Click
here to close Hello! We notice that
you are using Internet Explorer, which is not supported by Echinobase
and may cause the site to display incorrectly. We suggest using a
current version of Chrome,
FireFox,
or Safari.
PLoS One
2020 Jan 01;153:e0226173. doi: 10.1371/journal.pone.0226173.
Show Gene links
Show Anatomy links
Marine deforestation leads to widespread loss of ecosystem function.
Edwards M
,
Konar B
,
Kim JH
,
Gabara S
,
Sullaway G
,
McHugh T
,
Spector M
,
Small S
.
???displayArticle.abstract???
Trophic interactions can result in changes to the abundance and distribution of habitat-forming species that dramatically reduce ecosystem functioning. In the coastal zone of the Aleutian Archipelago, overgrazing by herbivorous sea urchins that began in the 1990s resulted in widespread deforestation of the region''s kelp forests, which led to lower macroalgal abundances and higher benthic irradiances. We examined how this deforestation impacted ecosystem function by comparing patterns of net ecosystem production (NEP), gross primary production (GPP), ecosystem respiration (Re), and the range between GPP and Re in remnant kelp forests, urchin barrens, and habitats that were in transition between the two habitat types at nine islands that spanned more than 1000 kilometers of the archipelago. Our results show that deforestation, on average, resulted in a 24% reduction in GPP, a 26% reduction in Re, and a 24% reduction in the range between GPP and Re. Further, the transition habitats were intermediate to the kelp forests and urchin barrens for these metrics. These opposing metabolic processes remained in balance; however, which resulted in little-to-no changes to NEP. These effects of deforestation on ecosystem productivity, however, were highly variable between years and among the study islands. In light of the worldwide declines in kelp forests observed in recent decades, our findings suggest that marine deforestation profoundly affects how coastal ecosystems function.
???displayArticle.pubmedLink???
32130220
???displayArticle.pmcLink???PMC7055868 ???displayArticle.link???PLoS One
Fig 1. Three habitat types.Photographs of each habitat type showing (A) high abundance of benthic macroalgae and canopy-forming kelps in the kelp forests, (B) lack of benthic macroalgae but remaining canopy-forming kelps and high abundances of sea urchins in the transition habitats, and (C) lack of benthic macroalgae and canopy-forming kelps, but high abundances of sea urchins in the urchin barrens.
Fig 2. Map of the Aleutian Archipelago.Map of the Aleutian Archipelago showing locations of the nine islands (denoted by red circles) where ecosystem productivity (NEP, GPP and Re) was measured in the cBITs. Shoreline data was obtained from the Global Self-Consistent Hierarchical High-resolution Shoreline (GSHHG) dataset version 2.3.4 (www.soest.hawaii.edu/wessel/gshhg/) [32].
Fig 3. Algae and invertebrate biomass.Box plots showing (A) Macroalgae (gray bars) and invertebrate (white bars) biomass measured in the cBITs deployed within each habitat type (kelp forests, transition habitats, and urchin barrens) at six islands during 2017 (Table 1). Red diamonds represent mean values, and horizontal lines represent median values.
Fig 4. Algae and invertebrate biomass.Mean biomass (± SE) of (A) all kelps, and red, brown and green macroalgae, and (B) the most abundant taxonomic groups of invertebrates collected from within the cBITs in each habitat type at six of the islands where the cBITs were deployed in 2017 (Table 1). Fig 5B is divided into two panels, with abundant taxa on the left panel, and rarer taxa on the right panel.
Fig 5. Production metrics.Box plots showing (A) Net Ecosystem Production (NEP), (B) Gross Primary Production (GPP), (C) Ecosystem Respiration (Re), (D) the range between GPP and Re (Range), and (E) Irradiance (PAR), as measured in the cBITs deployed within each habitat type (kelp forests, transition habitats, and urchin barrens) at nine islands during 2016 and 2017 (Fig 2, Table 1). Red diamonds represent mean values, and horizontal lines represent median values. Boxes within each graph that do not share letters represent significant differences between habitat pairs.
Fig 6. GPP versus Re.Relationship between gross primary production (GPP) and ecosystem respiration (Re) for each habitat type across all nine islands where cBITs were deployed in 2016 and 2017 (Table 1). Each point represents measurements from a single cBIT. Gray shading denoted 95% confidence intervals.
Fig 7. GPP and Re ratios.Frequency distribution of GPP / Re ratios within each habitat type across all nine islands where cBITs were deployed in 2016 and 2017 (Table 1). Each data point represents measurements from a single cBIT. Note the urchin barrens have the highest ratios observed, and the kelp forests have the largest number of low values. The vertical dashed line represents the 1:1 ratio.
Fig 8. Photograph of cBIT.Photograph of (A) cBIT before deployment showing 26â skirt around perimeter, flexible polycarbonate walls, steel framing, anchor chain used to hold skirt and cBIT to the benthos, and (B) cBIT deployed in kelp forest showing PAR and oxygen sensors placed both inside and outside the chamber.
Bracken,
Realistic changes in seaweed biodiversity affect multiple ecosystem functions on a rocky shore.
2013, Pubmed
Bracken,
Realistic changes in seaweed biodiversity affect multiple ecosystem functions on a rocky shore.
2013,
Pubmed
Brook,
Catastrophic extinctions follow deforestation in Singapore.
2003,
Pubmed
Burt,
Sudden collapse of a mesopredator reveals its complementary role in mediating rocky reef regime shifts.
2018,
Pubmed
,
Echinobase
Duarte,
The CO2 balance of unproductive aquatic ecosystems.
1998,
Pubmed
Edwards,
A COMPARISON OF DRAGON KELP, EUALARIA FISTULOSA, (PHAEOPHYCEAE) FECUNDITY IN URCHIN BARRENS AND NEARBY KELP BEDS THROUGHOUT THE ALEUTIAN ARCHIPELAGO(1).
2012,
Pubmed
Estes,
Killer whale predation on sea otters linking oceanic and nearshore ecosystems.
1998,
Pubmed
,
Echinobase
Haas,
Influence of coral and algal exudates on microbially mediated reef metabolism.
2013,
Pubmed
Hewson,
Densovirus associated with sea-star wasting disease and mass mortality.
2014,
Pubmed
,
Echinobase
Krumhansl,
Global patterns of kelp forest change over the past half-century.
2016,
Pubmed
Menge,
Sea Star Wasting Disease in the Keystone Predator Pisaster ochraceus in Oregon: Insights into Differential Population Impacts, Recovery, Predation Rate, and Temperature Effects from Long-Term Research.
2016,
Pubmed
,
Echinobase
Michelou,
The Ecology of Microbial Communities Associated with Macrocystis pyrifera.
2013,
Pubmed
Middelboe,
Highly predictable photosynthetic production in natural macroalgal communities from incoming and absorbed light.
2006,
Pubmed
Miller,
Addition of species abundance and performance predicts community primary production of macroalgae.
2012,
Pubmed
Minich,
Elevated temperature drives kelp microbiome dysbiosis, while elevated carbon dioxide induces water microbiome disruption.
2018,
Pubmed
Pfister,
Kelp beds and their local effects on seawater chemistry, productivity, and microbial communities.
2019,
Pubmed
Reed,
Extreme warming challenges sentinel status of kelp forests as indicators of climate change.
2016,
Pubmed
Reisewitz,
Indirect food web interactions: sea otters and kelp forest fishes in the Aleutian archipelago.
2006,
Pubmed
,
Echinobase
Shukla,
Amazon deforestation and climate change.
1990,
Pubmed
Smale,
Impacts of ocean warming on kelp forest ecosystems.
2020,
Pubmed
Staufenberger,
Phylogenetic analysis of bacteria associated with Laminaria saccharina.
2008,
Pubmed
Tait,
Legacy effects of canopy disturbance on ecosystem functioning in macroalgal assemblages.
2011,
Pubmed
Tanaka,
Warming off southwestern Japan linked to distributional shifts of subtidal canopy-forming seaweeds.
2012,
Pubmed
Weigel,
Successional Dynamics and Seascape-Level Patterns of Microbial Communities on the Canopy-Forming Kelps Nereocystis luetkeana and Macrocystis pyrifera.
2019,
Pubmed
Wernberg,
Climate-driven regime shift of a temperate marine ecosystem.
2016,
Pubmed