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Plant diversity may enhance stability of ecosystem function and its satellite-derived indicators. However, its potential to stabilize phenology, or seasonal changes in plant function, is little understood, especially in understudied systems with high biodiversity potential such as wetlands. Using a large sample of U.S. wetlands and a new satellite-based indicator of phenological stability, we found that plant diversity was negatively associated with interannual phenological variability after controlling for covariates representing climate, site conditions, and spectral fluctuations. Furthermore, plant diversity and covariates better explained phenological variability than stability in annually summarized satellite-based biomass indicators used by earlier studies. Last, a subsequent path analysis indicated that phenological variability could mediate plant diversity relationship with the latter stability. Our results suggest that contributions of plant diversity to seasonality of ecosystems may have a stabilizing role in their functioning and offer a new basis for assessing biodiversity-stability relationships across broad geographic extents.

To monitor wetlands at regional scales, it is pivotal to identify metrics that show rapid and predictable responses to restoration interventions. Remote sensing can monitor such metrics at high frequency and low cost but remains underutilized in practice. This study sought to find a set of landscape metrics most responsive to restoration and vegetation dynamics across 11 years and 20 restored wetlands in the Sacramento-San Joaquin Delta of California, USA. Breakpoint analysis was used to detect phases in the development of vegetated pixels as estimated from the enhanced vegetation index (EVI) derived from Landsat (2004–2017). Landscape metrics were then generated from land cover classifications based on high resolution aerial images from the National Agricultural Inventory Program (NAIP). Using hierarchical clustering, we grouped phases showing similar temporal characteristics. We selected a subset of landscape metrics that best described the spatial structure of vegetation and its dynamics in each phase type. We identified four phases in vegetation development: (1A) rapid increase; (1B) decrease; (2A) low change; (2B) low change with fluctuations. Landscape metrics showed a significant response to vegetation dynamics in our sample, suggesting their potential to expand current monitoring practices at low cost. Young sites and sites experiencing a rapid increase in greenness were characterized by a lower density of small patches, while older sites, reference sites, and low variability sites were characterized by large, clustered patches. Our study demonstrates that open source remote sensing can detect patterns in wetland response to restoration and help identify factors promoting their recovery.

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.

Inundated wetlands can potentially sequester substantial amounts of soil carbon (C) over the long-term because of slow decomposition and high primary productivity, particularly in climates with long growing seasons. Restoring such wetlands may provide one of several effective negative emission technologies to remove atmospheric CO2 and mitigate climate change. However, there remains considerable uncertainty whether these heterogeneous ecotones are consistent net C sinks and to what degree restoration and management methods affect C sequestration. Since wetland C dynamics are largely driven by climate, it is difficult to draw comparisons across regions. With many restored wetlands having different functional outcomes, we need to better understand the importance of site-specific conditions and how they change over time. We report on 21 site-years of C fluxes using eddy covariance measurements from five restored fresh to brackish wetlands in a Mediterranean climate. The wetlands ranged from 3 to 23 years after restoration and showed that several factors related to restoration methods and site conditions altered the magnitude of C sequestration by affecting vegetation cover and structure. Vegetation established within two years of re-flooding but followed different trajectories depending on design aspects, such as bathymetry-determined water levels, planting methods, and soil nutrients. A minimum of 55% vegetation cover was needed to become a net C sink, which most wetlands achieved once vegetation was established. Established wetlands had a high C sequestration efficiency (i.e. the ratio of net to gross ecosystem productivity) comparable to upland ecosystems but varied between years undergoing boom-bust growth cycles and C uptake strength was susceptible to disturbance events. We highlight the large C sequestration potential of productive inundated marshes, aided by restoration design and management targeted to maximise vegetation extent and minimise disturbance. These findings have important implications for wetland restoration, policy, and management practitioners.

Significant wetland losses across the globe have motivated large-scale restoration efforts to improve the quality of wetland habitats. However, previous studies have shown a high variability in the outcomes of restoration treatments. Post-restoration monitoring is critical to identifying factors constraining wetland recovery and diverting sites away from restoration goals but is often limited by a lack of funding. To circumvent limitations to the large-scale monitoring of wetlands, it is pivotal to identify metrics that can be implemented at low cost yet provide a reliable signal of restoration progress. We review scientific literature on methods to appraise post-restoration progress in wetland ecosystems, focusing on vegetation-based indicators. We present a synthesis of demonstrated relationships between these indicators, site conditions, landscape context, and key ecosystem functions to highlight benefits and potential limitations to the widespread applications of these indicators to post-restoration monitoring. Based on this literature synthesis, we suggest adopting a multi-metric approach to fully measure ecosystem recovery. Potential solutions identified in this review to reduce costs associated with large-scale monitoring include: identifying correlation among indicators, focusing on the most widespread species, and using remote sensing to expand the spatiotemporal scope of monitoring and inform monitoring efforts.

The unprecedented global biodiversity loss has massive implications for the capacity of ecosystems to maintain functions critical to human well-being, urgently calling for rapid, scalable, and reproducible strategies for biodiversity monitoring, particularly in threatened ecosystems with difficult field access such as wetlands. Remote sensing indicators of spectral variability and greenness may predict the diversity of plant communities based on their optical diversity; however, most evidence is based on narrowband spectral data or terrestrial ecosystems. We investigate how spectral greenness and heterogeneity from publicly available broadband multi-spectral Landsat satellite imagery explain variation in vegetation diversity across different wetland types, ecoregions, and disturbance levels using 1,138 sites surveyed by U.S. EPA's National Wetland Condition Assessment. We found positive correlations of plant species richness and diversity with indicators of annual maximum spectral greenness and its spatial heterogeneity, explaining up to 43% variation within the global sample, 48% within wetland types or ecoregions, and up to 61% with abiotic covariates. The combined effect of spectral greenness and heterogeneity was stronger than the best-performing model using climatic, topographic, and edaphic factors alone. When compared among major U.S. watersheds and individual states, the fit of diversity-greenness models increased when more wetland types were included within the corresponding region's boundaries, up to 61% at the watershed and 77% at the state level, respectively, for diversity models and up to 73% and 80%, respectively, for richness models. Model outliers were characterized by a significantly greater diversity of nonnative species (P < 0.0001), suggesting that changes in model performance and greenness distributions could be used as indicators of shifts in plant community composition, particularly in tidal wetlands making the majority of outliers with significantly lower than predicted diversity. This study represents a first-time national-scale effort to use publicly available remote sensing, climatic, and topographic data to predict plant diversity in wetlands, which tend to be understudied compared to terrestrial ecosystems despite being among the most stressed ecosystems on Earth. Our study suggests that multi-temporal broadband satellite imagery could provide a low-cost assessment of regional and national wetland biodiversity for prioritization of conservation efforts and early detection of biodiversity loss.

https://doi.org/10.15447/sfews.2019v17iss2art2 Significant wetland losses and continuing threats to remnant habitats have motivated extensive restoration efforts in the San Francisco Bay–Delta estuary of California, the largest in the western United States. Consistent monitoring of ecological outcomes from this restoration effort would help managers learn from past projects to improve the design of future endeavors. However, budget constraints and challenging field conditions can limit the scope of current monitoring programs. Geospatial tools and remote sensing data sets could help complement field efforts for a low-cost, longer, and broader monitoring of wetland resources. To understand where geospatial tools could best complement current field monitoring practices, we reviewed the metrics and monitoring methods used by 42 wetland restoration projects implemented in the estuary. Monitoring strategies within our sample of monitoring plans relied predominantly on field surveys to assess key aspects of vegetation recovery while geospatial data sets were used sparingly. Drawing on recent publications that focus on the estuary and other wetland systems, we propose additional geospatial applications to help monitor the progress made toward site-specific and regional goals. These include the use of ecological niche models to target on-the-ground monitoring efforts, the up-scaling of field measurements into regional estimates using remote sensing data, and the analysis of time-series to detect ecosystem shifts. We discuss challenges and limitations to the broad-scale application of remote sensing data in wetland monitoring. These notably include the need to find a venue to store and share computationally intensive data sets, the often cumbersome pre-processing effort needed for long-term analyses, and multiple confounding factors that can obscure the signal of remote sensing data sets.

Seasonal phenological dynamics of vegetation hold important clues on ecosystem performance towards management goals, such as carbon uptake, and thus should be considered in projections of their targeted services. However, in wetlands spatio-temporal heterogeneity due to mixing of open water, soil, green and dead vegetation makes it difficult to generalize ecosystem functioning across different regions. Remote sensing observations can provide spatially-explicit, cost-effective phenology indicators; however, little is known about their capacity to indicate the links between wetland ecosystem structure and function. Here we assessed this potential by comparing one-year Enhanced Vegetation Index (EVI) from satellite products at high (5m; RapidEye) and low (30m; Landsat) spatial resolutions with eddy covariance time series of net carbon exchange, field digital camera (phenocam) greenness and water temperature among three floristically similar restored wetlands in California, USA. Phenological timing differed by wetland site: depending on satellite, the range in site-median start of greening was up to 28 days, end of greening – up to 73 days, start of senescence – up to 79 days, and end of senescence – up to 10 days. Key transition dates from satellite inputs agreed with seasonal changes in net carbon exchange, phenocam greenness and water temperatures, suggesting that phenological contrasts could result in part from site differences in vegetation configuration and litter affecting the exposure of canopy, soil and water to sunlight and thus sub-canopy microclimate and ecosystem functioning. Yet, the agreement between satellite inputs was non-systematic, with the greatest disparities at the more heterogeneous, less vegetated site. Phenological model fitting uncertainty increased with greater spatial resolution, highlighting the tradeoff between the accuracy of representing vegetation and the complexity of local seasonal variation. These findings highlight the sensitivity of satellite-derived phenology to structural and functional heterogeneity of ecosystems and call for more rigorous spatially-explicit analyses to inform assessments of restoration and management outcomes.

Leaf area index (LAI, one-sided leaf area per unit ground area) is an important parameter in models of canopy-atmosphere carbon exchange and greenhouse gas fluxes that has been disproportionately under-studied in wetland ecosystems. This study assessed variation in LAI and its sensitivity to canopy height, structure and remotely sensed normalized difference vegetation index (NDVI) in the California Delta, USA in July–August 2014. Plant area index (PAI), an optically measured LAI proxy, significantly varied among wetland sites and vegetation types (p

Land conversion and fragmentation threaten the resilience and biodiversity of wetland ecosystems which makes the future of their services to humans uncertain. Remote sensing can provide frequent and consistent data to facilitate wetland monitoring from regional to national scales and support their conservation and adaptive management. However, unique characteristics of wetlands, particularly land cover heterogeneity and background reflectance from soil, water and dead biomass, limit the efficacy of remote-sensing based metrics developed for terrestrial ecosystems. To identify the factors impacting satellite-based measurements of wetland greenness, we tested how six spectral vegetation indices responded to the land surface characteristics and regional climatic and edaphic context of 1,138 wetlands sites surveyed by the U.S EPA's National Wetland Condition Assessment. Spectral vegetation indices (SVIs) were estimated using all cloud-free surface reflectance data captured in 2011 by Landsat 5 TM and 7 ETM+. We tested two annually aggregated metrics —maximum and median greenness— for each SVI to facilitate the analysis of such a large dataset of satellite images. Using univariate and multivariate ordinary least square regression, we assessed how the annual maximum and median of each SVI responded to indicators of vegetation structure and composition, presence of dead biomass, open water, bare soil, and climatic/edaphic variables. Results show that, in the full national-scale dataset, the normalized difference vegetation index (NDVI) and the green normalized difference vegetation index (GNDVI) were most responsive to field-based metrics of vegetation structure and composition. However, the responses of SVIs differed significantly among wetland types, suggesting that their use should be tailored to the specific characteristics of the monitored wetlands. Annually aggregated metrics showed different sensitivity in multivariate models, with median greenness being more sensitive to structure and composition, but also to confounding site variables including litter, open water, and bare soil. This study represents a first-time effort to study relationships between the on-site properties of wetlands and their spectral characteristics at a national scale.

Invasive species are especially problematic when introduced into ecosystems with native congeners. The extent to which niches overlap in space determines whether the introduced species threatens the native one or the native species can escape competition or the effect of control. We compared the spatial distribution in relation to landscape and land-use/ land-cover variables of introduced and native Phragmites australis (common reed) in a landscape of protected freshwater wetlands in Quebec, Canada. Results showed that the wetlands still serve as refuges for native P. australis. At this stage of invasion, native and introduced P. australis occupy distinct spatial niches, the more abundant native type in low marsh and areas of lesser human impacts, the introduced one closer to roads and drier land covers. For now, native P. australis largely escapes competition, and the lack of spatial overlap could reduce opportunities for hybridization. Our study also suggests that invasion foci could still be ...