Search for: All records

A critical tool in assessing ecosystem change is the analysis of long‐term data sets, yet such information is generally sparse and often unavailable for many habitats. Kelp forests are an example of rapidly changing ecosystems that are in most cases data poor. Because kelp forests are highly dynamic and have high intrinsic interannual variability, understanding how regional‐scale drivers are driving kelp populations—and particularly how kelp populations are responding to climate change—requires long‐term data sets. However, much of the work on kelp responses to climate change has focused on just a few, relatively long‐lived, perennial, canopy‐forming species. To understand how kelp populations with different life history traits are responding to climate‐related variability, we leverage 35 yr of Landsat satellite imagery to track the population size of an annual, ruderal kelp,Nereocystis luetkeana, across Oregon. We found high levels of interannual variability inNereocystiscanopy area and varying population trajectories over the last 35 yr. Surprisingly, OregonNereocystispopulation sizes were unresponsive to a 2014 marine heat wave accompanied by increases in urchin densities that decimated northern CaliforniaNereocystispopulations. Some OregonNereocystis populations have even increased in area relative to pre‐2014 levels. Analysis of environmental drivers found thatNereocystispopulation size was negatively correlated with estimated nitrate levels and positively correlated with winter wave height. This pattern is the inverse of the predicted relationship based on extensive prior work on the perennial kelpMacrocystis pyriferaand may be related to the annual life cycle ofNereocystis. This article demonstrates (1) the value of novel remote sensing tools to create long‐term data sets that may challenge our understanding of nearshore marine species and (2) the need to incorporate life history traits into our theory of how climate change will shape the ocean of the future.

 

ABSTRACT Predicting outcomes of marine disease outbreaks presents a challenge in the face of both global and local stressors. Host-associated microbiomes may play important roles in disease dynamics but remain understudied in marine ecosystems. Host–pathogen–microbiome interactions can vary across host ranges, gradients of disease, and temperature; studying these relationships may aid our ability to forecast disease dynamics. Eelgrass, Zostera marina , is impacted by outbreaks of wasting disease caused by the opportunistic pathogen Labyrinthula zosterae . We investigated how Z. marina phyllosphere microbial communities vary with rising wasting disease lesion prevalence and severity relative to plant and meadow characteristics like shoot density, longest leaf length, and temperature across 23° latitude in the Northeastern Pacific. We detected effects of geography (11%) and smaller, but distinct, effects of temperature (30-day max sea surface temperature, 4%) and disease (lesion prevalence, 3%) on microbiome composition. Declines in alpha diversity on asymptomatic tissue occurred with rising wasting disease prevalence within meadows. However, no change in microbiome variability (dispersion) was detected between asymptomatic and symptomatic tissues. Further, we identified members of Cellvibrionaceae, Colwelliaceae, and Granulosicoccaceae on asymptomatic tissue that are predictive of wasting disease prevalence across the geographic range (3,100 kilometers). Functional roles of Colwelliaceae and Granulosicoccaceae are not known. Cellvibrionaceae, degraders of plant cellulose, were also enriched in lesions and adjacent green tissue relative to nonlesioned leaves. Cellvibrionaceae may play important roles in disease progression by degrading host tissues or overwhelming plant immune responses. Thus, inclusion of microbiomes in wasting disease studies may improve our ability to understand variable rates of infection, disease progression, and plant survival. IMPORTANCE The roles of marine microbiomes in disease remain poorly understood due, in part, to the challenging nature of sampling at appropriate spatiotemporal scales and across natural gradients of disease throughout host ranges. This is especially true for marine vascular plants like eelgrass ( Zostera marina ) that are vital for ecosystem function and biodiversity but are susceptible to rapid decline and die-off from pathogens like eukaryotic slime-mold Labyrinthula zosterae (wasting disease). We link bacterial members of phyllosphere tissues to the prevalence of wasting disease across the broadest geographic range to date for a marine plant microbiome-disease study (3,100 km). We identify Cellvibrionaceae, plant cell wall degraders, enriched (up to 61% relative abundance) within lesion tissue, which suggests this group may be playing important roles in disease progression. These findings suggest inclusion of microbiomes in marine disease studies will improve our ability to predict ecological outcomes of infection across variable landscapes spanning thousands of kilometers. 

Two complementary approaches were used to assess year-round variation in the diet of sea otters Enhydra lutris around Prince of Wales Island (POW) in southern Southeast Alaska, a region characterized by mixed-bottom habitat. We observed sea otters foraging to determine diet composition during the spring and summer. Then, we obtained sea otter vibrissae, which record temporal foraging patterns as they grow, from subsistence hunters to identify year-round changes in sea otter diets via stable isotope analysis of carbon (δ 13 C) and nitrogen (δ 15 N). We compared the stable isotopes from sea otter vibrissae and sea otter prey items that were collected during spring, summer, and winter. Overall, year-round sea otter diet estimates from stable isotope signatures and visual observations from spring and summer were dominated by clams in terms of biomass, with butter clams Saxidomus gigantea the most common clam species seen during visual observations. Our results indicate that these sea otters, when considered together at a regional level around POW, do not exhibit shifts in the main prey source by season or location. However, sea otter diets identified by stable isotopes had a strong individual-level variation. Behavioral variation among individual sea otters may be a primary driving factor in diet composition. This study provides quantitative diet composition data for modeling predictions of invertebrate population estimates that may aid in the future management of shellfisheries and subsistence hunting and the development of co-management strategies for this protected species. 

Previous research in southeast Alaska on the effects of sea otters Enhydra lutris in seagrass Zostera marina communities identified many but not all of the trophic relationships that were predicted by a sea otter-mediated trophic cascade. To further resolve these trophic connections, we compared biomass, carbon (δ 13 C) and nitrogen (δ 15 N) stable isotope (SI), and fatty acid (FA) data from 16 taxa at 3 sites with high and 3 sites with low sea otter density (8.2 and 0.1 sea otters km -2 , respectively). We found lower crab and clam biomass in the high sea otter region but did not detect a difference in biomass of other seagrass community taxa or the overall community isotopic niche space between sea otter regions. Only staghorn sculpin differed in δ 13 C between regions, and Fucus , sugar kelp, butter clams, dock shrimp, and shiner perch differed in δ 15 N. FA analysis indicated multivariate dissimilarity in 11 of the 15 conspecifics between sea otter regions. FA analysis found essential FAs, which consumers must obtain from their diet, including 20:5ω3 (EPA) and 22:6ω3 (DHA), were common in discriminating conspecifics between sea otter regions, suggesting differences in consumer diets. Further FA analysis indicated that many consumers rely on diverse diets, regardless of sea otter region, potentially buffering these consumers from sea otter-mediated changes to diet availability. While sea otters are major consumers in this system, further studies are needed to understand the mechanisms responsible for the differences in biomarkers between regions with and without sea otters.