Geology topics

Joanna Grand

Publications and source records attributed to Joanna Grand.

4 recordsLinked to original sources

USGS2025

A simple predictive model for salt marsh internal deterioration under sea-level rise and sediment deficits: Application to Chesapeake Bay

Salt marshes are dynamic biogeomorphic systems reliant on autochthonous and allochthonous input to maintain their three-dimensional configuration. Sea-level rise, subsidence, and sediment deficits can lead to submergence, open-water expansion, and ultimately loss of the vegetated marsh plain and associated ecosystem services. Widely used management-focused models focus on vegetation zonation in response to sea level but neglect sediment transport processes and geomorphic change. Process-based research models attempt to represent complex physical and biogeomorphic interactions but operate on spatiotemporal scales that are not directly transferable to restoration or management. Here we bridge these two paradigms and present a novel geomorphic model (UBMorph) based on the sediment-based lifespan concept that accounts for sea-level rise and open-water expansion to predict changes in salt marsh area in Chesapeake Bay. Model parameters such as surface accretion rate and elevation-to-areal loss fraction are selected using a separate, fully coupled biogeomorphic model (MarshMorpho2D) and the predicted lifespan is then compared with high marsh coverage from a zonation model (SLAMM). Across all of Chesapeake Bay, UBMorph estimates an overall loss of 404 km 2 (37%) of vegetated marsh area under a dynamic 3–12 mm/y sea-level rise scenario (between 2010 and 2110). We then demonstrate a management-focused application of UBMorph and SLAMM used in tandem, for developing both a marsh condition and restoration model of the Chesapeake Bay portion of Maryland. The restoration model, which includes hydrologic intervention and sediment placement actions, indicates that ~ 400 km 2 of marsh require either no intervention or low effort hydrologic intervention presently, whereas if no action is taken, over 700 km 2 will require high effort intervention by 2070. This synthesis of research models with management-focused decision models demonstrates a tangible advance in bridging the gap between process-based research and restoration needs.

Maryland, Virginia↗

USGS2024

Avian communities respond to plant and landscape composition in actively revegetated floodplains of the Colorado River delta in Mexico

We examined the influence of local habitat factors such as plant community composition and species cover, and landscape habitat factors (e.g., land cover types) on the composition of the avian community in an arid-region large river delta (Colorado River). This 106 river km-long study area has experienced restoration through environmental water deliveries and active management of vegetation for ca. 10 years after decades of degradation. Variation partitioning and spatial models (Moran Eigenvector Maps) showed that plant communities and land cover combined explained 29.3% of the variability of 115 bird species, with a high overlap of 13.1% as vegetation and landscape factors were partially confounded and spatially correlated. Redundancy analyses showed that a higher cover of native riparian trees and shrubs and a larger amount of land covered by forests, typical characteristics of revegetated sites, favored bird species with affinity for riparian forests. Marshland and open water landscape features and high cover of macrophytes (which were common in the wettest river reach among the five included in the study), irrespective of active revegetation, were associated with a higher prevalence of wetland birds. Dominance by the non-native shrub Tamarix spp. and, especially, barren areas were detrimental to most bird species. The proportion of agricultural lands around the study sites was related to high abundance of generalists and some non-native species. Overall, our study showed that both local (vegetation) and landscape (land use) factors are important considerations for restoration of riparian bird communities.

Ecological Engineering↗

USGS2024

Strategic restoration planning for land birds in the Colorado River Delta, Mexico

Ecological restoration is an essential strategy for mitigating the current biodiversity crisis, yet restoration actions are costly. We used systematic conservation planning principles to design an approach that prioritizes restoration sites for birds and tested it in a riparian forest restoration program in the Colorado River Delta. Restoration goals were to maximize the abundance and diversity of 15 priority birds with a variety of habitat preferences. We built abundance models for priority birds based on the current landscape, and predicted bird distributions and relative abundances under a scenario of complete riparian forest restoration throughout our study area. Then, we used Zonation conservation planning software to rank this restored landscape based on core areas for all priority birds. The locations with the highest ranks represented the highest priorities for restoration and were located throughout the river reach. We optimized how much of the available landscape to restore by simulating restoration of the top 10–90% of ranked sites in 10% intervals. We found that total diversity was maximized when 40% of the landscape was restored, and mean relative abundance was maximized when 80% of the landscape was restored. The results suggest that complete restoration is not optimal for this community of priority birds and restoration of approximately 60% of the landscape would provide a balance between maximum relative abundance and diversity. Subsequent planning efforts will combine our results with an assessment of restoration costs to provide further decision support for the restoration-siting process. Our approach can be applied to any landscape-scale restoration program to improve the return on investment of limited economic resources for restoration.

Colorado River Delta↗

USGS2022

Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter datasets versus pseudo-absence locations during migratory periods, and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and post-breeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations, when compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings, and thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach for integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Ecological Applications↗