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Global distribution of the cold-water coral Lophelia pertusa
Get PDFLophelia pertusa plays an important role as a major contributor to many cold-water coral reefs, supporting a high diversity of associated benthic and benthopelagic species. Due to the high sensitivity of L. pertusa to human activity, it has been classified as indicator species for Vulnerable Marine Ecosystems. However, the global spatial distribution of L. pertusa is far from well known. In this study, a database of L. pertusa presence data was compiled derived from the large number of L. pertusa occurrence records appearing in recent years. In conjunction with data layers covering a range of environmental drivers, habitat suitability for L. pertusa was predicted using the Random Forest approach. Suitable habitat for L. pertusa was predicted to occur primarily on continental margins, with the most suitable habitat likely to occur in the North East Atlantic and South Eastern United States of America. Aragonite saturation state, temperature and salinity were identified as the most important contributors to the habitat suitability model. Given the high vulnerability of reef-forming cold-water corals to anthropogenic impacts, habitat suitability models are critical in developing worldwide conservation and management strategies for biodiverse and biomass rich cold-water coral ecosystems
The Scientific Basis of Climate Change: Understanding the Past to Present and Implications for the Future
Get PDFWe will discuss the current state of the science of climate, its variations and change especially since preindustrial times (part of Anthropocene era). Developing mathematical models of the Earth\u27s climate system and utilizing observations, we investigate the forcing of the climate system which includes natural and human causes; processes and interactions that govern the sensitivity of the system; and impacts ranging from globe-wide to regional spatial scales. The use of model simulations and observational evidence of the past-to-present changes leads to attribution and identification of the mechanisms, including traceability to human-induced activities. The climate system perturbations extend across Earth\u27s physical, biogeochemical and ecosystem domains. Understanding of the past climate and scenarios of mankind\u27s development leads to numerical projections of future climate states, including expectations of changes in extremes of societal concern. Challenges on the science side include improving confidence measures in the outcomes which can then provide improved guidance to technical solutions for adaptation and mitigation. The steady progress in the understanding of the nonstationary climate system has led to reliable science-based inputs for policy decision-making
Salt marsh climate change adaptation: Using runnels to adapt to accelerating sea level rise within a drowning New England salt marsh
No full textSea level rise within New England is accelerating at a rate faster than the global average, leaving salt marshes particularly susceptible to degradation. Hydrological alteration is a type of climate change adaptation technique that can be used to combat the effects of sea level rise within salt marshes. Runnels (shallow channels) are a type of climate adaptation strategy used to enhance drainage in drowning marshes. In this study, we investigated the impacts of runnel installations, 3–5 years post-implementation, on soil properties, vegetation composition, and greenhouse gas fluxes. We studied two runnel treatments (Low Elevation Runnel and High Elevation Runnel) and found that in the Low Elevation Runnel areas Spartina alterniflora stem density significantly increased in the three growing seasons after runnels were installed, and the high marsh plant, Spartina patens, persisted in the High Elevation Runnel areas. There was a significant difference in carbon dioxide uptake rates among treatments, with the unmanipulated (Reference) areas having the highest uptake rates and an increase in CO2 uptake over time seen in the Low Elevation Runnel treatment. These findings highlight the potential use of a climate change adaptation strategy to combat sea level rise impacts and provide insights for future adaptation efforts
Evaluation of LAI Estimation of Mangrove Communities Using DLR and ELR Algorithms With UAV, Hyperspectral, and SAR Images
Get PDFThe high-precision estimation of mangrove leaf area index (LAI) using a deep learning regression algorithm (DLR) always requires a large amount of training sample data. However, it is difficult for LAI field measurements to collect a sufficient amount of sample data in mangrove wetlands. To tackle this challenge, this paper proposed an approach for expanding training samples and quantitatively evaluated the performance of estimating LAI for mangrove communities using Deep Neural Networks (DNN) and Transformer algorithms. This study also explored the effects of unmanned aerial vehicle (UAV) and Sentinel-2A multispectral, orbital hyper spectral (OHS), and GF-3 SAR images on LAI estimation of different mangrove communities. Finally, this paper evaluated the LAI estimation ability of mangrove communities using ensemble learning regression (ELR) and DLR algorithms. The results showed that: (1) the UAV images achieved the better LAI estimation of different mangrove communities (R2 = 0.5974–0.6186), and GF-3 SAR images were better for LAI estimation of Avicennia marina with high coverage (R2 = 0.567). The optimal spectral range for estimating LAI for mangroves in the optical images was between 650–680 nm. (2) The ELR model outperformed single base model, and produced the high-accuracy LAI estimation (R2 = 0.5266–0.713) for different mangrove communities. (3) The average accuracy (R2) of the ELR model was higher by 0.0019–0.149 than the DLR models, which demonstrated that the ELR model had a better capability (R2 = 0.5865–0.6416) in LAI estimation. The Transformer-based LAI estimation of A. marina (R2 = 0.6355) was better than the DNN model, while the DNN model produced higher accuracy for Kandelia candel (KC) (R2 = 0.5577). (4) With the increase in the expansion ratio of the training sample (10–50%), the LAI estimation accuracy (R2) of DNN and Transformer models for different mangrove communities increased by 0.1166–0.2037 and 0.1037–0.1644, respectively. Under the same estimation accuracy, the sample enhancement method in this paper could reduce the number of filed measurements by 20–40%
Saturated, Suffocated, and Salty: Human Legacies Produce Hot Spots of Nitrogen in Riparian Zones
No full textThe compounding effects of anthropogenic legacies for environmental pollution are significant, but not well understood. Here, we show that centennial-scale legacies of milldams and decadal-scale legacies of road salt salinization interact in unexpected ways to produce hot spots of nitrogen (N) in riparian zones. Riparian groundwater and stream water concentrations upstream of two mid-Atlantic (Pennsylvania and Delaware) milldams, 2.4 and 4 m tall, were sampled over a 2 year period. Clay and silt-rich legacy sediments with low hydraulic conductivity, stagnant and poorly mixed hydrologic conditions, and persistent hypoxia in riparian sediments upstream of milldams produced a unique biogeochemical gradient with nitrate removal via denitrification at the upland riparian edge and ammonium-N accumulation in near-stream sediments and groundwaters. Riparian groundwater ammonium-N concentrations upstream of the milldams ranged from 0.006 to 30.6 mgN L−1 while soil-bound values were 0.11–456 mg kg−1. We attribute the elevated ammonium concentrations to ammonification with suppression of nitrification and/or dissimilatory nitrate reduction to ammonium (DNRA). Sodium inputs to riparian groundwater (25–1,504 mg L−1) from road salts may further enhance DNRA and ammonium production and displace sorbed soil ammonium-N into groundwaters. This study suggests that legacies of milldams and road salts may undercut the N buffering capacity of riparian zones and need to be considered in riparian buffer assessments, watershed management plans, and dam removal decisions. Given the widespread existence of dams and other barriers and the ubiquitous use of road salt, the potential for this synergistic N pollution is significant