Data from: Habitat dimensionality, temperature and feeding strategies as determinants of trophic structure in a marine food web
Data files
Aug 15, 2024 version files 11.10 KB
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README.md
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stable_isotope_data_punta_del_diablo_2015.csv
Abstract
Disentangling the determinants of trophic structure is central to ecology. The capacity to capture subjugate and consume a prey (i.e. gape limitation) is a relevant limitation to acquire energy for most organisms, especially those in smaller size ranges. This generates a size hierarchy of trophic positions in which large organisms consume small ones. Body size is tightly correlated to gape limitation and explains a large fraction of variance in the body size-trophic position relationship. However, a considerable fraction of variance still remains to be explained. Consumer search space dimensionality (2D or 3D) and feeding strategies, temperature and the size structure of primary producers can alter the trophic structure, but tests based on information from natural food webs are scarce.
We generated specific predictions about the body size trophic position relationship and evaluated them using information from a subtropical South Atlantic coastal marine ecosystem: benthic realm (2D, rocky shore and sandy beach) and the pelagic realm (3D). We characterized this marine coastal food web based on stable isotopes of carbon and nitrogen from 256 samples from primary producers (macroalgae and phytoplankton) to large predators (sand shark) in summer and winter. Consumer body size encompassed 6 orders of magnitude in weight from 10-2 to 6x104 g.
Isotopic signal corresponded to an integration of carbon sources from basal consumers to top predators. The body size-trophic position relationship showed a linear positive association with different slopes for the benthic and pelagic environments. This implies a smaller predator prey size ratio for pelagic (3D) with respect to benthic consumers (2D) as theoretically expected. No seasonal differences were found in slopes and most of the overall variance in benthic environments was largely explained by feeding strategies of the different taxonomic groups.
We provide an integrated evaluation on the role of body size, consumer search space and feeding strategy to understand the determinants of trophic position.
Results demonstrate that integrating Gape Limitation hypothesis, the dimensionality of consumer search space and feeding strategies into a formal robust framework to understand trophic structure is feasible even in complex natural ecosystems.
README
Title of Dataset
Data from: Habitat dimensionality, temperature and feeding strategies as determinants of trophic structure in a marine food web
Corresponding author: Angel Manuel Segura (asegura@cure.edu.uy)
This dataset encompasses Carbon (δ¹³C) and Nitrogen (δ¹⁵N) isotopic values obtained from various organisms and species during two surveys in 2015, conducted during the austral summer and winter, and covering both benthic and pelagic zones in the coastal area of Punta del Diablo (Uruguay), situated in the subtropical convergence of the Southwestern Atlantic Ocean.
Description of Dataset
File count: 1
File size: 8.3 KB
File format: .csv
File name: stable_isotope_data_punta_del_diablo_2015.csv
Provides a concise summary of isotopic values from:
- Pelagic Particulate Organic Matter (POM), serving as a proxy for phytoplankton
- Composite Zooplankton
- 32 Species of Macroinvertebrates from rocky shores, sublittoral zones, and sandy habitats
- 19 Species of Fishes
Carbon and nitrogen isotope values are reported using the standard delta notation relative to Vienna Pee Dee Belemnite (V-PDB) and to V-AIR, respectively , and expressed as deviations regarding that standard, in parts per mile in a delta notation (δ ‰).
Description of features/column header for the Dataset
date
: The specific date when the data was collected, formatted as YYYY-MM-DD.
year
: The year of data collection, all values are from the year 2015.
month
: The month in which the data was collected, "February" or "September".
season
: The season during which the data collection occurred, categorized as "Summer" or "Winter."
country
: The country where the data was collected, "Uruguay".
locality
: The specific locality or site within the country where the data collection took place, "Punta del Diablo".
scientific_name
: The taxonomic identification of the species that was subjected to stable isotope analysis (SIA).
life_stage
: The life stage of the specie, categorized as "A" for adults or "J" for juveniles.
count
: The number of individuals used for each species to perform SIA.
mean_d15N
: The mean value of nitrogen isotope (δ¹⁵N), expressed in parts per thousand (‰).
sd_d15N
: The standard deviation of δ¹⁵N.
mean_d13C
: The mean value of carbon isotope (δ¹³C), expressed in parts per thousand (‰).
sd_d13C
: The standard deviation of δ¹³C.
mean_mass
: The mean body size, expressed as wet weight in grams.
sd_mass
: The standard deviation of the body size.
Any Empty Value in the Data
Any cells containing 'NA' or left empty represent missing (null) values.
Sharing/Access information
This is the only publicly accessible locations of the dataset.
Methods
Study area and field collections
Samples were collected from Punta del Diablo, a coastal marine ecosystem on the South Atlantic coast of Uruguay (33°54’S - 53°30’W and 34°02’S – 53°32’W). Two surveys were conducted: one during austral summer (12th February) and a second one in winter (14th September) of 2015, at five sampling stations in both pelagic and benthic realms. Biological samples were collected with multiple gears to capture different size groups and to perform stable isotope analyses (SIA).
Laboratory analysis
Samples were analyzed at the Center for Stable Isotopes, University of New Mexico, USA (https://csi.unm.edu/). Carbon (δ13C) and nitrogen (δ15N) isotope ratios were measured by Elemental Analyzer Continuous Flow Isotope Ratio Mass Spectrometry using a Costech ECS 4010 Elemental Analyzer coupled to a ThermoFisher Scientific Delta V Advantage mass spectrometer via a CONFLO IV interface.
Detailed descriptions of the methodologies for SIA analysis, the study area, and the associated data analysis are available in Leoni et al. (2024), Journal of Animal Ecology.