Trait-mediated indirect interactions among residents of rocky shore tidepools

Trait-mediated indirect interactions (TMIIs) are an important component of food web structure and dynamics. We determined whether TMIIs occur in rocky tidepool communities on the west coast of the USA. In the laboratory, both adults and juveniles of the keystone predator Pisaster ochraceus and adults of a smaller predatory seastar Leptasterias spp. caused the abundant herbivorous snail Tegula funebralis to stop foraging and flee the water, inducing a positive TMII on micro- and macroalgae. Snails preferred 3 common species of macroalgae (Ulva lactuca, Cladophora columbiana and Porphyra spp.) over 4 others, indicating that seastars might provide the strongest benefits to these species in tidepools. In the laboratory, snails responded rapidly to both species of predatory seastars and many more snails responded than could be eaten; thus, there is a potential for TMIIs to occur in natural populations. Snails responded to waterborne cues from P. ochraceus by reducing grazing and leaving still water, and reducing grazing in laminar flow (0.5 l min-1), resulting in TMII effects at least as far as 75 cm away. Adult P. ochraceus and Leptasterias spp. introduced to tidepools during low tide induced many snails to flee the tidepools. Considerable individual variation occurred in the responses of snails. Medium and large snails mediated TMIIs and hungry snails were marginally less responsive to seastars potentially altering TMII strength in nature. Thus, we demonstrated that TMIIs could occur in natural tidepools and showed how predator and algal identity, predator and prey size, water flow and prey hunger level may influence these TMIIs.Keywords: Rocky intertidal tidepools, Trait-mediated indirect interaction, Chemical cue Community structure, Predator-prey interaction, Nonconsumptive effectKeywords: Rocky intertidal tidepools, Trait-mediated indirect interaction, Chemical cue Community structure, Predator-prey interaction, Nonconsumptive effec

Sea Star Wasting Disease in the Keystone Predator Pisaster ochraceus in Oregon: Insights into Differential Population Impacts, Recovery, Predation Rate, and Temperature Effects from Long-Term Research

Sea star wasting disease (SSWD) first appeared in Oregon in April 2014, and by June had spread to most of the coast. Although delayed compared to areas to the north and south, SSWD was initially most intense in north and central Oregon and spread southward. Up to 90% of individuals showed signs of disease from June-August 2014. In rocky intertidal habitats, populations of the dominant sea star Pisaster ochraceus were rapidly depleted, with magnitudes of decline in density among sites ranging from -2x to -9x (59 to 84%) and of biomass from -2.6x to -15.8x (60 to 90%) by September 2014. The frequency of symptomatic individuals declined over winter and persisted at a low rate through the spring and summer 2015 (~5–15%, at most sites) and into fall 2015. Disease expression included six symptoms: initially with twisting arms, then deflation and/or lesions, lost arms, losing grip on substrate, and final disintegration. SSWD was disproportionally higher in orange individuals, and higher in tidepools. Although historically P. ochraceus recruitment has been low, from fall 2014 to spring 2015 an unprecedented surge of sea star recruitment occurred at all sites, ranging from ~7x to 300x greater than in 2014. The loss of adult and juvenile individuals in 2014 led to a dramatic decline in predation rate on mussels compared to the previous two decades. A proximate cause of wasting was likely the “Sea Star associated Densovirus” (SSaDV), but the ultimate factors triggering the epidemic, if any, remain unclear. Although warm temperature has been proposed as a possible trigger, SSWD in Oregon populations increased with cool temperatures. Since P. ochraceus is a keystone predator that can strongly influence the biodiversity and community structure of the intertidal community, major community-level responses to the disease are expected. However, predicting the specific impacts and time course of change across west coast meta-communities is difficult, suggesting the need for detailed coast-wide investigation of the effects of this outbreak

Community Responses to Climate-Related Variability and Disease: The Critical Importance of Long-Term Research

A major goal of the Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO) has been to understand the impacts of climate change and variability on the coastal ecosystems of the inner shelf of the California Current Large Marine System in particular, and other marine and even nonmarine systems more generally. Insights can result from determination of impacts of climatic perturbations such as the El Niño-Southern Oscillation, the North Pacific Gyre Oscillation, and the Pacific Decadal Oscillation, as well as impacts of climate-related surprises on populations, communities, and ecosystems. To gain insight into warming impacts at organismal levels, we also investigated mechanistic suborganismal (physiological, molecular) responses to thermal conditions. Warmer water was connected to changes in ecological subsidies, growth of dominant space occupiers (mussels and barnacles), and heightened physiological stress impacts. Fortuitously, PISCO researchers were ideally positioned to document ecosystem vulnerability and resilience to an unprecedented ecological surprise—coast-wide collapse of keystone predator (sea star) populations—and to investigate its consequences. As these examples suggest, long-term sampling is critically important for helping society anticipate and adapt to present and future disruptions caused by global change

SEX AND MICROHABITAT INFLUENCE THE ALLOCATION OF MYCOSPORINE-LIKE AMINO ACIDS TO TISSUES IN THE PURPLE SEA URCHIN, STRONGYLOCENTROTUS PURPURATUS

Field surveys of Strongylocentrotus purpuratus demonstrated that concentrations of natural sunscreens, mycosporine-like amino acids (MAAs), were higher in females than males for both gonadal and epidermal tissues, increased in ovaries as spawning season approached, and were influenced by the sea urchins’ microhabitat. Sea urchins occupying burrows, or “pits”, had lower concentrations of MAAs than those outside pits, suggesting a trade-off between physical and UV protection. Overall, UV irradiance did not influence MAA accumulation in gonadal tissues. However, males increased their allocation of MAAs to epidermal tissues in the microhabitat with the highest irradiance. Relative concentrations of individual MAAs were similar for epidermal tissues from both sexes and ovaries, providing broadband UVA/UVB absorbance, but testes contained principally one MAA, palythine. This is the first study to demonstrate that S. purpuratus and eight species of macroalgae in California have MAAs, and that the concentrations can be influenced by microhabitat

Daily air and water temperatures, monthly mean wave heights, and monthly tidal extremes from central Oregon to southern California

Latitudinal variation in intertidal conditionsTemperature Logger Data AnalysisTo characterize the temperature regime at each site (see Sites dataset), we used existing temperature loggers deployed by the PISCO and MARINe research programs during 2016-2018. Most sites (n = 25) had at least one logger deployed during the study but several sites (n=8) did not, so we used the nearest site with a logger, with a maximum distance of 44.8 km away from a site. Temperature loggers (HOBO TidBit v2 by Onset) were deployed at fixed locations inside steel mesh cages, set to record every 15 mins, and swapped every ~6-12 months. Once loggers were collected, we assigned the tidal levels for each site and time stamp using Xtide software (https://flaterco.com/xtide/files.html) and the nearest harmonic tidal station (see Environmental Stations). We included logger temperatures for 2016 – 2018 since not all sites had loggers deployed continuously in 2018 alone. We graphed the temperature and the tide heights for each logger, and used this to visually estimate the shore level of the logger to the nearest 0.5 ft (air temperatures have clearly higher variance than water temperatures). We assigned any tide height higher than the logger height as “water” and any tide height lower than the logger height as “air”. We calculated the daily average mean and maximum air and water temperatures at each site, then graphed the monthly means with latitude to visualize latitudinal trends. We also calculated the average daily mean and maximum water temperature from 2016-2018. On wavy days, temperatures assigned as air temperatures probably intermittently submerged. However, we are more interested in air temperature stress than average air temperature, so our focal air temperature metric was maximum daily air temperature, which likely occurred during the lowest tides when waves were not washing over the loggers.Tidal Extremes, Tidal Amplitude, and Significant Wave HeightTo broadly characterize tidal levels and wave exposure trends that may influence the latitudinal and vertical ranges of our focal species, we queried daily environmental data during 2018 from offshore NOAA offshore oceanographic buoys for waves (https://www.ndbc.noaa.gov/obs.shtml) and onshore tidal stations for tides (https://tidesandcurrents.noaa.gov/stations.html?type=Water+Level+Reports) closest to each of our sites (see Environmental Stations). We calculated and graphed the average daily and then monthly mean significant wave height (i.e., highest ⅓ of waves) from each oceanographic buoy and the highest and lowest monthly tidal extremes for each onshore tidal station.</p

Densities, Lengths and Vertical Limits of intertidal predator species at 33 sites on the US West Coast

Predator SurveysWe conducted predator surveys in spring and summer 2018 at 33 rocky intertidal field sites from Orange County in southern California to Lincoln County in central Oregon (Fig. 1, Appendix S1 Table S1.1). The lower latitude sites represented the coastline at or nearing the southern range boundaries of the focal taxa (Frontana-Uribe et al., 2008; Marko et al., 2003; Morris et al., 1980). We surveyed five transects per site that extended from the high to low intertidal zones and spanned mussel beds (2-50 meters in length depending on site topography). We surveyed 0.5 x 0.5-meter quadrats placed at 0.5 to 2 meter intervals along each transect. Quadrat intervals were closer (every 0.5 m) near the lower limits of the mussel beds for finer spatial resolution where predators tended to be more abundant. We avoided surveying large tidepools (>~50 cm wide or >~20cm deep), deep cracks (> ~20 cm deep) and highly rugose surfaces.In each quadrat, we counted and measured individuals of all accessible predatory sea star and snail species, including Pisaster ochraceus, Leptasterias spp., Acanthinucella spp., Nucella canaliculata, N. emarginata, N. lamellosa, N. ostrina, and Paciocinebrina circumtexta. Size data were not collected at the two southernmost sites, Crystal Cove and Shaw’s Cove (CRCO and SHCO). Whelk size was maximum shell length (mm) from apex to the siphonal notch. Sea star size was length (mm) from the center of the central disk to the straightest arm tip (Leptasterias, P. ochraceus in California) or from madreporite to the opposite arm tip (P. ochraceus in Oregon, keeping with legacy practice). See Conversion for P. ochraceus Arm Length Measurements for more information.Species groupingsSince some predator taxa were rare or only occurred at some sites (Acanthinucella spp., N. lamellosa, Paciocinebrina circumtexta), we focused only on the predator taxa that were common, including Pisaster ochraceus, Leptasterias spp., N. canaliculata, N. ostrina and N. emarginata. Identification of P. ochraceus and the channeled whelk N. canaliculata in the field is straightforward. Field identification for species in the Leptasterias spp. complex (Flowers & Foltz, 2001; Foltz et al., 2008; Melroy & Cohen, 2021) is not possible, however. Similarly, the visually indistinguishable congeners N. emarginata and N. ostrina overlap from San Francisco Bay to Point Conception (Fig.1, Marko et al., 2003). Hence, we grouped these taxa as Leptasterias spp. and emarginate whelks, respectively.Vertical Zonation of PredatorsWe assigned each individual predator a shore level according to the center of the quadrat in which it was found (see Calculating Shore Levels in for more information). To determine the vertical limits of each predator, we estimated the upper and lower limits of each predator for each transect as the 0.5% quantile and 99.5% quantile, respectively, the median limit of the zone as the 50% quantile, and the vertical span as the difference between the upper and lower limits. Since P. ochraceus, Leptasterias spp. and N. canaliculata extend into the subtidal zone, we did not analyze the lower limits nor vertical span of these predators. Emarginate whelks are exclusively intertidal, so we were able to analyze their lower limits and vertical spans. For each of the 4 predator’s statistical models, we fit mixed effects linear models in JMP (v16.0, SAS Institute) by restricted maximum likelihood (REML) and included site as a random variable to account for the non-independence of transects within a given site. We tested the main and interactive effects of latitude and the 4 predator taxa on upper and median limits and the effect of latitude on the lower limit and vertical span of the emarginate whelk species complex.Densities of PredatorsWe calculated densities of species at the quadrat, transect, and site level only from quadrats in the ‘potential habitable zone’ of each species so that we excluded quadrats that were not within their vertical range at a given latitude (see Potential Habitable Zone for more information). We analyzed density with latitude using a generalized linear model (glm() in stats package v4.0.0) in R (R Core Team, 2020) and specified a Poisson distribution. We tested the main and interactive effects of latitude and species on counts at each site, using the log10 of total area surveyed as an offset. We analyzed the effects of species, region, and site nested within region on counts using a generalized linear mixed model (glmer in lme4 R package v 1.1-34 (Bates et al., 2015), and again used a Poisson distribution and the log10 of total area surveyed as an offset. Southern California sites could not be included in this model since there were zero individuals of all species except N. ostrina and emarginata.Conversion for P. ochraceus Arm Length Measurements To enable P. ochraceus size comparisons between California and Oregon and to allow other researchers to easily convert between arm lengths using different published methods, we measured arm lengths of 25 sea stars ranging in arm length from ~5-200mm at each of 6 sites in Oregon (Fig. 1) using both measurement approaches. To determine whether site influenced this conversion, we first ran a linear model with madreporite measure as the response variable and site and center measure as the interacting factors. No interacting effect of site and arm measurement from center to arm tip was found (F5,138 = 0.64, P = 0.672), suggesting this metric is consistent geographically, at least within Oregon. We had no data for California. So, we used a simple linear regression (R2 = 0.97, P Calculating Shore Levels At each site, we determined the height above mean sea level (MSL) of at least one reference point (a permanent lag screw) using a Trimble system with decimeter accuracy (cutoff was ± 0.25 m) (Trimble ® Zephyr™ Model 2 external Global Navigation Satellite System antenna, Trimble® GPS Pathfinder® ProXRT receiver and Trimble® Nomad® 900 series computer, https://geospatial.trimble.com/products-and-solutions/gnss-systems). Before using the Trimble, we identified the time windows with the best satellite configuration and lowest dilution of precision values using http://gnssmissionplanning.com/. We then calculated the MSL of every quadrat relative to this lag bolt, using surveying equipment (rotating laser level and stadia rod, TopCon RL-H4C). MSL measures were converted to the more ecologically-relevant meters above Mean Lower Low Water (MLLW), the tidal datum for this coast, by correcting for the meters of offset between the two measures for each site (https://vdatum.noaa.gov/vdatumweb/). By calculating the shore level above MSL for every quadrat, we were able to compare vertical distributions of predators between sites and within sites regardless of rock topography. Potential Habitable Zone Our transects spanned from the upper to lower intertidal, so we often sampled areas that were outside the zone of a given predator. To calculate accurate densities only within the habitable zone of a predator, we established the “potential habitable zone” for each species, which clearly changed with latitude (Fig. S2). We first analyzed how the shore level of individuals varied with latitude for each species using a regression. We then calculated the confidence interval around the line of fit at alpha = 0.005. We used this 99% confidence limit formula to calculate the upper and lower limits of the ‘potential habitable zone’ at a given latitude (Fig. S2). Note that this is different than the upper and lower limits above because 1) it spans a larger vertical area to capture the entire habitable zone (99% CI instead of the 95% CI), 2) it is a potential zone based on the latitude of the site, not the realized zone based on the position of individuals at a site, 3) it is not influenced by site-level density and 4) it should be independent of site topography (e.g. rocky habitat availability). By doing this, we were able to calculate species densities only within appropriate habitat in which we can reasonably expect to find a given predator at a given site.</p

Pisaster ochraceus arm length conversion using center or madreporite

Conversion for Pisaster ochraceus Arm Length MeasurementsTo enable P. ochraceus size comparisons between California and Oregon and to allow other researchers to easily convert between arm lengths using different published methods, we measured arm lengths of 25 sea stars ranging in arm length from ~5-200mm at each of 6 sites in Oregon (see manuscript) using both measurement approaches. To determine whether site influenced this conversion, we first ran a linear model with madreporite measure as the response variable and site and center measure as the interacting factors. No interacting effect of site and arm measurement from center to arm tip was found (F5,138 = 0.64, P = 0.672), suggesting this metric is consistent geographically, at least within Oregon. We had no data for California. So, we used a simple linear regression (R2 = 0.97, P < 0.001) to convert madreporite measures to center measures for all our data. Conversion formulas in centimeters are: [madreporite arm length = 4.074 + (1.060*center arm length)] or [center arm length= -0.729 + (0.914*madreporite arm length)].</p

Rocky intertidal site list

Oregon and California site list matching data in Biogeographic patterns in density, recruitment, body size, and zonation of rocky intertidal predators suggest increased population vulnerability near southern range limits</p