Plant diversity safeguards wetland ecosystem functions, stability, and resilience, but is threatened by habitat loss and degradation. Remote sensing could support the cost-effective management of biodiversity by providing consistent and frequent data at large scales. While identifying individual species from remote sensing datasets with low spatial and spectral resolution is challenging, studies can focus on factors known to correlate with or promote diversity. We tested the predictive potential of such factors — maximum annual greenness as an indicator of productivity, texture (i.e., spatial arrangement of grey tones) as a proxy for habitat heterogeneity, and spatial autocorrelation — across a dataset of 1115 wetlands in the conterminous United States surveyed by the EPA's National Wetland Condition Assessment. We used multivariate linear regressions to test whether spectral and spatial metrics derived from two open-source datasets — NASA's Landsat 5 TM and 7 ETM+ (30 m, 16-day revisit) and USDA's National Agriculture Inventory Program (1 m, biennial) — can predict wetland plant diversity and richness. Individual texture metrics showed different sensitivity to vegetation evenness, growth form, and spatial distribution and could together predict 35–36% of site variation in richness and diversity. This highlights the impact of habitat heterogeneity on species diversity and spectral variability. While maximum annual greenness and texture metrics had similar predictive capacity, their interactions and combined effects improved the fit of linear models by 11–14%, demonstrating their complementarity. Best results were achieved when including distance-based Moran's Eigenvector Maps (dbMEMs) describing spatial relations among sites at multiple scales and reflecting the role of spatially structured factors (e.g., climate, topography, dispersal) on diversity. Together greenness, texture, and dbMEMs could predict 59% of plant richness and 50% of plant diversity across the entire dataset and up to 71% of the richness of least disturbed sites. These results show the potential of open-source remote sensing datasets to monitor biodiversity resources at a large scale and prioritize the protection and field monitoring of wetlands.

In the Sacramento–San Joaquin Delta (Delta), widespread drainage of historical wetlands has led to extensive subsidence and peat carbon losses, as well as high ongoing greenhouse gas (GHG) emissions. Large-scale wetland restoration and conversion to rice fields has the potential to mitigate these effects while conferring flood protection and creating habitat for wetland species. To explore the scale of these potential benefits, this study evaluated the effects of seven Delta-wide land-use scenarios on carbon stocks, land-surface elevation, GHG emissions, and habitat. Peat mapping and data from peat cores indicate that soil carbon stocks have decreased between the early 1800s and 2010s from 288 ± 15 to 145 ± 14 million metric tons (Mt) of carbon (C). If existing land uses continue, the Delta could lose an additional 8.3 Mt C during the coming 40 years, equal to average GHG emissions of 1.2 Mt CO2 equivalents (CO2e) yr-1. Future restoration and rice-farming scenarios indicate that wetland restoration could theoretically halt GHG emissions, converting the Delta from a large GHG source to a weak net source or sink. Across three future scenarios based on existing restoration targets, wetland creation and conversion to rice fields reduced GHG emissions by 0.39 to 0.67 Mt CO2e yr-1, with per-area benefits of 16 to 28 t CO2e per hectare (ha) yr-1. Differences among scenarios in extents of wetland types influenced their relative benefits for different management goals. Tidal restoration and conversion to rice fields enhanced habitat benefits and offered a source of agricultural income, but with reduced GHG mitigation compared with conversion to peat-building wetlands. This highlights the importance of clear objectives when developing land-use plans. A strategic land-management portfolio that includes rice fields and both impounded and tidal wetlands could be designed to provide GHG and subsidence mitigation while offering a diverse suite of benefits for ecosystems and people.