Diana Stralberg

Niches, models, and climate change: assessing the assumptions and uncertainties.

As the rate and magnitude of climate change accelerate, understanding the consequences becomes increasingly important. Species distribution models (SDMs) based on current ecological niche constraints are used to project future species distributions. These models contain assumptions that add to the uncertainty in model projections stemming from the structure of the models, the algorithms used to translate niche associations into distributional probabilities, the quality and quantity of data, and mismatches between the scales of modeling and data. We illustrate the application of SDMs using two climate models and two distributional algorithms, together with information on distributional shifts in vegetation types, to project fine-scale future distributions of 60 California landbird species. Most species are projected to decrease in distribution by 2070. Changes in total species richness vary over the state, with large losses of species in some “hotspots” of vulnerability. Differences in distributional shifts among species will change species co-occurrences, creating spatial variation in similarities between current and future assemblages. We use these analyses to consider how assumptions can be addressed and uncertainties reduced. SDMs can provide a useful way to incorporate future conditions into conservation and management practices and decisions, but the uncertainties of model projections must be balanced with the risks of taking the wrong actions or the costs of inaction. Doing this will require that the sources and magnitudes of uncertainty are documented, and that conservationists and resource managers be willing to act despite the uncertainties. The alternative, of ignoring the future, is not an option.

Evaluating Tidal Marsh Sustainability in the Face of Sea-Level Rise: A Hybrid Modeling Approach Applied to San Francisco Bay

Background Tidal marshes will be threatened by increasing rates of sea-level rise (SLR) over the next century. Managers seek guidance on whether existing and restored marshes will be resilient under a range of potential future conditions, and on prioritizing marsh restoration and conservation activities. Methodology Building upon established models, we developed a hybrid approach that involves a mechanistic treatment of marsh accretion dynamics and incorporates spatial variation at a scale relevant for conservation and restoration decision-making. We applied this model to San Francisco Bay, using best-available elevation data and estimates of sediment supply and organic matter accumulation developed for 15 Bay subregions. Accretion models were run over 100 years for 70 combinations of starting elevation, mineral sediment, organic matter, and SLR assumptions. Results were applied spatially to evaluate eight Bay-wide climate change scenarios. Principal Findings Model results indicated that under a high rate of SLR (1.65 m/century), short-term restoration of diked subtidal baylands to mid marsh elevations (−0.2 m MHHW) could be achieved over the next century with sediment concentrations greater than 200 mg/L. However, suspended sediment concentrations greater than 300 mg/L would be required for 100-year mid marsh sustainability (i.e., no elevation loss). Organic matter accumulation had minimal impacts on this threshold. Bay-wide projections of marsh habitat area varied substantially, depending primarily on SLR and sediment assumptions. Across all scenarios, however, the model projected a shift in the mix of intertidal habitats, with a loss of high marsh and gains in low marsh and mudflats. Conclusions/Significance Results suggest a bleak prognosis for long-term natural tidal marsh sustainability under a high-SLR scenario. To minimize marsh loss, we recommend conserving adjacent uplands for marsh migration, redistributing dredged sediment to raise elevations, and concentrating restoration efforts in sediment-rich areas. To assist land managers, we developed a web-based decision support tool (www.prbo.org/sfbayslr).

Modeling Tidal Marsh Distribution with Sea-Level Rise: Evaluating the Role of Vegetation, Sediment, and Upland Habitat in Marsh Resiliency

Tidal marshes maintain elevation relative to sea level through accumulation of mineral and organic matter, yet this dynamic accumulation feedback mechanism has not been modeled widely in the context of accelerated sea-level rise. Uncertainties exist about tidal marsh resiliency to accelerated sea-level rise, reduced sediment supply, reduced plant productivity under increased inundation, and limited upland habitat for marsh migration. We examined marsh resiliency under these uncertainties using the Marsh Equilibrium Model, a mechanistic, elevation-based soil cohort model, using a rich data set of plant productivity and physical properties from sites across the estuarine salinity gradient. Four tidal marshes were chosen along this gradient: two islands and two with adjacent uplands. Varying century sea-level rise (52, 100, 165, 180 cm) and suspended sediment concentrations (100%, 50%, and 25% of current concentrations), we simulated marsh accretion across vegetated elevations for 100 years, applying the results to high spatial resolution digital elevation models to quantify potential changes in marsh distributions. At low rates of sea-level rise and mid-high sediment concentrations, all marshes maintained vegetated elevations indicative of mid/high marsh habitat. With century sea-level rise at 100 and 165 cm, marshes shifted to low marsh elevations; mid/high marsh elevations were found only in former uplands. At the highest century sea-level rise and lowest sediment concentrations, the island marshes became dominated by mudflat elevations. Under the same sediment concentrations, low salinity brackish marshes containing highly productive vegetation had slower elevation loss compared to more saline sites with lower productivity. A similar trend was documented when comparing against a marsh accretion model that did not model vegetation feedbacks. Elevation predictions using the Marsh Equilibrium Model highlight the importance of including vegetation responses to sea-level rise. These results also emphasize the importance of adjacent uplands for long-term marsh survival and incorporating such areas in conservation planning efforts.

Calibrating indices of avian density from non-standardized survey data: making the most of a messy situation

Summary The analysis of large heterogeneous data sets of avian point-count surveys compiled across studies is hindered by a lack of analytical approaches that can deal with detectability and variation in survey protocols. We reformulated removal models of avian singing rates and distance sampling models of the effective detection radius (EDR) to control for the effects of survey protocol and temporal and environmental covariates on detection probabilities. We estimated singing rates and EDR for 75 boreal forest songbird species and found that survey protocol, especially point-count radius, explained most of the variation in detectability. However, environmental and temporal covariates (date, time, vegetation) affected singing rates and EDR for 73% and 59% of species, respectively. Unadjusted survey counts increased by an average of 201% from a 5-min, 50-m radius survey to a 10-min, 100-m radius survey (n = 75 species). This variability was decreased to 8·5% using detection probabilities estimated from a combination of removal and distance sampling models. Our modelling approach reduced computation when fitting complex models to large data sets and can be used with a wide range of statistical techniques for inference and prediction of avian densities.

Landscape influence on the quality of heron and egret colony sites

We evaluated landscape associations related to heron and egret colony site selection and the productivity of successful great blue heron (Ardea herodias) and great egret (Ardea alba) nests. The study was based on annual observations (1991–2005) at 45 colony sites known to be active within 10 km of historic tidal marshes of northern San Francisco Bay. The analyses focused on a priori models analyzed within 1, 3, 5, 7, and 10 km of colony sites, using the areal extents of several NOAA land cover types (Landsat images, 2000–2002), number of wetland patches, and total wetland edge as predictor variables. A comparison of landscape characteristics surrounding colony sites with those surrounding randomly selected, unoccupied sites revealed the primary importance of estuarine emergent wetland and open water within 1 km of colony sites. Increased productivity in successful great blue heron nests was associated with more estuarine emergent wetland, open water, and low-intensity development, and less grassland, but was not differentially related to the extent of habitat available within any particular distance from colony sites. The productivity in successful great egret nests was associated with variation in habitat extent at larger spatial scales, especially within 10 km of heronies, with nests producing more young at sites surrounded by more estuarine emergent wetland and low-intensity development, less open water and palustrine emergent wetland, and more patches of wetland habitat. To estimate landscape foraging patterns, we used aircraft to track the flights of great egrets departing from heronries and used the observed flight distances, colony sizes, and the regional distribution of wetland habitat to model regional foraging densities. Results suggested that increasing the extent of wetland feeding areas for herons and egrets might improve reproductive performance in colony sites up to 10 km away, increase foraging by herons and egrets in created or restored wetlands within 3–10 km of sites, and enhance nest abundance at colony sites within 1 km of restoration sites. Regional maps based on the distribution of colony-sites and predictions of landscape influences on colony site selection, nest productivity, and foraging dispersion, suggested areas potentially suitable for colonization.

Mapping changes in tidal wetland vegetation composition and pattern across a salinity gradient using high spatial resolution imagery

Detailed vegetation mapping of wetlands, both natural and restored, can offer valuable information about vegetation diversity and community structure and provides the means for examining vegetation change over time. We mapped vegetation at six tidal marshes (two natural, four restored) in the San Francisco Estuary, CA, USA, between 2003 and 2004 using detailed vegetation field surveys and high spatial-resolution color-infrared aerial photography. Vegetation classes were determined by performing hierarchical agglomerative clustering on the field data collected from each tidal marsh. Supervised classification of the CIR photography resulted in vegetation class mapping accuracies ranging from 70 to 92%; 10 out of 12 classification accuracies were above 80%, demonstrating the potential to map emergent wetland vegetation. The number of vegetation classes decreased with salinity, and increased with size and age. In general, landscape diversity, as measured by the Shannon’s diversity index, also decreased with salinity, with an exception for the most saline site, a newly restored marsh. Vegetation change between years is evident, but the differences across sites in composition and pattern were larger than change within sites over two growing seasons.

Identifying habitat conservation priorities and gaps for migratory shorebirds and waterfowl in California

Conservation of migratory shorebirds and waterfowl presents unique challenges due to extensive historic loss of wetland habitats, and current reliance on managed landscapes for wintering and migratory passage. We developed a spatially-explicit approach to estimate potential shorebird and waterfowl densities in California by integrating mapped habitat layers and statewide bird survey data with expert-based habitat rankings. Using these density estimates as inputs, we used the Marxan site-selection program to identify priority shorebird and waterfowl areas at the ecoregional level. We identified 3.7 million ha of habitat for shorebirds and waterfowl, of which 1.4 million ha would be required to conserve 50% of wintering populations. To achieve a conservation goal of 75%, more than twice as much habitat (3.1 million ha) would be necessary. Agricultural habitats comprised a substantial portion of priority areas, especially at the 75% level, suggesting that under current management conditions, large areas of agricultural land, much of it formerly wetland, are needed to provide the habitat availability and landscape connectivity required by shorebird and waterfowl populations. These habitats were found to be largely lacking recognized conservation status in California (96% un-conserved), with only slightly higher levels of conservation for priority shorebird and waterfowl areas. Freshwater habitats, including wetlands and ponds, were also found to have low levels of conservation (67% un-conserved), although priority shorebird and waterfowl areas had somewhat higher levels of conservation than the state as a whole. Conserving migratory waterfowl and shorebirds will require a diversity of conservation strategies executed at a variety of scales. Our modeled results are complementary with other approaches and can help prioritize areas for protection, restoration and other actions. Traditional habitat protection strategies such as conservation easements and fee acquisitions may be of limited utility for protecting and managing significant areas of agricultural lands. Instead, conservation strategies focused on incentive-based programs to support wildlife friendly management practices in agricultural settings may have greater utility and conservation effectiveness.

Modeling climate change impacts on tidal marsh birds: Restoration and conservation planning in the face of uncertainty

The large uncertainty surrounding the future effects of sea-level rise and other aspects of climate change on tidal marsh ecosystems exacerbates the difficulty in planning effective conservation and restoration actions. We addressed these difficulties in the context of large-scale wetland restoration activities underway in the San Francisco Estuary (Suisun, San Pablo and San Francisco Bays). We used a boosted regression tree approach to project the future distribution and abundance of five marsh bird species (through 2110) in response to changes in habitat availability and suitability as a result of projected sea-level rise, salinity, and sediment availability in the Estuary. To bracket the uncertainty, we considered four future scenarios based on two sediment availability scenarios (high or low), which varied regionally, and two rates of sea-level rise (0.52 or 1.65 m/100 yr). We evaluated three approaches for using model results to inform the selection of potential restoration projects: (1) Use current conditions only to prioritize restoration. (2) Use a single future scenario (among the four referred to above) in combination with current conditions to select priority restoration projects. (3) Combine current conditions with all four future scenarios, while incorporating uncertainty among future scenarios into the selection of restoration projects. We found that simply using current conditions resulted in the poorest performing restoration projects selected in terms of providing habitat for tidal marsh birds in light of possible future scenarios. The most robust method for selecting restoration projects, the “combined” strategy, used projections from all future scenarios with a discounting of areas with high levels of variability among future scenarios. We show that uncertainty about future conditions can be incorporated in site prioritization algorithms and should motivate the selection of adaptation measures that are robust to uncertain future conditions. These results and data have been made available via an interactive decision support tool at www.prbo.org/sfbayslr.

Scale-dependent complementarity of climatic velocity and environmental diversity for identifying priority areas for conservation under climate change

As most regions of the earth transition to altered climatic conditions, new methods are needed to identify refugia and other areas whose conservation would facilitate persistence of biodiversity under climate change. We compared several common approaches to conservation planning focused on climate resilience over a broad range of ecological settings across North America and evaluated how commonalities in the priority areas identified by different methods varied with regional context and spatial scale. Our results indicate that priority areas based on different environmental diversity metrics differed substantially from each other and from priorities based on spatiotemporal metrics such as climatic velocity. Refugia identified by diversity or velocity metrics were not strongly associated with the current protected area system, suggesting the need for additional conservation measures including protection of refugia. Despite the inherent uncertainties in predicting future climate, we found that variation among climatic velocities derived from different general circulation models and emissions pathways was less than the variation among the suite of environmental diversity metrics. To address uncertainty created by this variation, planners can combine priorities identified by alternative metrics at a single resolution and downweight areas of high variation between metrics. Alternately, coarse-resolution velocity metrics can be combined with fine-resolution diversity metrics in order to leverage the respective strengths of the two groups of metrics as tools for identification of potential macro- and microrefugia that in combination maximize both transient and long-term resilience to climate change. Planners should compare and integrate approaches that span a range of model complexity and spatial scale to match the range of ecological and physical processes influencing persistence of biodiversity and identify a conservation network resilient to threats operating at multiple scales.

Predicting Avian Abundance Within and Across Tidal Marshes Using Fine-Scale Vegetation and Geomorphic Metrics

Tidal marsh monitoring and restoration can benefit from the union of fine-scale remote sensing products and field-based survey data via spatial predictive models. As part of an interdisciplinary wetland monitoring project in San Francisco Bay, we developed a suite of 1-m pixel-level spatial metrics describing patterns in marsh vegetation and geomorphology for six sites across a large salinity gradient. These metrics, based on multi-spectral aerial imagery and derived vegetation maps, provided a basis for fine-scale spatial modeling of avian habitat potential. Using common yellowthroat (Geothlypis trichas), song sparrow (Melospiza melodia), and black rail (Laterallus jamaicensis) abundance data, we developed statistical models with relatively high explanatory power. In each case, models were improved by including vegetation-map variables, but variables directly extracted from aerial imagery were more reliable indicators of avian abundance. Although results varied by species, our models achieved reasonable within-site predictive success. When predicting to sites not used in the training set, however, validation results were inconsistent and often poor, suggesting that these models should be used with caution outside of the original study sites. As remotely sensed data become more readily available, our methods may be applied to a diverse range of sites, resulting in improved model generality and applicability.