The natural capital of seagrass beds in the Caribbean: evaluating their ecosystem services and blue carbon trade potential.

Seagrass beds provide tremendous services to society, including the storage of carbon, with important implications for climate change mitigation. Prioritizing conservation of this valuable natural capital is of global significance, and including seagrass beds in global carbon markets through projects that minimize loss, increase area or restore degraded areas represents a mechanism towards this end. Using newly available Caribbean seagrass distribution data, we estimated carbon storage in the region and calculated economic valuations of total ecosystem services and carbon storage. We estimated the 88 170 km2 of seagrass in the Caribbean stores 1337.8 (360.5-2335.0, minimum and maximum estimates, respectively) Tg carbon. The value of these seagrass ecosystems in terms of total ecosystem services and carbon alone was estimated to be $255 billion yr-1 and $88.3 billion, respectively, highlighting their potential monetary importance for the region. Our results show that Caribbean seagrass beds are globally substantial pools of carbon, and our findings underscore the importance of such evaluation schemes to promote urgently needed conservation of these highly threatened and globally important ecosystems.

Mechanistic support for increased primary production around artificial reefs.

Understanding factors controlling primary production is fundamental for the protection, management, and restoration of ecosystems. Tropical seagrass ecosystems are among the most productive ecosystems worldwide, yielding tremendous services for society. Yet they are also among the most impaired from anthropogenic stressors, prompting calls for ecosystem-based restoration approaches. Artificial reefs (ARs) are commonly applied in coastal marine ecosystems to rebuild failing fisheries and have recently gained attention for their potential to promote carbon sequestration. Nutrient hotspots formed via excretion from aggregating fishes have been empirically shown to enhance local primary production around ARs in seagrass systems. Yet, if and how increased local production affects primary production at ecosystem scale remains unclear, and empirical tests are challenging. We used a spatially explicit individual-based simulation model that combined a data-rich single-nutrient primary production model for seagrass and bioenergetics models for fish to test how aggregating fish on ARs affect seagrass primary production at patch and ecosystem scales. Specifically, we tested how the aggregation of fish alters (i) ecosystem seagrass primary production at varying fish densities and levels of ambient nutrient availability and (ii) the spatial distribution of seagrass primary production. Comparing model ecosystems with equivalent nutrient levels, we found that when fish aggregate around ARs, ecosystem-scale primary production is enhanced synergistically. This synergistic increase in production was caused by nonlinear dynamics associated with nutrient uptake and biomass allocation that enhances aboveground primary production more than belowground production. Seagrass production increased near the AR and decreased in areas away from the AR, despite marginal reductions in seagrass biomass at the ecosystem level. Our simulation's findings that ARs can increase ecosystem production provide novel support for ARs in seagrass ecosystems as an effective means to promote (i) fishery restoration (increased primary production can increase energy input to the food web) and (ii) carbon sequestration, via higher rates of primary production. Although our model represents a simplified, closed seagrass system without complex trophic interactions, it nonetheless provides an important first step in quantifying ecosystem-level implications of ARs as a tool for ecological restoration.

Alternative Quantifications of Landscape Complementation to Model Gene Flow in Banded Longhorn Beetles [Typocerus v. velutinus (Olivier)].

Rapid progression of human socio-economic activities has altered the structure and function of natural landscapes. Species that rely on multiple, complementary habitat types (i.e., landscape complementation) to complete their life cycle may be especially at risk. However, such landscape complementation has received little attention in the context of landscape connectivity modeling. A previous study on flower longhorn beetles (Cerambycidae: Lepturinae) integrated landscape complementation into a continuous habitat suitability 'surface', which was then used to quantify landscape connectivity between pairs of sampling sites using gradient-surface metrics. This connectivity model was validated with molecular genetic data collected for the banded longhorn beetle (Typocerus v. velutinus) in Indiana, United States. However, this approach has not been compared to alternative models in a landscape genetics context. Here, we used a discrete land use/land cover map to calculate landscape metrics related to landscape complementation based on a patch mosaic model (PMM) as an alternative to the previously published, continuous habitat suitability model (HSM). We evaluated the HSM surface with gradient surface metrics (GSM) and with two resistance-based models (RBM) based on least cost path (LCP) and commute distance (CD), in addition to an isolation-by-distance (IBD) model based on Euclidean distance. We compared the ability of these competing models of connectivity to explain pairwise genetic distances (R ST) previously calculated from ten microsatellite genotypes of 454 beetles collected from 17 sites across Indiana, United States. Model selection with maximum likelihood population effects (MLPE) models found that GSM were most effective at explaining pairwise genetic distances as a proxy for gene flow across the landscape, followed by the landscape metrics calculated from the PMM, whereas the LCP model performed worse than both the CD and the isolation by distance model. We argue that the analysis of a continuous HSM with GSM might perform better because of their combined ability to effectively represent and quantify the continuous degree of landscape complementation (i.e., availability of complementary habitats in vicinity) found at and in-between sites, on which these beetles depend. Our findings may inform future studies that seek to model habitat connectivity in complex heterogeneous landscapes as natural habitats continue to become more fragmented in the Anthropocene.