Skip to main content
Dryad logo

Effects of harvesting on subtidal kelp forests (Lessonia trabeculata) in Central Chile

Citation

Pérez-Matus, Alejandro et al. (2022), Effects of harvesting on subtidal kelp forests (Lessonia trabeculata) in Central Chile, Dryad, Dataset, https://doi.org/10.5061/dryad.1zcrjdft7

Abstract

The systematic degradation of marine ecosystems is a global phenomenon that has important and diverse consequences including biodiversity loss and reduced ecosystem service provisions. In temperate regions, subtidal kelp forests are dominant ecosystems in rocky coasts, subjected to the influence of local-scale stressors and regional environmental variation. For example, kelps within the Humboldt Current System are at risk of degradation from live-harvesting by fisheries. However, limited information exists regarding the long-term consequences of kelp harvesting which, in turn, limits the ability to provide effective management and conservation efforts. Here, we examined the ecosystem-level consequences of the artisanal subtidal Lessonia trabeculata fishery along the coast of central Chile during a two-year period, assessing a) the change in adult and juvenile L. trabeculata density within harvested and non-harvested (control) plots (~90m2), b) the impact of L. trabeculata harvesting on reef fish and macroinvertebrate assemblages, and c) the change in density of the most abundant L. trabeculata-associated species. The experiment was conducted over a two-year period, from December 2016 to May 2019. Approximately 90% of L. trabeculata was removed by an experienced kelp fisherman in experimental plots. After two years, L. trabeculata and its associated community showed a lack of recovery in the harvested plots. Within these plots, the average abundance of the rock shrimp, Rhynchocinetes typus, and the herbivorous snail, Tegula tridentata, was greater than in non-harvested plots and the pattern persisted over the study period. The difference in abundance of associated species may be key to the (lack of) recovery of L. trabeculata forests. Our study highlights the impact of L. trabeculata harvesting on associated fauna, however, significant knowledge gaps remain regarding the capacity and time frame to re-establish the original biomass of L. trabeculata, as well as its associated fauna. The management of L. trabeculata fisheries needs to account for ecosystem-wide impacts in order to better manage and protect vital coastal ecosystems.

Methods

Experimental plots were monitored 6 times between December 2016 and May 2019. The first monitoring was conducted immediately prior to the harvesting (Pre) in order to provide baseline information on each plot. Afterwards, monitoring was conducted every three months during the first year and then two-years after the kelp was harvested.

At each sampling time, one 25-m transect was deployed within each plot and surveys of various portions of the transect alongside quadrats of varying size and placement interval (based on the size and mobility of target organisms/species) were conducted by SCUBA divers. When the transect extended beyond the edge of harvested plots, only the harvested portion of the transect was monitored. All data was standardized according to the sampled surface area in order to ensure comparability of measurements across treatments.

The density of adult (holdfast diameter ≥ 10 cm) and juvenile (< 10 cm) L. trabeculata sporophytes were estimated using the standard transect-quadrat method. Kelp L. trabeculata density was estimated in at least five 1 m2 quadrats that were placed every two meters over a transect placed at the center of each plot. In addition, the holdfast diameter, number of stipes, length (from base of holdfast to tip of stipe), and the foliage index of the canopy was recorded for each L. trabeculata sporophyte found within the quadrats. The foliage index is a visual estimate of the percentage of stipes containing blades with values ranging from 1 to 5 according to the following categories: 1 < 10%, 2 = 10 - 30 %, 3 = 30 - 50%, 4 = 50 - 80%, 5 = 80 -100% (see Pérez-Matus et al. 2017a for further information).

The density of mobile benthic macroinvertebrates (> 1 cm) were estimated by visual counts in at least five 2 m2 quadrats in the same transect where kelp was measured. In each quadrat, individuals were identified to the lowest possible taxonomic level. In two monitoring occasions (at 12 and 24 months post-harvesting), the percentage cover of macroscopic sessile invertebrate species (e.g. hydrozoans, macroalgae, barnacles, sponges) was also quantified in ten 0.25 m2 quadrats placed randomly within each plot. The percent cover of bare space (i.e. substrate free of macrobenthic species) was also quantified. In the case of organisms impossible to identify in situ, samples were taken for subsequent identification in the laboratory. 

Reef fishes were quantified using underwater visual census (UVC) along a 25 m transect placed at each plot. Along each transect, a diver registered the identity of each fish encountered within a 4 m wide and 5 m tall "tunnel". Common cryptic fish fauna (e.g. Blennidae, Labrisomidae, Clinidae, Trypterigidae) were quantified along the same transect but in a 2 m wide section (5 m tall; 250 m3). Fish surveys were conducted pre-harvesting and 6, 12 and 24 months post-harvesting.However, after harvesting event the UVC was performed only in the harvested section in the harvested plots therefore the transect length was reduced to ~11-15 m in length.  

Abiotic conditions including depth, slope and surface rugosity of each plot were estimated. Depth was recorded at each quadrat while the bottom slope was calculated as change in depth over length of transect. Bottom rugosity, an indicator of seafloor habitat complexity, was estimated by randomly placing a 4 m long, small link chain (1 cm per link) along a central area of each plot, ensuring it followed the topography of the substrate. The linear horizontal distance between the extremes of the chain provided a rugosity index. This measurement was repeated three times per plot and the average rugosity index was calculated. 

Usage Notes

6 different sheets are uploaded: 

Spread Sheet    Spread Sheet description
1. Spp_DB    Data base of the average abundance for each taxa, standardized per unit of observation
1. Spp_DB    Data base of the average abundance for each taxa, standardized per unit of observation
1. Spp_DB    Data base of the average abundance for each taxa, standardized per unit of observation
1. Spp_DB    Data base of the average abundance for each taxa, standardized per unit of observation
1. Spp_DB    Data base of the average abundance for each taxa, standardized per unit of observation
2. Slope_DB    Data base of the slope observed in each plot
2. Slope_DB    Data base of the slope observed in each plot
3. Rugosity_DB    Data base of the surface rugosity observed in each plot
3. Rugosity_DB    Data base of the surface rugosity observed in each plot
3. Rugosity_DB    Data base of the surface rugosity observed in each plot
4. Depth_DB    Data base of the average depth observed in each plot
4. Depth_DB    Data base of the average depth observed in each plot
5. Kelp Morphology    Data base of the kelp forest characterization observed in each plot
5. Kelp Morphology    Data base of the kelp forest characterization observed in each plot
5. Kelp Morphology    Data base of the kelp forest characterization observed in each plot
5. Kelp Morphology    Data base of the kelp forest characterization observed in each plot
5. Kelp Morphology    Data base of the kelp forest characterization observed in each plot
6. Readme

Column

Column description
A-C    Sampling Time, Treatment and Plot Identification
D-E    Kelp density data in: individuals * m-2
F-AU    Mobile Benthic Macroinvertebrates density data in: individuals * m-2
AV-BS    Sessile Kelp Understory species coverage data in: %
BT-CL    Reef Fish density data in: individuals * m-3
A-C    Sampling Time, Treatment and Plot Identification
D    Estimated slope of the plot
A-C    Sampling Time, Treatment and Plot Identification
D    N° of Replicate within each plot
E    Observed chain length once it was placed over the seafloor
A-C    Sampling Time, Treatment and Plot Identification
D    Average depth of the plot
A-C    Sampling Time, Treatment and Plot Identification
D    Average Holdfast Diameter within each plot, meassured as the maximum observed diameter
E    Average N° of Stipes per kelp within each plot
F    Average Foliage Index per kelp within each plot
G    Average Height per kelp within each plot, measured in a straight line from the holdfast up to the top of canopy

Funding

Consejo Nacional de Ciencia, Tecnología e Innovación Tecnológica, Award: NE/S011692

FONDECYT, Award: 1210216

FONDECYT, Award: 1171603

FONDECYT, Award: 1130167