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454 records · Page 26Linked to original sources
USGS2022

Diet energy density estimated from isotopes in predator hair associated with survival, habitat, and population dynamics

Sea ice loss is fundamentally altering the Arctic marine environment. Yet there is a paucity of data on the adaptability of food webs to ecosystem change, including predator-prey interactions. Polar bears ( Ursus maritimus ) are an important subsistence resource for Indigenous people and an apex predator that relies entirely on the under-ice food web to meet their energy needs. Here, we assessed whether polar bears maintained dietary energy density by prey switching in response to spatial-temporal variation in prey availability. We compared the macronutrient composition of diets inferred from stable carbon and nitrogen isotopes in polar bear guard hair (primarily representing summer/fall diet) during periods when bears had low and high survival 2004-2016, between bears that summered on land versus pack ice, and between bears occupying different regions of the Alaskan and Canadian Beaufort Sea. Polar bears consumed diets with lower energy density during periods of low survival suggesting that concurrent increased dietary proportions of beluga whales ( Delphinapterus leucas ) did not offset reduced proportions of ringed seals ( Pusa hispida ). Diets with the lowest energy density and proportions from ringed seal blubber were consumed by bears in the western Beaufort Sea (Alaska) during a period when polar bear abundance declined. Intake required to meet energy requirements of an average free-ranging adult female polar bear was 2.1 kg/day on diets consumed during years with high survival but rose to 3.0 kg/day when survival was low. Although bears that summered onshore in the Alaskan Beaufort Sea had higher fat diets than bears that summered on the pack ice, access to the remains of subsistence-harvested bowhead whales ( Balaena mysticetus ) contributed little to improving diet energy density. Because most bears in this region remain with the sea ice year-round, prey-switching and consumption of whale carcasses onshore appear insufficient to augment diets when availability of their primary prey, ringed seals, is reduced. Our results show that a strong predator-prey relationship between polar bears and ringed seals continues in the Beaufort Sea. The method of estimating dietary blubber using predator hair, demonstrated here, provides a new metric to monitor predator-prey relationships that affect individual health and population demographics.

Ecological Applications↗
USGS2006

Modeling habitat distribution from organism occurrences and environmental data: Case study using anemonefishes and their sea anemone hosts

We demonstrate the KGSMapper (Kansas Geological Survey Mapper), a straightforward, web-based biogeographic tool that uses environmental conditions of places where members of a taxon are known to occur to find other places containing suitable habitat for them. Using occurrence data for anemonefishes or their host sea anemones, and data for environmental parameters, we generated maps of suitable habitat for the organisms. The fact that the fishes are obligate symbionts of the anemones allowed us to validate the KGSMapper output: we were able to compare the inferred occurrence of the organism to that of the actual occurrence of its symbiont. Characterizing suitable habitat for these organisms in the Indo-West Pacific, the region where they naturally occur, can be used to guide conservation efforts, field work, etc.; defining suitable habitat for them in the Atlantic and eastern Pacific is relevant to identifying areas vulnerable to biological invasions. We advocate distinguishing between these 2 sorts of model output, terming the former maps of realized habitat and the latter maps of potential habitat. Creation of a niche model requires adding biotic data to the environmental data used for habitat maps: we included data on fish occurrences to infer anemone distribution and vice versa. Altering the selection of environmental variables allowed us to investigate which variables may exert the most influence on organism distribution. Adding variables does not necessarily improve precision of the model output. KGSMapper output distinguishes areas that fall within 1 standard deviation (SD) of the mean environmental variable values for places where members of the taxon occur, within 2 SD, and within the entire range of values; eliminating outliers or data known to be imprecise or inaccurate improved output precision mainly in the 2 SD range and beyond. Thus, KGSMapper is robust in the face of questionable data, offering the user a way to recognize and clean such data. It also functions well with sparse datasets. These features make it useful for biogeographic meta-analyses with the diverse, distributed datasets that are typical for marine organisms lacking direct commercial value. ?? Inter-Research 2006.

Marine Ecology Progress Series↗
USGS2015

Determining origin in a migratory marine vertebrate: a novel method to integrate stable isotopes and satellite tracking

Stable isotope analysis is a useful tool to track animal movements in both terrestrial and marine environments. These intrinsic markers are assimilated through the diet and may exhibit spatial gradients as a result of biogeochemical processes at the base of the food web. In the marine environment, maps to predict the spatial distribution of stable isotopes are limited, and thus determining geographic origin has been reliant upon integrating satellite telemetry and stable isotope data. Migratory sea turtles regularly move between foraging and reproductive areas. Whereas most nesting populations can be easily accessed and regularly monitored, little is known about the demographic trends in foraging populations. The purpose of the present study was to examine migration patterns of loggerhead nesting aggregations in the Gulf of Mexico (GoM), where sea turtles have been historically understudied. Two methods of geographic assignment using stable isotope values in known-origin samples from satellite telemetry were compared: 1) a nominal approach through discriminant analysis and 2) a novel continuous-surface approach using bivariate carbon and nitrogen isoscapes (isotopic landscapes) developed for this study. Tissue samples for stable isotope analysis were obtained from 60 satellite-tracked individuals at five nesting beaches within the GoM. Both methodological approaches for assignment resulted in high accuracy of foraging area determination, though each has advantages and disadvantages. The nominal approach is more appropriate when defined boundaries are necessary, but up to 42% of the individuals could not be considered in this approach. All individuals can be included in the continuous-surface approach, and individual results can be aggregated to identify geographic hotspots of foraging area use, though the accuracy rate was lower than nominal assignment. The methodological validation provides a foundation for future sea turtle studies in the region to inexpensively determine geographic origin for large numbers of untracked individuals. Regular monitoring of sea turtle nesting aggregations with stable isotope sampling can be used to fill critical data gaps regarding habitat use and migration patterns. Probabilistic assignment to origin with isoscapes has not been previously used in the marine environment, but the methods presented here could also be applied to other migratory marine species.

Ecological Applications↗
USGS2017

Trophic structure of mesopelagic fishes in the Gulf of Mexico revealed by gut content and stable isotope analyses

Mesopelagic fishes represent an important component of the marine food web due to their global distributions, high abundances and ability to transport organic material throughout a large part of the water column. This study combined stable isotope (SIAs) and gut content analyses (GCAs) to characterize the trophic structure of mesopelagic fishes in the North-Central Gulf of Mexico. Additionally, this study examined whether mesopelagic fishes utilized chemosynthetic energy from cold seeps. Specimens were collected (9–25 August 2007) over three deep (>1,000 m) cold seeps at discrete depths (surface to 1,503 m) over the diurnal cycle. GCA classified 31 species (five families) of mesopelagic fishes into five feeding guilds: piscivores, large crustacean consumers, copepod consumers, generalists and mixed zooplanktivores. However, these guilds were less clearly defined based on stable isotope mixing model (MixSIAR) results, suggesting diets may be more mixed over longer time periods (weeks–months) and across co-occurring species. Copepods were likely important for the majority of mesopelagic fishes, consistent with GCA (this study) and previous literature. MixSIAR results also identified non-crustacean prey items, including salps and pteropods, as potentially important prey items for mesopelagic fishes, including those fishes not analysed in GCA ( Sternoptyx spp. and Melamphaidae). Salps and other soft-bodied species are often missed in GCAs. Mesopelagic fishes had δ 13 C results consistent with particulate organic matter serving as the baseline organic carbon source, fueling up to three trophic levels. Fishes that undergo diel vertical migration were depleted in 15 N relative to weak migrators, consistent with depth-specific isotope trends in sources and consumers, and assimilation of 15 N-depleted organic matter in surface waters. Linear correlations between fish size and δ 15 N values suggested ontogenetic changes in fish diets for several species. While there was no direct measure of mesopelagic fishes assimilating chemosynthetic material, detection of infrequent consumption of this food resource may be hindered by the assimilation of isotopically enriched photosynthetic organic matter. By utilizing multiple dietary metrics ( e.g . GCA, δ 13 C, δ 15 N, MixSIAR), this study better defined the trophic structure of mesopelagic fishes and allowed for insights on feeding, ultimately providing useful baseline information from which to track mesopelagic trophodynamics over time and space.

Marine Ecology↗