Department of Ecology and Evolutionary Biology

Fucus distichus, a rockweed common to the mid-intertidal shoreline within the San Francisco Estuary (previously known as F. gardneri), was injured during the Cosco Busan oil spill in November 2007 and subsequent clean-up actions. Restoration planning activities are underway to help recover F. distichus at sites within central San Francisco Bay where damage occurred. As a first step, we conducted shoreline surveys during the summers of 2012–2013 to map the occurrence of this rockweed. Of the 151.73 km of rocky shoreline within the central bay, F. distichus covered 32.16 km of shoreline. The alga generally occurred in narrow bands but formed expansive beds at locations with natural, flat bedrock benches. We also observed F. distichus on artificial substrata such as seawalls and riprap, but not on pilings. Samples of F. distichus from 11 sites throughout the central / east San Francisco Bay were genetically analyzed (microsatellite genotyping). The populations analyzed (1) had low genetic diversity, (2) the frequency of homozygotes was higher than expected (suggesting high inbreeding), and (3) also displayed geographic population structure, in part driven by very small differences in the midst of extremely low within-population genetic diversity. However, these genetic data do not raise concerns for restoration methods in terms of choosing donor populations and mixing F. distichus from different sites within the central bay. The choice of donor populations should be based on practical criteria for effective restoration; individuals will nonetheless be taken from locations as nearby to donor sites as possible. Various locations throughout the central San Francisco Bay are composed of cobble or small riprap that are populated with F. distichus, which could provide efficient means of translocating rockweed for future restoration activities.

In the spatial management of marine resources, there are a variety of contexts in which it is valuable to estimate local, site-specific demographic rates, particularly harvest rates. For example, in the case of no-take marine reserves, estimating the fishing mortality rate (F) prior to reserve implementation can inform quantitative expectations for increases in the abundance of protected populations in the reserve. Additionally, estimating F after implementation could be used to detect poaching. Often the data available for these estimates are length-abundance survey data, such as from visual diver or camera surveys. One can estimate F by fitting models to population size-structure data; understanding how the accuracy of such estimates depends on sampling effort and fish life history can inform monitoring approaches. Here, we quantified the capacity of a state-space integral projection model (SS-IPM) to estimate local F, and how that depends on life history, the true value of F, and monitoring sampling design. We found that estimates of F were (a) more accurate for species with lower natural mortality rates and (b) less precise for higher values of F. Yet, with enough sampling effort, estimates of F were generally within 10% of the true value. In general, estimating local F reliably requires sampling ≥ 100 fish each year over at least 12–15 years. We used empirical data from California to illustrate these general results, which could inform adaptive management plans for other marine reserves globally.

Polyergus kidnapper ants are widely distributed, but relatively uncommon, throughout the Holarctic, spanning an elevational range from sea level to over 3,000 m. These species are well known for their obligate social parasitism with various Formica ant species, which they kidnap in dramatic, highly coordinated raids. Kidnapped Formica larvae and pupae become integrated into the Polyergus colony where they develop into adults and perform nearly all of the necessary colony tasks for the benefit of their captors. In California, Polyergus mexicanus is the most widely distributed Polyergus, but recent evidence has identified substantial genetic polymorphism within this species, including genetically divergent lineages associated with the use of different Formica host species. Given its unique behavior and genetic diversity, P. mexicanus plays a critical role in maintaining ecosystem balance by influencing the population dynamics and genetic diversity of its host ant species, Formica, highlighting its conservation value and importance in the context of biodiversity preservation. Here, we present a high-quality genome assembly of P. mexicanus from a sample collected in Plumas County, CA, United States, in the foothills of the central Sierra Nevada. This genome assembly consists of 364 scaffolds spanning 252.31 Mb, with contig N50 of 481,250 kb, scaffold N50 of 10.36 Mb, and Benchmarking Universal Single-Copy Orthologs (BUSCO) completeness of 95.4%. We also assembled the genome of the Wolbachia endosymbiont of P. mexicanus-a single, circular contig spanning 1.23 Mb. These genome sequences provide essential resources for future studies of conservation genetics, population genetics, speciation, and behavioral ecology in this charismatic social insect.

Despite substantial reductions in the cost of sequencing over the last decade, genetic panels remain relevant due to their cost-effectiveness and flexibility across a variety of sample types. In particular, single nucleotide polymorphism (SNP) panels are increasingly favoured for conservation applications. SNP panels are often used because of their adaptability, effectiveness with low-quality samples, and cost-efficiency for population monitoring and forensics. However, the selection of diagnostic SNPs for population assignment and individual identification can be challenging. The consequences of poor SNP selection are under-powered panels, inaccurate results, and monetary loss. Here, we develop a novel and user-friendly SNP selection pipeline (mPCRselect) that can be used to select SNPs for population assignment and/or individual identification. mPCRselect allows any researcher, who has sufficient SNP-level data, to design a successful and cost-effective SNP panel for a diploid species of conservation concern.

Large-scale marine protected areas (LSMPAs; > 1000 km2) provide important refuge for large mobile species, but most do not encompass species ranges. To better understand current and future LSMPA value, we concurrently tracked nine species (seabirds, cetaceans, pelagic fishes, manta rays, reef sharks) at Palmyra Atoll and Kingman Reef (PKMPA) in the U.S. Pacific Islands Heritage Marine National Monument. PKMPA and the U.S. Exclusive Economic Zone encompassed 39% and 54% of species movements (n = 83; tracking duration range: 0.5-350 days), respectively. Species distribution models indicated 73% of PKMPA contained highly suitable habitat. Under two projected future scenarios (SSP 1-2.6, Sustainability; SSP 3-7.0, Rocky Road), strong sea surface temperature gradients initially could cause abrupt oceanic change resulting in predicted habitat loss in 2040-2050, followed by an equilibrium response and regained habitat by 2090-2100. Current and future suitable habitats were available adjacent to PKMPA, suggesting that increased MPA size could enhance protection. Our three-tiered approach combining animal tracking with publicly available remote sensing data and future projected environmental scenarios could be used to design, study, and monitor protected areas throughout the world. Holistic approaches that encompass diverse species and habitat use can enhance assessments of protected area designs. Animal telemetry and remote sensing may be helpful for ascertaining the extent to which other MPAs protect large mobile species in the future.

Abstract: Water temperature is a strong driver of growth, survival, and local adaptation in corals, but our knowledge of the temperatures experienced by corals on reefs worldwide remains limited. While in situ temperature loggers can provide high quality data, they are relatively expensive to place and retrieve. Alternatively, remotely sensed sea surface temperature data are globally available but may be a biased representation of the temperatures experienced by corals. Here, we compared data from 314 temperature loggers on coral reefs to the ~ 1 km2 resolution remotely sensed Multi-scale Ultra-high Resolution Sea Surface Temperature (MUR) product from NASA. We found good agreement (Pearson’s r = 0.95) between maximum monthly mean temperatures calculated from remote and in situ data, with 84% of temperatures within 0.5 °C of each other. However, remotely sensed temperature did not effectively capture sub-diel temperature fluctuations and the highest peak temperatures that may be most dangerous for corals. Predictions of in situ temperatures were significantly but weakly improved by a consideration of reef geomorphology. Ultimately, we found that remotely sensed temperatures can accurately represent the monthly conditions experienced by most corals but should be used with caution at finer temporal scales.

The use of quantitative real-time PCR (qPCR) to monitor pathogens is common; however, quantitative frameworks that consider the observation process, dynamics in pathogen presence, and pathogen load are lacking. This can be problematic in the early stages of disease progression, where low level detections may be treated as inconclusive and excluded from analyses. Alternatively, a framework that accounts for imperfect detection would provide more robust inferences. To better estimate pathogen dynamics, we developed a hierarchical multi-scale dynamic occupancy hurdle model (MS-DOHM). The model used data gathered during sampling for Pseudogymnoascus destructans (Pd), the causative agent of white-nose syndrome, a fungal disease that has cause severe declines in several species of hibernating bats in North America. The model allowed us to estimate initial occupancy, colonization, persistence and prevalence of Pd at bat hibernacula. Additionally, utilizing the relationship between cycle threshold and pathogen load, we estimated pathogen detectability and modeled expected colony and bat pathogen loads. To assess the ability of MS-DOHM to estimate pathogen dynamics, we compared MS-DOHMs results to those of a dynamic occupancy model and naïve detection/non-detection. MS-DOHMs estimates of site-level pathogen presence were up to 11.9% higher than estimates from the dynamic occupancy model and 35.7% higher than naïve occupancy. Including prevalence and load in our modeling framework resulted in estimates of pathogen arrival that were two to three years earlier compared to the dynamic occupancy and naïve detection/non-detection, respectively. Compared to naïve values, MS-DOHM predicted greater pathogen loads on colonies; however, we found no difference between model estimates and naïve values of prevalence. While the model predicted no declines in site-level prevalence, there were instances where pathogen load decreased in colonies that had been Pd positive for longer periods of time. Our findings demonstrate that accounting for pathogen load and prevalence at multiple scales changes our understanding of Pd dynamics, potentially allowing earlier conservation intervention. Additionally, we found that accounting for pathogen load and prevalence within hibernacula and among individuals resulted in a better fitting model with greater predictive ability.

PREMISE: Floral pigments such as anthocyanins are well known to influence pollinator attraction, yet they also confer tolerance to abiotic stressors such as harsh soils, extreme temperatures, low precipitation, and UV radiation. In such cases, environmental variation in abiotic stressors over space or time could lead to the maintenance of flower color variation within species. Under this scenario, flower color in natural populations should covary with environmental stressors. METHODS: Using a comparative approach, we tested whether abiotic variables predict flower color in Leptosiphon parviflorus, a species with pink and white flower color morphs. We conducted in-depth field studies to assess morph frequency, soil chemistry, and climate. We then employed community scientist-powered iNaturalist observations to examine patterns across even larger spatial scales. RESULTS: Across 21 field sites, L. parviflorus had a higher frequency of pink morphs in sites with serpentine soil, higher average annual temperatures, and higher average climatic water deficit (a proxy for drought stress). iNaturalist observations supported this finding-the probability of flowers being pink is greater in locations with serpentine-derived soil, especially when the local average UV radiation and climatic water deficit are higher. CONCLUSIONS: Spatial variation in abiotic stressors may contribute to the maintenance of flower color variation across the geographic range of L. parviflorus. Future studies will examine mechanisms by which flower color affects stress tolerance and will assess whether fitness trade-offs in contrasting habitats across the range are associated with flower color.

Abstract: Fisheries science agencies are responsible for informing fisheries management and ocean planning worldwide, often requiring scientific analysis and management actions across multiple spatial scales. For example, catch limits are typically defined annually over regional scales, fishery bycatch rules are defined at fine spatial scales on daily to annual time scales, and aquaculture and energy lease areas are defined over decades for subregional permitting at intermediate scales. Similarly, these activities require synthesizing monitoring data and mechanistic knowledge operating across different spatial resolutions and domains. These needs drive a growing role for models that predict animal presence or densities at fine spatial scales, including daily, seasonal, and interannual variation, often called species distribution/density models (SDMs). SDMs can inform many ocean management needs; however, their development and usage are often haphazard. In this paper we discuss various ways SDMs can and have been used in stock, habitat, protected species, and ecosystem management activities as well as marine spatial planning, survey optimization, and as an interface with ecosystem and climate models. We conclude with a discussion of future directions, focusing on information needs and current development, and highlight avenues for furthering the community of practice around SDM development and use.