Data from: Population-level habitat breadth varies with richness in reef fishes
Data files
Nov 05, 2024 version files 25.38 MB
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gaspar_for_dryad.csv
25.33 MB
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README.md
3.63 KB
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SpTraits_five_species_filled_by_Yoni.csv
43.25 KB
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taxa_data.csv
3.72 KB
Dec 21, 2024 version files 25.38 MB
-
gaspar_for_dryad.csv
25.33 MB
-
README.md
3.63 KB
-
SpTraits_five_species_filled_by_Yoni.csv
43.25 KB
-
taxa_data.csv
3.72 KB
Abstract
Aim: It has been hypothesized that niche-breadth should decrease with richness, due to interactions such as competition, forcing species to specialize. This hypothesis has been tested at the community-level using species-level niche breadth estimates. However, evidence for changes in niche-breath among populations of the same species are scant. Examining this relationship among populations is crucial for understanding the role of interactions, as opposed to large-scale climate, in altering realized niche breadth.
Location: The Pacific Ocean
Time period: 1996-2010
Methods: We focus on reef fishes along a large-scale richness gradient that is not accompanied by marked environmental changes. Fishes in each site were surveyed in four distinct habitats which allow to estimate the habitat-breadth for each population. We calculated the habitat-breadth of distinct populations of 154 fish species and tested how habitat-breadth varied with richness, while controlling for the effect of abundance. We further tested the effect of traits and trait-distinctiveness on the richness-sensitivity of habitat-breadth.
Results: Habitat-breadth varied with species traits, as large and mobile species were found to be habitat generalists while schooling species habitat specialists. Importantly, habitat-breadth was negatively correlated to richness for 109 out of the 154 species, and, across all species, the relationship was highly significant. As expected from competition being the major driver, we found that species with distinct traits displayed a wider habitat breadth, but that the relationship was sensitive to the type of trait-distinctiveness index used.
Conclusions: This is the first large-scale evidence that population-level habitat-breadth changes with richness. Results suggest that the realized niche is population specific, and that niche-breadth is reduced by local interactions such as competition. This implies that populations, specifically in rich areas, are far from using their entire fundamental niche. Therefore, the ability to predict habitat preferences in response to global change based on current habitat associations, but without accounting for species interactions, may be limited.
https://doi.org/10.5061/dryad.mcvdnck8q
Description of the data and file structure
Reef fish census survey data collected by a single surveyor (Michel Kulbicki) from 1988 to 2015, from dozens of locations across the globe.
The sampling unit is a belt transect (Search area indicated in the data).
Files and variables
File: gaspar_for_dryad.csv
Description:
Variables
- Subregion:
- Location: A location usually encompasses a few sites, up to a distance of a few tens of km.
- Site: A site is typically a few hundred m to a few km in size.
- ReefType: six distinct reef types: Lagoon facing barrier reef and Ocean facing barrier reef, Lagoon facing patch reef and Ocean facing patch reef, Lagoon facing fringing reef and Ocean facing fringing reef.
- Date: Date.
- Sample_ID_2: The sample unit unique ID.
- Search_Area: In squared meters
- Species: Species name.
- density: Number of individuals per 100 squared meters spotted.
- abundance: Number of individuals spotted.
File: SpTraits_five_species_filled_by_Yoni.csv
Description:
Variables
- Species: Name of species.
- Size.Class: Due the difficulty of obtaining a standard and reliable measure of body size, we separate all species into one of six size classes <7 cm; 7–15 cm; 15–30 cm; 30–50 cm; 50-80 cm; >80 cm.
- Home.Range: One of three ordinal categories: S - Sedentary or territorial species, species staying in a restricted area (less than a few 100 m²) for extended periods (at least a month). M – Mobile species, which will move from reef to reef or travel large distances over a reef. VM – Very mobile species which frequently change reefs or which daily travel large distances over a reef.
- Activity: Dial activity pattern. One of three ordinal categories: D – diurnal species. Fish active during day time hours. B – both. species active at all times, both night and day. N – night. Nocturnal species.
- Schooling: One of five ordinal categories: S – solitary species. Fish usually living alone (but they may group for reproduction or some other specific need). P – pairing species. Fish usually seen in pairs. F – species living in small groups (3–20 individuals). Groups do not need to be schools. M – species in groups of 20–50 individuals. L – species living in large groups or schools (>50 individuals).
- Level.water: Height in the water column. One of three ordinal categories: Bottom – species staying on the bottom at all times. Low – species living slightly above the bottom but which may at time rest on the bottom. High – species spending most of their active time high above the bottom (several meters)
- Diets: One of seven categorical groups: HD = herbivores-detritivores (undefined organic material, turf or filamentous algae), HM= herbivores (macroalgae and seagrass), IS= sessile invertebrates (e.g. corals, sponges and ascidians), IM= benthic mobile invertebrates, PK= planktivores (plankton and small organisms which migrate in the water column), FC= Pelagic and benthic macro-organisms (fish and cephalopods), OM= omnivores (carnivores and herbivores / detritivores).
File: taxa_data.csv
Description:
Variables
- Family: Family
- Genus: Genus
Code/software
Code_for_publication_Nov2024.Rmd- R markdown code.
Explanations within the code - pretty simple, nothing too complicated.
List of libraries used at the top (and within specific chunks of code at the end).
Underwater visual fish census survey data collected by Michel Kulbicki and Laurent Vigliola.
Data columns are very informative.
'Density' refers to the number of individuals per 100 squared meters.