Pacific Science Center

Abstract Degradation of coral reefs over the past several decades has caused regional‐scale erosion of the shallow seafloor that serves as a protective barrier against coastal hazards along southeast Florida, USA. How future change in coral reefs may affect coastal flooding, however, has been less attended than other factors contributing to increasing risks such as sea‐level rise and more intense storms. Here, the increased flooding hazard faced by Florida's coastal communities from the projected future degradation of its adjacent coral reefs is evaluated through oceanographic, coastal engineering, habitat, geospatial, and socioeconomic modeling. Risk‐based valuation approaches were followed to map flood zones at 10‐m 2 resolution along 430 km of Florida's reef‐lined coast for the current and projected future coral reef conditions. The projected degradation of Florida's coral reefs can increase annual flooding to more than 8.77 km 2 of land and 4,980 km of roads, affecting more than 7,315 people, $412.5 million in damages to 1,400 buildings, and economic disruption of $438.1 million annually (2024 US dollars). The degradation of Florida's coral reefs would increase the annual risk to people and structures by more than 42% and 47%, respectively, but is spatially variable due to the heterogeneous alongshore nature and distribution of the reefs and communities: the increased risk exceeds $1 million/km annually to more than 17% of the coastline but also disproportionately would affect vulnerable populations. These results help identify areas where coral reef protection could help reduce the projected increased storm flooding risk to Florida's coastal communities.

<strong class="journal-contentHeaderColor">Abstract.</strong> Coastal areas, such as the Salish Sea, are becoming increasingly vulnerable to compound flooding due to the interaction between storm surge, tides, and river outflow. This hazard is anticipated to increase under sealevel rise and climate change. This research offers a high-resolution flood hazard mapping for King and Pierce Counties of Washington State (United States of America) using the SFINCS (Super-Fast INundation of CoastS) model to facilitate a Continuous Flood Response Modeling (CFRM) framework wherein decades of dynamic coastal and fluvial processes are simulated. By applying a cell-by-cell extreme value analysis, we predict flood areas for return periods of 1&ndash;100 years and compute the Expected Annual Flooded Area (EAFA) as a probability-weighted indicator of flood exposure. Model validation against National Oceanic and Atmospheric Administration (NOAA) and United States Geological Survey (USGS) gauge data demonstrates skill (RMSE: 14&ndash;17 cm for coastal water levels; unbiased RMSE: 49&ndash;116 cm for river water levels), and comparison with FEMA Special Flood Hazard Areas shows high spatial agreement of flooding (hit rates: 0.75&ndash;0.83). The timing statistics of the flooding reveal that the December 28, 2022, event was responsible for most historically observed flooding across the area. Climate simulations for today show EAFA ranges from 56 to 200 hectares in King County and from 250 to 644 hectares in Pierce County. Future projections show that sea level rise is the main contributor to increasing flood extent, whereas climate change drivers such as storm pattern change have little additional effect. We also identified a threshold around 100&ndash;150 cm of sea level rise at which the flood-exposed area increases substantially. Additionally, simplified deterministic flood maps can underestimate flood hazard by up to 0.5 m if not all relevant drivers are included. These results support the use of probabilistic, event-independent flood metrics such as EAFA to inform more rational and spatially responsive flood risk management.

Integration of agroecosystems and other working landscapes with protected lands and waters is critical to the conservation of Earth's biodiversity. Rice agroecosystems support many species by providing aquatic habitat where natural wetlands have been altered or drained. In regions with long dry seasons, rice fields and associated irrigation canals provide essential habitat for wetland‐dependent species. We quantified the spatial scale and magnitude of the effect of rice growing on the growth and survival of the giant gartersnake (Thamnophis gigas), a threatened species that persists primarily in areas of rice agriculture in the Central Valley of California, USA. We used structural causal models to identify drought condition as a key confounder to adjust for when estimating the total effect of rice growing on demographic rates. We analyzed capture‐mark‐recapture data from 19 populations of giant gartersnakes with an integrated growth–survival model and used distance‐weighted covariates to account for the decline in influence of rice with increasing distance from our study sites. We found strong support for a positive effect of rice grown within 1.9 km of a canal on giant gartersnake growth. There was also support for a positive effect of rice on giant gartersnake survival, although the spatial scale extended out to 5 km or more. Our results demonstrate how active rice growing benefits giant gartersnakes inhabiting irrigation canals and demonstrate an approach for studying landscape effects on wildlife in agroecosystems.

Estimating the distributions of cryptic species is essential for conservation, yet our understanding is hampered by animal behavior and imperfect detection. We developed and implemented a multiscale occupancy survey protocol to estimate the probability of occurrence, probability of being active on the surface, and detection probability of two range-restricted terrestrial salamanders, Scott Bar Salamanders (Plethodon asupak) and Siskiyou Mountains Salamanders (P. stormi), in interior northern California, USA. We established survey sites near locations of historical occurrence of these salamanders and surveyed each site on one to six visits in late fall 2023 and spring 2024. We compared models with different environmental variables for predicting salamander occurrence and surface activity. Much model selection uncertainty in the effects of covariates existed, but the model with most support indicated that Plethodon salamanders in interior northern California were more likely to occur at sites near recent historical occurrences that had longer growing seasons after controlling for elevation and aspect. Plethodon stormi or P. asupak surface activity was higher at night than during the day and was highest when substrates were cool and moist. Our survey protocol was successful for quantifying the effects of site and visit characteristics on P. stormi or P. asupak occurrence and availability; minor modifications will likely improve its utility for providing unbiased inference about salamander occurrence and surface activity.

Abstract Yes. Equilibrium shoreline models, which simulate wave‐driven cross‐shore erosion and accretion, are mathematically equivalent to a discrete convolution (i.e., a weighted, moving average) of a time series of wave‐forcing conditions with a parameterized memory‐decay kernel function. The direct equivalence between equilibrium shoreline models and convolutions reveals key theoretical aspects of equilibrium behavior. Convolutions (representing quasi‐low‐pass filter operations) provide an intuitive theoretical description of shoreline erosion and accretion behavior in response to waves: that is, shoreline position often mirrors the weighted moving average of wave time series. Model‐convolution equivalence also provides a conceptual basis to interpret, evaluate, and construct data‐driven Machine‐Learning/Deep‐Learning (ML/DL) models that use convolutions to extract features from data and then apply them for prediction (e.g., Convolutional Neural Networks (CNNs)). Finally, our findings provide a methodological pathway (based on Fourier transforms) for future understanding of wave‐driven shoreline change, which can be used to interpret the coherence between the frequency spectrum of the processes of waves and shoreline change and construct more computationally efficient and effective shoreline‐modeling approaches.

Cold-water coral (CWC) environments provide a suite of ecosystem and ecological services analogous to their tropical counterparts. They create complex habitats that serve as a home and nursery grounds for a variety of species and play key roles in carbon cycling and sequestration. CWC depend on the flux of photosynthetic production transported via rapid currents for energy and essential nutrients. However, temporal and spatial patterns in trophodynamics and energy flow within and among CWC ecosystems remain poorly known. Given predicted changes in the quality and quantity of surface production, as well as nutrient availability, CWC resilience to these changes will be related to their environmental niche, as well as functional diversity and redundancy. This study used stable isotopes and isotopic modeling to examine the interspecific patterns in CWC trophic niches and how those niches compare to associated species found in several CWC environments (400-1400m depth) throughout U.S. Atlantic and Gulf of Mexico regions. The isotopic composition of particulate organic matter was consistent with photosynthetically-derived organic matter, and the niche space overlapped among coral communities, indicative of isotopic stability in basal carbon sources. Different species of sympatric corals exhibited wide isotopic niches with differing degrees of overlap among species, indicating either species specific variability in food selection (carbon source) and/or variability in the isotope composition of baseline food resources over time. Co-located corals had lower isotopic values than suspension-feeding sponges, which may be a function of food resource use and roles of their microbiomes. Likewise, significant differences among feeding groups suggested spatial variability in the isotopic composition of nutritional inputs and/or variation in food selection. Comparisons of isotopic niches indicated overlap across regions, suggesting similarities in baseline food resources over space and time. Potential drivers of isotope niche space include variation in the seafloor complexity, inferred from measurements of slope, profile and plan curvature, that are linked to local hydrodynamics, nutrient flow, and food supply. Understanding key drivers of trophic complexity in CWCs and their associates help inform models predicting their occurrence, as well as distribution in the deep sea, given future climate scenarios.

Great Aleutian underthrusting earthquakes produced destructive tsunamis impacting Hawaiʻi in 1946 and 1957. Prior modeling of the 1957 tsunami deposit and runup records on eastern Aleutian and Hawaiian Islands jointly with tide-gauge observations across the Pacific Ocean constrained a rupture model with shallow slip up to 26 m along 600 km of the plate boundary. Here we implement this modeling approach to older deposits and show alternating deep and shallow megathrust slip up to 26, 32, and 22 m for great earthquakes along the same segment in the 18th, 15th, and 14th centuries. All three modeled prehistoric Aleutian earthquakes produce tsunami inundation in Hawaiʻi with the most severe, 14th century event having impacts exceeding the 1957 event. The along-dip variability of these four ruptures spanning seven centuries provides insights on earthquake cycles for engineering design and hazard assessment. The 15th century and 1957 rupture models provide evidence for recurrence of tsunami earthquakes, which can produce disproportionately large tsunamis for a given moment magnitude due to reduced rigidity in the shallow megathrust. The 14th and 18th century events likely ruptured deeper regions that did not slip in 1957, suggesting potential for corresponding deeper failure in the next great eastern Aleutian earthquake.