pesticide risk assessment to bring organism-level endpoints, exposure assumptions, and species characteristics together in an ecologically relevant context. Environ Toxicol Chem 2018;37:1545-1555. © 2018 SETAC.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.