Geology topics

Kristin B. Byrd

Publications and source records attributed to Kristin B. Byrd.

At least 19 recordsLinked to original sources

USGS2026

Towards a refined definition of “tidal influence” for the coastal wetland sciences

The astronomical tide relates to lunar (and to a lesser extent solar) influences on rising and falling water bodies, and is a key control of many coastal processes. However, tides manifest along coastal margins in different ways to muddle application beyond Sir Isaac Newton’s first descriptions. Here, we argue that tide, or specifically “tidal,” has not been adequately defined for the coastal wetland sciences to facilitate contemporary interdisciplinary distinction for rapidly changing coastlines and future climate adaptation planning. We provide a brief history of the tidal concept, and we describe tides in a diversity of uncommonly recognized marginal coastal environments. Common astronomical tide manifestations are described through hydrographic examples, then expanded to include those tidal environments exposed additionally to fluvial, meteorological (wind), or groundwater influences. Our expanded definition of “tidal” is intended to be a forward-looking construct as environments will inevitably change with sea-level rise, water extraction, and anthropogenic flow alteration. Our definition of wetland tidal influence, which we broaden, includes those “wetlands affected by astronomic water level fluctuations within coastally restricted environments causing frequent or infrequent surface inundation or groundwater tidal variation that affects the biogeochemistry of the soil (e.g., ion exchange capacity, oxygen state, mineralization processes)”. Astronomic water level fluctuations are often amplified or dampened by non-astronomical events, such as wind. Expanding the definition of what is considered tidal by the scientific community is critical for improved understanding of coastal wetland function and the suite of ecosystem services they provide people and society, including climate mitigation opportunity, management, and adaptation.

Wetlands↗

USGS2026

Loss and transformation of coastal wetlands due to global change in the conterminous United States: Past, present, and future

Coastal wetlands are being transformed by global change, impacting the ecological and societal benefits provided by these ecosystems. Synthesizing knowledge of historical and expected future transformations in coastal wetlands can help inform forward-looking planning and stewardship efforts. Here, we review anticipated future ecological transformations in coastal wetlands of the conterminous United States and contrast them with past transformations. We examine trends at the national scale but focus in detail on the following six wetland-rich regions: (1) Everglades, (2) Mississippi River delta, (3) Chesapeake Bay, (4) San Francisco Estuary, (5) Puget Sound, and (6) Great Lakes. This review is among the first to integrate and compare coastal wetland transformations in the Great Lakes with their oceanic counterparts. Between 1850 and 1970, wetland losses across the nation were high because coastal wetlands were viewed as flooded wastelands needing to be drained, filled, or excavated to make room for other land uses. Over the last 50 years, growing public and scientific appreciation of the ecological and societal benefits provided by coastal wetlands has fostered tremendous gains in wetland restoration and legal protection. Looking to the future, climate change and accelerated sea-level rise have become critical threats to coastal wetlands and are emerging as major drivers of ecological loss and transformation. This review synthesizes regional knowledge regarding past, present, and future changes to help coastal scientists, environmental managers, and the public better anticipate and prepare for future coastal wetland transformations due to climate change, accelerated sea-level rise, land-use change, and other aspects of global change.

conterminous United States↗

USGS2025

RUSH: Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models

Coastal vegetated ecosystems, including tidal marshes, vegetated dunes, and shrub- and forest-dominated wetlands, can mitigate hurricane impacts such as coastal flooding and erosion by increasing surface roughness and reducing wave energy. Land cover maps can be used as input to improve simulations of surface roughness in advanced hydro-morphological models. Consequently, there is a need for efficient tools to develop up-to-date land cover maps that include the accurate distribution of vegetation types prior to an extreme storm. In response, we developed the RUSH tool (Rapid remote sensing Updates of land cover for Storm and Hurricane forecast models). RUSH delivers high-resolution maps of coastal vegetation for near-real-time or historical conditions via a Jupyter Notebook application and a graphical user interface (GUI). The application generates 3 m spatial resolution land cover maps with classes relevant to coastal settings, especially along mainland beaches, headlands, and barrier islands, as follows: (1) open water; (2) emergent wetlands; (3) dune grass; (4) woody wetlands; and (5) bare ground. These maps are developed by applying one of two seasonal random-forest machine learning models to Planet Labs SuperDove multispectral imagery. Cool Season and Warm Season Models were trained on 665 and 594 reference points, respectively, located across study regions in the North Carolina Outer Banks, the Mississippi Delta in Louisiana, and a portion of the Florida Gulf Coast near Apalachicola. Cool Season and Warm Season Models were tested with 666 and 595 independent points, with an overall accuracy of 93% and 94%, respectively. The Jupyter Notebook application provides users with a flexible platform for customization for advanced users, whereas the GUI, designed with user-experience feedback, provides non-experts access to remote sensing capabilities. This application can also be used for long-term coastal geomorphic and ecosystem change assessments.

Florida, Louisiana, North Carolina↗

USGS2025

Using imaging spectroscopy and elevation in machine learning to estimate soil salinity in intermittently tidal wetlands

Coastal soil salinization patterns are changing due to drought, sea level rise (SLR), and changing freshwater inflow. These changes are expected to impact coastal wetland plant health and ecosystem function, such as changes to biomass and productivity. These impacts have led to greater interest in how we monitor soil salinization across spatial and temporal scales. Remote sensing is a promising tool for estimating soil salinity at the spatial scales required for decision making by land managers. However, the development of a remote sensing estimation approach for wetland soil salinity must account for two factors: (1) the high spatial and temporal heterogeneity of coastal wetlands and (2) the fact that soil salinity is the result of multiple historical land use, hydrological, and geomorphic processes. In spring 2022, a combined airborne-field campaign, known as SHIFT, collected a weekly time series of airborne visible to shortwave infrared (VSWIR) image spectroscopy data. This dataset provides a unique opportunity to assess the application of fine spatial (5 m) and temporal (weekly) resolution VSWIR data to estimate root zone soil salinity; when combined with environmental variables such as elevation, these data can account for some of these factors. In this study, we utilized VSWIR and elevation datasets in a random forest regression to predict and map soil salinity in an intermittently tidal estuary, Devereux Slough, located in Santa Barbara County, California. The final model combined spectral indices with elevation to better capture soil salinity dynamics despite lower correlation ( r = 0.85) than solely using elevation ( r = 0.92). This research demonstrates the utility of remote sensing datasets, namely, elevation and the modified Anthocyanin Reflectance Index (mARI), for predicting root zone soil salinity in intermittently tidal coastal wetlands. These findings are an important step in advancing coastal remote sensing by creating a gridded salinity dataset that can be used for salinity monitoring and other coastal applications, such as modeling change in vegetation communities or ecosystems facing the impacts of climatic variability and change.

California↗

USGS2025

Multi-scale spectroscopy to map intertidal microbial biofilm community and trait diversity

Intertidal microbial biofilms, or microphytobenthos, support estuarine biogeochemical cycling, the physical stability of mudflats, and food webs, particularly those of migratory shorebirds. Photosynthetic biofilms dominated by diatoms, cyanobacteria, and chlorophytes represent a significant fraction of biofilm biomass and contain pigments that can be detected with remote sensing. These diverse biofilm community types vary in indicator pigments and functional traits related to biogeochemical cycling and nutritional quality. We modeled and mapped spatial variation in intertidal biofilm distribution, quantity, diversity, and functional traits using multi-scale spectroscopic data collected within southern San Francisco Bay, California, USA (South SFB). We developed a new biofilm index (B-index) from 5 mm HySpex spectra to detect biofilm presence. We developed single and multiple response partial least squares regression (PLS) models of chlorophyll -a (chl -a ; biomass indicator), indicator pigments: fucoxanthin and diadinoxanthin (diatoms), zeaxanthin (cyanobacteria), and chl -b (chlorophytes), and functional traits: carbohydrates, lipids, and total organic carbon from paired in situ biofilm data and field spectra. The B-index and PLS models were scaled to South SFB with a 3.7 m AVIRIS-NG hyperspectral image. The model %RMSE calculated from AVIRIS-NG test samples ranged from 12.7% for chl -a to 49% for chl -b ; for six of the eight models, %RMSE was 23% or below. Mapped community types differed in mapped traits, with average lipid concentrations three times higher in areas indicated as diatoms compared to other groups. Available maps depict for the first time the spatial variation of an important shorebird food resource and inform the contribution of intertidal biofilm in carbon and nutrient cycling.

California↗

USGS2025

Ecological thresholds and transformations due to climate change: The role of abiotic stress

An ecological threshold is the point at which a comparatively small environmental change triggers an abrupt and disproportionately large ecological response. In the face of accelerating climate change, there is concern that abrupt ecosystem transformations will become more widespread as critical ecological thresholds are crossed. There has been ongoing debate, however, regarding the prevalence of ecological thresholds across the natural world. While ecological thresholds are ubiquitous in some ecosystems, thresholds have been difficult to detect in others. Some studies have even concluded that threshold responses are uncommon in the natural world and overly emphasized in the ecological literature. As ecologists who work in ecosystems chronically exposed to high abiotic stress, we consider ecological thresholds and ecosystem transformations to be critical concepts that can greatly advance understanding of ecological responses to climate change and inform ecosystem management. But quantifying ecological thresholds can be challenging, if not impossible, without data that are strategically collected for that purpose. Here, we present a conceptual framework built upon linkages between abiotic stress, climate-driven ecological threshold responses, and the risk of ecosystem transformation. We also present a simple approach for quantifying ecological thresholds across abiotic stress gradients. We hypothesize that climate-driven threshold responses are especially influential in ecosystems chronically exposed to high abiotic stress, where autotroph diversity is low and foundation species play a prominent ecological role. Abiotic conditions in these environments are often near physiological tolerance limits of foundation species, which means that small abiotic changes can trigger landscape-level ecological transformations. Conversely, the alleviation of stress near thresholds can allow foundation species to thrive and spread into previously inhospitable locations. We provide examples of this climate-driven threshold behavior from four high-stress environments: coastal wetlands, coral reefs, drylands, and alpine ecosystems. Our overarching aim in this review is to clarify the strong relationships between abiotic stress, climate-driven ecological thresholds, and the risk of ecosystem transformation under climate change.

Ecosphere↗

USGS2025

Unlocking ecological insights from sub-seasonal visible-to-shortwave infrared imaging spectroscopy: The SHIFT campaign

We stand at the threshold of a transformative era in Earth observation, marked by space-borne visible-to-shortwave infrared (VSWIR) imaging spectrometers that promise consistent global observations of ecosystem function, phenology, and inter- and intra-annual change. However, the full value of repeat spectroscopy, the information embedded within different temporal scales, and the reliability of existing algorithms across diverse ecosystem types and vegetation phenophases have remained elusive due to the absence of suitable sub-seasonal spectroscopy data. In response, the Surface Biology and Geology (SBG) High-Frequency Time Series (SHIFT) campaign was initiated during late February 2022 in Santa Barbara County, California. SHIFT, designed to support NASA's SBG mission, addressed mission scoping, scientific advancement, applications development, and community building. This ambitious endeavor included weekly Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG) imagery acquisitions for 13 weeks (spanning February 24 to May 29, 2022), accompanied by coordinated terrestrial vegetation and coastal aquatic data collection. We describe the rich datasets collected and illustrate how the complex sub-seasonal patterns of change can be linked to biological science and applications, surpassing insights from multispectral observations. Leveraging open-source processing methods and cloud-based analysis tools, the SHIFT campaign showcases the readiness of the scientific community to harness ecological insights from remotely sensed hyperspectral time series. We provide an overview of SHIFT's goals, data collections, preliminary results, and the collaborative efforts of early career scientists committed to unlocking the transformative potential of high-frequency time series data from space-borne VSWIR imaging spectrometers.

Ecosphere↗

USGS2025

Land change, fire, and climate weaken carbon sink in the conterminous U.S.

The land carbon sink of the conterminous United States was evaluated using a bottom-up modeling framework and 30-meter land change data from 1985 to 2020. This cross-scale, cross-landscape, and cross-system approach tracked fractional land cover changes and applied regional model calibration. Results show average terrestrial and aquatic carbon sinks of +110 ± 37 and +19 ± 0.5 teragrams of carbon per year, respectively. The terrestrial carbon sink, showing no clear trend, peaked in the 1990s, with more years as a carbon source since 2000, contradicting recent national and global studies. Land change had the largest impact (−70 ± 5.5 teragrams of carbon per year), exceeding impacts of climate (−33 ± 48 teragrams of carbon per year), wildfire (−7.7 ± 2.4 teragrams of carbon per year), and erosion transport (−1.9 ± 0.13 teragrams of carbon per year). The positive CO2 fertilization effect (+69 ± 12 teragrams of carbon per year) was insufficient to maintain the carbon sink strength. Our framework reveals key paths of carbon loss, with implications for carbon budget and energy policies in the United States and beyond.

conterminous United States↗

USGS2024

Birdwatching preferences reveal synergies and tradeoffs among recreation, carbon, and fisheries ecosystem services in Pacific Northwest estuaries, USA

Coastal ecosystems provide multiple ecosystem services that are valued in diverse ways. The Nisqually River Delta (the Delta), an estuary in Puget Sound, Washington, U.S.A., is co-managed by the Nisqually Indian Tribe and the Billy Frank Jr. Nisqually National Wildlife Refuge. In an ecosystem services assessment, we used different service-appropriate methods including citizen science, statistical and geospatial models, and scenario analysis to evaluate three ecosystem services – recreational birdwatching, soil carbon accumulation and fishery production – indicated as priorities for the Refuge, Nisqually Indian Tribe, and surrounding communities. We developed a generalized additive mixed model set based on eBird mobile application birdwatching observations to understand the biological and landscape features that influence birdwatching and to project birdwatching visitation based on scenarios of Delta habitat change. We evaluated ecosystem service synergies and tradeoffs associated with habitat change for three coastal habitat types using scenario outputs from the birdwatching model and published results on Delta soil carbon accumulation and fishery production. The highest-ranked birdwatching models explained 88 % of the deviance and showed that visitation was greatest in winter months when distance to major cities was approximately 20 km. Recreational birdwatching increased with increasing area of forested wetland, emergent wetland, aquatic vegetation bed, open access, and total estuary. With increasing forested and emergent wetland area, recreational birdwatching, out-migrating juvenile Chinook salmon weight and soil carbon accumulation all increased. With increasing aquatic vegetation bed (resulting from sea level rise), recreational birdwatching increased, but salmon weight and soil carbon accumulation decreased. We identified practical ways in which ecosystem services may be incorporated into adaptive management frameworks that support climate adaptation decision making. This study illustrated how use of ecosystem services can help managers make decisions that have greater benefit for wildlife and people, communicate the societal value of decisions and increase local support and participation.

Washington↗

USGS2024

Current and future potential ecosystem services of the Nisqually River Delta: An assessment approach for Puget Sound estuaries and USFWS coastal refuges

The Nisqually River Delta, located in South Puget Sound, contains a rich mosaic of different coastal habitat types. The goal of this project was to quantify ecosystem services — benefits that wildlife or ecosystems provide to people — that are priorities for the Billy Frank Jr. Nisqually National Wildlife Refuge, the Nisqually Indian Tribe, and the surrounding communities. We modeled how change in these habitats from sea level rise (SLR) or management activities like restoration could affect ecosystem services in the future. We focused on changes to three main ecosystem services: soil carbon accumulation, birdwatching visitation, and juvenile Chinook salmon growth rates, which served as a proxy for fishery production. A habitat and carbon model projected that after 100 years, most high salt marsh would remain with < 1m SLR, but a substantial area would convert to low salt marsh and mudflat with ≥ 1m SLR. Total carbon accumulation would plateau or decline with ≥ 1m SLR, yet economic value of carbon accumulation would continue to rise over time, suggesting that the value of this ecosystem service is resilient to SLR. Birdwatching visitation was greatest in winter months and was positively related to area of forested wetland, emergent wetland, aquatic vegetation bed (e.g., eelgrass) and mudflat and open access (areas freely accessible to the public). Increases in forested wetland may lead to greater increases in visitation compared to other habitat types. All three ecosystem services increased with increases in forested wetland and emergent wetland, and tradeoffs among services occurred with increases in aquatic vegetation bed and mudflat. While both prey-rich salt marshes and eelgrass meadows facilitate salmon growth, loss of salt marsh led to declines in juvenile salmon weight. In conversation with USFWS managers, we identified practical ways to incorporate ecosystem services into adaptive management frameworks that support climate adaptation decision making. Our study illustrated how accounting for ecosystem services helps managers make decisions that greatly benefit wildlife and people, communicate the societal value of decisions, and increase local engagement and participation.

Washington↗

USGS2023

Nisqually River Delta—Humans and nature benefiting together

Introduction This is a brochure created in partnership with the U.S. Geological Survey (USGS), the Nisqually Indian Tribe, and the Billy Frank Jr. Nisqually National Wildlife Refuge. Designed for a public audience, the brochure describes the history of the Nisqually Indian Tribe, the ecology of the delta, the resources and recreational opportunities available for Refuge visitors, future challenges posed by climate change, and opportunities to protect wildlife and their habitats in the future.

Washington↗

USGS2023

Translating stakeholder narratives for participatory modeling in landscape ecology

Context Engaging stakeholders in research is needed for many of the sustainability challenges that landscape ecologists address. Involving stakeholders’ perspectives through narratives in participatory modeling fosters better understanding of the problem and evaluation of the acceptability of tradeoffs and creates buy-in for management actions. However, stakeholder-driven inputs often take the form of complex qualitative descriptions, rather than model-ready numerical or categorical inputs. Objectives Translating narratives into models, model parameters, or scenarios is essential for leveraging stakeholder knowledge and engagement. Drawing from varied experiences to identify lessons learned and pitfalls, we address the practice of translating narratives into models and using those narratives to interpret and communicate results. Methods We drew from seven participatory landscape ecology projects across North America to synthesize lessons for the inclusion of stakeholder narratives in modeling studies. Results We offer 8 lessons as practical guidance for other landscape ecologists to move the science beyond a unilateral focus on ecological systems and to maximize the benefits of landscape sustainability science. Conclusions These lessons are starting points, as real projects are complex, nuanced, and sometimes contradictory. Translating narratives into models is important for addressing complex sustainability challenges; we hope that these starting points are helpful to those foraying into this type of research.

Landscape Ecology↗

USGS2023

Capturing patterns of evolutionary relatedness with reflectance spectra to model and monitor biodiversity

Biogeographic history can set initial conditions for vegetation community assemblages that determine their climate responses at broad extents that land surface models attempt to forecast. Numerous studies have indicated that evolutionarily conserved biochemical, structural, and other functional attributes of plant species are captured in visible-to-short wavelength infrared, 400 to 2,500 nm, reflectance properties of vegetation. Here, we present a remotely sensed phylogenetic clustering and an evolutionary framework to accommodate spectra, distributions, and traits. Spectral properties evolutionarily conserved in plants provide the opportunity to spatially aggregate species into lineages (interpreted as “lineage functional types” or LFT) with improved classification accuracy. In this study, we use Airborne Visible/Infrared Imaging Spectrometer data from the 2013 Hyperspectral Infrared Imager campaign over the southern Sierra Nevada, California flight box, to investigate the potential for incorporating evolutionary thinking into landcover classification. We link the airborne hyperspectral data with vegetation plot data from 1372 surveys and a phylogeny representing 1,572 species. Despite temporal and spatial differences in our training data, we classified plant lineages with moderate reliability (Kappa = 0.76) and overall classification accuracy of 80.9%. We present an assessment of classification error and detail study limitations to facilitate future LFT development. This work demonstrates that lineage-based methods may be a promising way to leverage the new-generation high-resolution and high return-interval hyperspectral data planned for the forthcoming satellite missions with sparsely sampled existing ground-based ecological data.

Proceedings of the Natural Academy of Sciences↗

USGS2023

Above- and belowground biomass carbon stock and net primary productivity maps for tidal herbaceous marshes of the United States

Accurate assessments of greenhouse gas emissions and carbon sequestration in natural ecosystems are necessary to develop climate mitigation strategies. Regional and national-level assessments of carbon sequestration require high-resolution data to be available for large areas, increasing the need for remote sensing products that quantify carbon stocks and fluxes. The Intergovernmental Panel on Climate Change (IPCC) provides guidelines on how to quantify carbon flux using land cover land change and biomass carbon stock information. Net primary productivity (NPP), carbon uptake, and storage in vegetation, can also be used to model net carbon sequestration and net carbon export from an ecosystem (net ecosystem carbon balance). While biomass and NPP map products for terrestrial ecosystems are available, there are currently no conterminous United States (CONUS) biomass carbon stock or NPP maps for tidal herbaceous marshes. In this study, we used peak soil adjusted vegetation index (SAVI) values, derived from Landsat 8 composites, and five other vegetation indices, plus a categorical variable for the CONUS region (Pacific Northwest, California, Northeast, Mid-Atlantic, South Atlantic-Gulf, or Everglades), to model spatially explicit aboveground peak biomass stocks in tidal marshes (i.e., tidal palustrine and estuarine herbaceous marshes) for the first time. Tidal marsh carbon conversion factors, root-to-shoot ratios, and vegetation turnover rates, were compiled from the literature and used to convert peak aboveground biomass to peak total (above- and belowground) biomass and NPP. An extensive literature search for aboveground turnover rates produced sparse and variable values; therefore, we used an informed assumption of a turnover rate of one crop per year for all CONUS tidal marshes. Due to the lack of turnover rate data, the NPP map is identical to the peak biomass carbon stock map. In reality, it is probable that turnover rate varies by region, given seasonal length differences; however, the NPP map provides the best available information on spatially explicit CONUS tidal marsh NPP. This study identifies gaps in the scientific knowledge, to support future studies in addressing this lack of turnover data. Across CONUS, average total peak biomass carbon stock in tidal marshes was 848 g C m −2 (871 g C m −2 in palustrine and 838 g C m −2 in estuarine marshes), and based on a median biomass turnover rate of 1, it is expected that the mean NPP annual flux for tidal marshes is similar (e.g., 848 g C m −2 y −1 ). Peak biomass carbon stocks in tidal marshes were lowest in the Florida Everglades region and highest in the California regions. These are the first fine-scale national maps of biomass carbon and NPP for tidal wetlands, spanning all of CONUS. These estimates of CONUS total peak biomass carbon stocks and NPP rates for tidal marshes can support regional- and national-scale assessments of greenhouse gas emissions, as well as natural resource management of coastal wetlands, as part of nature-based climate solution efforts.

Remote Sensing↗

USGS2023

Variation in leaf reflectance spectra across the California flora partitioned by evolutionary history, geographic origin, and deep time

Evolutionary relatedness underlies patterns of functional diversity in the natural world. Hyperspectral remote sensing has the potential to detect these patterns in plants through inherited patterns of leaf reflectance spectra. We collected leaf reflectance data from across the California flora from plants grown in a common garden. Regions of the reflectance spectra vary in the depth and strength of phylogenetic signal. We also show that these differences are much greater than variation due to the geographic origin of the plant. At the phylogenetic extent of the California flora, spectral variation explained by the combination of ecotypic variation (divergent evolution) and convergent evolution of disparate lineages was minimal (3 to 7 %) but statistically significant. Interestingly, at the extent of a single genus ( Arctostaphylos ) no unique variation could be attributed to geographic origin. However, up to 18% of the spectral variation among Arctostaphylos individuals was shared between phylogeny and intraspecific variation stemming from ecotypic differences (i.e., geographic origin). Future studies could conduct more structured experiments (e.g., transplants or observations along environmental gradients) to disentangle these sources of variation and include other intraspecific variation (e.g., plasticity). We constrain broad scale spectral variability due to ecotypic sources, providing further support for the idea that phylogenetic clusters of species might be detectable through remote sensing. Phylogenetic clusters could represent a valuable dimension of biodiversity monitoring and detection.

California↗

USGS2023

Changes in habitat suitability for wintering dabbling ducks during dry conditions in the Central Valley of California

In arid and Mediterranean regions, landscape-scale wetland conservation requires understanding how wildlife responds to dynamic freshwater availability and conservation actions to enhance wetland habitat. Taking advantage of Landsat satellite data and structured and community science bird survey data, we built species distribution models to describe how three duck species, the Northern Pintail ( Anas acuta ), Green-winged Teal ( Anas crecca ), and Northern Shoveler ( Anas clypeata ), respond to freshwater supply and food resources on different flooded land cover types in the Central Valley of California. Specifically, our models compared duck habitat suitability between the wettest and driest conditions in each month from September through April. Using abundance-weighted boosted regression trees, we created three sets of species occurrence models based on different covariates: (1) near real-time (hereafter “real-time”) covariates in which duck observations were matched to the water availability within the 16-day window of a Landsat observation, (2) a combination of real-time covariates and waterfowl food resource covariates describing annual corn and rice biomass and managed wetland moist soil seed yield estimates derived from Landsat data, and (3) long-term average covariates—the most common approach to species distribution modeling—in which long-term average surface water availability was used. We modeled the monthly occurrence of three duck species as a function of surface water availability, land cover type, road density, temperature, and bird data source. We found that dry conditions result in reduced habitat suitability, with the biggest reductions in November through January and in agricultural fields; in contrast, suitability of flooded wetland habitat was relatively robust to surface water availability. When models of habitat suitability based on long-term average climate conditions were compared to models based on real-time conditions, the highest long-term suitability values occurred in areas where suitability was high regardless of whether it was a wet or a dry year. While all models performed well, the inclusion of crop and wetland plant yield covariates resulted in slightly higher model performance. Overall, species distribution models created using data on the environmental conditions present at the time of bird observations can aid conservation efforts under extreme conditions over large spatial scales.

California↗

USGS2023

Knowledge coproduction on the impact of decisions for waterbird habitat in a changing climate

Scientists, resource managers, and decision-makers increasingly use knowledge co-production to guide the stewardship of future landscapes under climate change. This process was applied in the California Central Valley, USA to solve complex conservation problems, where managed wetlands and croplands are flooded between fall and spring to support some of the largest concentrations of shorebirds and waterfowl in the world. We co-produced scenario narratives, spatially-explicit flooded waterbird habitat models, data products, and new knowledge about climate adaptation potential. We document our co-production process, and using the co-produced models, we ask: “when and where do management actions make a difference?” and “when does climate override these actions?” The outcomes of this process provide lessons learned on how to co-create usable information and how to increase climate adaptive capacity in a highly managed landscape. We found that: 1) actions to restore wetlands and prioritize their water supply create habitat outcomes resilient to climate change impacts particularly in March, when habitat is most limited, 2) land protection combined with management can increase the ecosystem's resilience to climate change, and 3) the uptake and use of this information was influenced by the roles of different stakeholders, plus rapidly changing water policies, discrepancies in decision-making time frames, and immediate crises of extreme drought. While a broad stakeholder group contributed knowledge to scenario narratives and model development, to co-produce usable information, data products were tailored to a small set of decision contexts, leading to fewer stakeholder participants over time. A boundary organization convened stakeholders across a large landscape, and early adopters helped to build legitimacy, yet broad-scale use of climate adaptation knowledge will depend on state and local policies, engagement with decision-makers that have legislative and budgetary authority, and the capacity to fit data products to specific decision needs.

California↗

USGS2022

Can coastal habitats rise to the challenge? Resilience of estuarine habitats, carbon accumulation, and economic value to sea-level rise in a Puget Sound estuary

Sea-level rise (SLR) and obstructions to sediment delivery pose challenges to the persistence of estuarine habitats and the ecosystem services they provide. Restoration actions and sediment management strategies may help mitigate such challenges by encouraging the vertical accretion of sediment in and horizontal migration of tidal forests and marshes. We used a process-based soil accretion model (Coastal Wetland Equilibrium Model) combined with a habitat classification model (MOSAICS) to estimate the effects of SLR, suspended sediment, and inland habitat migration on estuarine habitats, soil carbon accumulation, and economic value of climate change mitigation of carbon accumulation (social cost of carbon dioxide) in a macrotidal estuary in the northwest USA over 100 years (2011 to 2110). Under present-day sediment levels, we projected that after 100 years, most high salt marsh would remain with < 100 cm SLR, but substantial area converted to transitional (low) salt marsh and mudflat with ≥ 100 cm SLR. Increasing sediment availability increased the projected resilience of transitional salt marsh to SLR but did not prevent declines in high marsh area. Projected total carbon accumulation plateaued or declined with ≥ 100 cm SLR, yet the economic value of carbon accumulation continued to rise over time, suggesting that the value of this ecosystem service was resilient to SLR. Doubling or tripling sediment availability increased projected carbon accumulation up to 7.69 and 14.2 kg m −2 and increased total economic value up to $373,000 and $710,000, respectively. Allowing marsh migration supported conversion of upland to freshwater marsh, with slight increases in carbon accumulation. These results inform climate adaptation planning for wetland managers seeking to understand the resilience of estuarine habitats and ecosystem services to SLR under multiple management strategies.

Washington↗