Anthropogenic pressures and life history predict trajectories of seagrass meadow extent at a global scale

Seagrass meadows are threatened by multiple pressures, jeopardizing the many benefits they provide to humanity and biodiversity, including climate regulation and food provision through fisheries production. Conservation of seagrass requires identification of the main pressures contributing to loss and the regions most at risk of ongoing loss. Here, we model trajectories of seagrass change at the global scale and show they are related to multiple anthropogenic pressures but that trajectories vary widely with seagrass life-history strategies. Rapidly declining trajectories of seagrass meadow extent (>25% loss from 2000 to 2010) were most strongly associated with high pressures from destructive demersal fishing and poor water quality. Conversely, seagrass meadow extent was more likely to be increasing when these two pressures were low. Meadows dominated by seagrasses with persistent life-history strategies tended to have slowly changing or stable trajectories, while those with opportunistic species were more variable, with a higher probability of either rapidly declining or rapidly increasing. Global predictions of regions most at risk for decline show high-risk areas in Europe, North America, Japan, and southeast Asia, including places where comprehensive long-term monitoring data are lacking. Our results highlight where seagrass loss may be occurring unnoticed and where urgent conservation interventions are required to reverse loss and sustain their essential services

Interactive effects of multiple stressors vary with consumer interactions, stressor dynamics and magnitude

Predicting the impacts of multiple stressors is important for informing ecosystem management but is impeded by a lack of a general framework for predicting whether stressors interact synergistically, additively or antagonistically. Here, we use process-based models to study how interactions generalise across three levels of biological organisation (physiological, population and consumer-resource) for a two-stressor experiment on a seagrass model system. We found that the same underlying processes could result in synergistic, additive or antagonistic interactions, with interaction type depending on initial conditions, experiment duration, stressor dynamics and consumer presence. Our results help explain why meta-analyses of multiple stressor experimental results have struggled to identify predictors of consistently non-additive interactions in the natural environment. Experiments run over extended temporal scales, with treatments across gradients of stressor magnitude, are needed to identify the processes that underpin how stressors interact and provide useful predictions to management

Opportunities for improving recognition of coastal wetlands in global ecosystem assessment frameworks

Vegetated coastal wetlands, including seagrass, saltmarsh and mangroves, are threatened globally, yet the need to avert these losses is poorly recognized in international policy, such as in the Convention on Biological Diversity and the United Nations (UN) Sustainable Development Goals. Identifying the impact of overlooking coastal wetlands in ecosystem assessment frameworks could help prioritize research efforts to fill these gaps. Here, we examine gaps in the recognition of coastal wetlands in globally applicable ecosystem assessments. We address both shortfalls in assessment frameworks when it comes to assessing wetlands, and gaps in data that limit widespread application of assessments. We examine five assessment frameworks that track fisheries, greenhouse gas emissions, ecosystem threats, and ecosystem services. We found that these assessments inform management decisions, but that the functions provided by coastal wetlands are incompletely represented. Most frameworks had sufficient complexity to measure wetland status, but limitations in data meant they were incompletely informed about wetland functions and services. Incomplete representation of coastal wetlands may lead to them being overlooked by research and management. Improving the coverage of coastal wetlands in ecosystem assessments requires improving global scale mapping of wetland trends, developing global-scale indicators of wetland function and synthesis to quantitatively link animal population dynamics to wetland trends. Filling these gaps will help ensure coastal wetland conservation is properly informed to manage them for the outstanding benefits they bring humanity

Global typologies of coastal wetland status to inform conservation and management

Global-scale conservation initiatives and policy instruments rely on ecosystem indicators to track progress towards targets and objectives. A deeper understanding of indicator interrelationships would benefit these efforts and help characterize ecosystem status. We study interrelationships among 34 indicators for mangroves, saltmarsh, and seagrass ecosystems, and develop data-driven, spatially explicit typologies of coastal wetland status at a global scale. After accounting for environmental covariates and gap-filling missing data, we obtained two levels of clustering at 5 and 18 typologies, providing outputs at different scales for different end users. We generated 2,845 cells (1° (lat) × 1° (long)) globally, of which 29.7% were characterized by high land- and marine-based impacts and a high proportion of threatened species, 13.5% by high climate-based impacts, and 9.6% were refuges with lower impacts, high fish density and a low proportion of threatened species. We identify instances where specific actions could have positive outcomes for coastal wetlands across regions facing similar issues. For example, land- and marine-based threats to coastal wetlands were associated with ecological structure and function indicators, suggesting that reducing these threats may reduce habitat degradation and threats to species persistence. However, several interdimensional relationships might be affected by temporal or spatial mismatches in data. Weak relationships mean that global biodiversity maps that categorize areas by single indicators (such as threats or trends in habitat size) may not be representative of changes in other indicators (e.g., ecosystem function). By simplifying the complex global mosaic of coastal wetland status and identifying regions with similar issues that could benefit from knowledge exchange across national boundaries, we help set the scene for globally and regionally coordinated conservation

Carbon and Nitrogen Sequestration of Melaleuca Floodplain Wetlands in Tropical Australia

Wetlands of Melaleuca spp. in Australia form large forests that are highly threatened by deforestation and degradation. In America, Melaleuca has invaded large areas of native wetlands causing extensive damage. Despite their status as an endangered native ecosystem and as a highly invasive one, little is known about their C and N dynamics. In this study, we sampled five Melaleuca wetlands and measured their C and N ecosystem stocks (aboveground biomass and soil), tree accumulation rates, sedimentation rates, and soil stability. Melaleuca wetlands were highly heterogeneous, but most have large ecosystem C [mean ± SE (range); 360 ± 100 (80-670) Mg C ha−1] and N [8100 ± 1900 (1600-13,000) kg N ha−1] stocks. Tree accumulation rates were 5.0 ± 2.1 Mg C y−1 and 26 ± 14 kg N y−1, and surface soil accumulation rates were 0.6 ± 0.2 Mg C ha−1 y−1 and 39 ± 1 kg N y−1. We found evidence of long-term C and N accumulation in the soil, but also of some level of organic decomposition. Overall, we found that Melaleuca wetlands store and accumulate large amounts of C, especially in their trees, and large amounts of N in their soils, suggesting an important role in coastal biogeochemical cycles

Nitrogen removal by tropical floodplain wetlands through denitrification

Excess nitrogen (N) leading to the eutrophication of water and impacts on ecosystems is a serious environmental challenge. Wetlands can remove significant amounts of N from the water, primarily through the process of denitrification. Most of our knowledge on wetland denitrification is from temperate climates; studies in natural tropical wetlands are very scarce. We measured denitrification rates during a dry and a wet season in five floodplain forests dominated by Melaleuca spp., a coastal freshwater wetland of tropical Australia. We hypothesised that the denitrification potential of these wetlands would be high throughout the year and would be limited by N and carbon (C) availability. Mean potential denitrification rates (Dt) were 5.0 ± 1.7 mg m2 h–1, and were within the reported ranges for other tropical and temperate wetlands. The rates of Dt were similar between the dry and the wet seasons. From the total unamended denitrification rates (Dw, 3.1 ± 1.7 mg m2 h–1), 64% was derived from NO3– of the water column and the rest from coupled nitrification–denitrification. The factor most closely associated with denitrification was background water NO3–-N concentrations. Improved management and protection of wetlands could play an important role in improving water quality in tropical catchments

Remote estimation of aquatic light environments using machine learning: a new management tool for submerged aquatic vegetation

Submerged aquatic vegetation (SAV; e.g. seagrasses, macroalgae), forms key habitats in shallow coastal systems that provide a plethora of ecosystem services, including coastal protection, climate mitigation and supporting fisheries production. Light limitation is a critical factor influencing the growth and survival of SAV, thus it is important to understand how much light SAV needs, and receives, to effectively assess the risk that light limitation poses. Light monitoring is commonly used to inform environmental decision making to minimise loss of SAV habitat, but the temporal and spatial extent of monitoring is often limited by cost and logistical difficulties. An ability to remotely estimate light across different locations can therefore improve the conservation and management of SAV habitats. Here we combine an extensive monitoring program with publicly available data and machine learning to develop a model that estimates the light reaching submerged seagrasses in a shallow subtropical embayment in southern Queensland, Australia. Our model accurately predicts the intensity of photosynthetically active radiation (PAR) reaching the canopy of SAV from entirely remotely available data. The best performing model predicted light intensity with >99% at the management relevant daily, and 14-day rolling average time resolutions. This model enables monitoring of light available to SAV without an ongoing need for in-water instruments, minimising cost and risk to personnel, and improving assessment speed. The technique can be applied to SAV management plans in shallow waters throughout the world, where suitable remote public data is available

Country-wide analysis of large wood as a driver of fish abundance in Swedish streams: Which species benefit and where?

1. Rivers are heavily affected by anthropogenic impacts that threaten many fish species. Among restoration measures, the addition of large wood (LW) in streams has been showed to increase fish abundance. However, what species benefit from LW, to what extent relative to other drivers, and what factors influence LW quantity is not clear, which limits our ability to use LW as an effective restoration measure. 2. Here, time series (from 1993 to 2016) of electrofishing data including 3641 streams across Sweden were used to investigate 1) beneficial effects of LW on the abundance of juvenile brown trout Salmo trutta, juvenile Atlantic salmon S. salar, and juvenile and adult sculpins Cottus gobio and C. poecilopus, while accounting for other abiotic and biotic factors, and 2) the drivers of LW abundance at country-wide scale. 3. LW benefitted brown trout, and the effects were larger with decreasing shaded stream surface. LW effects were comparable in magnitude to the positive effects of average annual air temperature and the negative effects of stream depth and predator abundance, factors whose influence was second only to the negative effects of stream width. LW did not benefit salmon abundance, which correlated positively with stream width and negatively with altitude, nor did it benefit sculpin abundances, which mainly decreased with annual average air temperature and altitude. 4. The quantity of LW strongly diminished with stream width, and, to a lesser extent, with stream depth, altitude, annual average air temperature and forest age, while it increased with stream velocity, slope and forest cover. 5. The results suggest that LW can be used as an effective restoration tool for brown trout in shallow and narrow streams, especially in areas with little shade. Here, the addition of large wood could help alleviate the impacts of forest clearance and climate change