Climate change mitigation potential of Louisiana's coastal area: Current estimates and future projections.

Coastal habitats can play an important role in climate change mitigation. As Louisiana implements its climate action plan and the restoration and risk-reduction projects outlined in its 2017 Louisiana Coastal Master Plan, it is critical to consider potential greenhouse gas (GHG) fluxes in coastal habitats. This study estimated the potential climate mitigation role of existing, converted, and restored coastal habitats for years 2005, 2020, 2025, 2030, and 2050, which align with the Governor of Louisiana's GHG reduction targets. An analytical framework was developed that considered (1) available scientific data on net ecosystem carbon balance fluxes per habitat and (2) habitat areas projected from modeling efforts used for the 2017 Louisiana Coastal Master Plan to estimate the net GHG flux of coastal area. The coastal area was estimated as net GHG sinks of -38.4 ± 10.6 and -43.2 ± 12.0 Tg CO2 equivalents (CO2 e) in 2005 and 2020, respectively. The coastal area was projected to remain a net GHG sink in 2025 and 2030, both with and without the implementation of Coastal Master Plan projects (means ranged from -25.3 to -34.2 Tg CO2 e). By 2050, with model-projected wetland loss and conversion of coastal habitats to open water due to coastal erosion and relative sea level rise, Louisiana's coastal area was projected to become a net source of GHG emissions both with and without the Coastal Master Plan projects. However, in the year 2050, the Louisiana Coastal Master Plan project implementation was projected to avoid the release of +8.8 ± 1.3 Tg CO2 e compared with an alternative with no action. Reduction in current and future stressors to coastal habitats, including impacts from sea level rise, as well as the implementation of restoration projects could help to ensure coastal areas remain a natural climate solution.

The polychaete, Paraprionospio pinnata, is a likely vector of domoic acid to the benthic food web in the northern Gulf of Mexico.

A somewhat disparate, yet temporally cohesive, set of phytoplankton abundance, microphytobenthos, including the diatom Pseudo-nitzschia, benthic infauna, and sediment toxin data were used to develop a theory for the transfer of domoic acid (DA) from the toxic diatom to the benthos in the highly productive waters of the northern Gulf of Mexico near the Mississippi River plume. Archived samples and new data were used to test the theory that DA is likely to be incorporated into benthic consumers. High spring abundances of potentially toxic Pseudo-nitzschia diatoms were simultaneously present in the surface waters, bottom waters and on the seafloor. Examination of the gut contents of a typical deposit-feeding and suspension-feeding polychaete, Paraprionospio pinnata, during similar periods of high Pseudo-nitzschia abundance in surface water indicated consumption of the diatoms. Demersal fishes, particularly Atlantic croaker, are known to consume these polychaetes, with a potential for transfer of DA to even higher trophic levels. These findings warrant a theory to be tested with further studies about the trophic linkage of a phytoplankton toxin into the benthic food web.

Historical Associations of Molecular Measurements of Escherichia coli and Enterococci to Anthropogenic Activities and Climate Variables in Freshwater Sediment Cores.

This study investigated the long-term associations of anthropogenic (sedimentary P, C, and N concentrations, and human population in the watershed), and climatic variables (air temperature, and river discharge) with Escherichia coli uidA and enterococci 23S rRNA concentrations in sediment cores from Anchor Bay (AB) in Lake St. Clair, and near the mouth of the Clinton River (CR), Michigan. Calendar year was estimated from vertical abundances of (137)Cs. The AB and CR cores spanned c.1760-2012 and c.1895-2012, respectively. There were steady state concentrations of enterococci in AB during c.1760-c.1860 and c.1910-c.2003 at ∼0.1 × 10(5) and ∼2.0 × 10(5) cell equivalents (CE) per g-dry wt, respectively. Enterococci concentrations in CR increased toward present day, and ranged from ∼0.03 × 10(5) to 9.9 × 10(5) CE/g-dry wt. The E. coli concentrations in CR and AB increased toward present day, and ranged from 0.14 × 10(7) to 1.7 × 10(7) CE/g-dry wt, and 1.8 × 10(6) to 8.5 × 10(6) CE/g-dry wt, respectively. Enterococci was associated with population and river discharge, while E. coli was associated with population, air temperature, and N and C concentrations (p < 0.05). Sediments retain records of the abundance of fecal indicator bacteria, and offer a way to evaluate responses to increased population, nutrient loading, and environmental policies.

Coupling socioeconomic and lake systems for sustainability: a conceptual analysis using Lake St. Clair region as a case study.

Applying sustainability at an operational level requires understanding the linkages between socioeconomic and natural systems. We identified linkages in a case study of the Lake St. Clair (LSC) region, part of the Laurentian Great Lakes system. Our research phases included: (1) investigating and revising existing coupled human and natural systems frameworks to develop a framework for this case study; (2) testing and refining the framework by hosting a 1-day stakeholder workshop and (3) creating a causal loop diagram (CLD) to illustrate the relationships among the systems' key components. With stakeholder assistance, we identified four interrelated pathways that include water use and discharge, land use, tourism and shipping that impact the ecological condition of LSC. The interrelationships between the pathways of water use and tourism are further illustrated by a CLD with several feedback loops. We suggest that this holistic approach can be applied to other case studies and inspire the development of dynamic models capable of informing decision making for sustainability.

A Bayesian hierarchical modeling approach for analyzing observational data from marine ecological studies.

We introduce the Bayesian hierarchical modeling approach for analyzing observational data from marine ecological studies using a data set intended for inference on the effects of bottom-water hypoxia on macrobenthic communities in the northern Gulf of Mexico off the coast of Louisiana, USA. We illustrate (1) the process of developing a model, (2) the use of the hierarchical model results for statistical inference through innovative graphical presentation, and (3) a comparison to the conventional linear modeling approach (ANOVA). Our results indicate that the Bayesian hierarchical approach is better able to detect a "treatment" effect than classical ANOVA while avoiding several arbitrary assumptions necessary for linear models, and is also more easily interpreted when presented graphically. These results suggest that the hierarchical modeling approach is a better alternative than conventional linear models and should be considered for the analysis of observational field data from marine systems.