Other faunas, coral rubbles, and soft coral covers are important predictors of coral reef fish diversity, abundance, and biomass
2
조회
0
다운로드
0
인용
0
참고문헌
키워드
초록
Coral reef fisheries are prominent for the archipelagic countries’ food sufficiency and security. Studies showed that fish abundance and biomass are affected by biophysical variables. The present study determines which biophysical variables are important predictors of fish diversity, abundance, and biomass. The study used available monitoring data from the Indonesian Research Center for Oceanography, the National Board for Research and Innovation. Data were collected from 245 transects in 19 locations distributed across the Indonesian Archipelago, including the eastern Indian Ocean, Sunda Shelf (Karimata Sea), Wallacea (Flores and Banda Seas), and the western Pacific Ocean. Principal component analysis and multiple regression model were administered to 13 biophysical metrics against 11 variables of coral reef fishes, i.e., diversity, abundance, and biomass of coral reef fishes at three trophic levels. The results showed for the first time that the covers of other fauna, coral rubbles, and soft corals were the three most important predictor variables for nearly all coral reef fish variables. Other fauna cover was the important predictor for all 11 coral reef fish variables. Coral rubble cover was the predictor for ten variables, but carnivore fish abundance. Soft coral cover was a good predictor for corallivore, carnivore, and targeted fishes. Despite important predictors for corallivore and carnivore fish variables, hard coral cover was not the critical predictor for herbivore fish variables. The other important predictor variables with a consistent pattern were dead coral covered with algae and rocks. Dead coral covered with algae was an important predictor for herbivore fishes, while the rock was good for only carnivore fishes.
Abstract
Coral reef fisheries are prominent for the archipelagic countries’ food sufficiency and security. Studies showed that fish abundance and biomass are affected by biophysical variables. The present study determines which biophysical variables are important predictors of fish diversity, abundance, and biomass. The study used available monitoring data from the Indonesian Research Center for Oceanography, the National Board for Research and Innovation. Data were collected from 245 transects in 19 locations distributed across the Indonesian Archipelago, including the eastern Indian Ocean, Sunda Shelf (Karimata Sea), Wallacea (Flores and Banda Seas), and the western Pacific Ocean. Principal component analysis and multiple regression model were administered to 13 biophysical metrics against 11 variables of coral reef fishes, i.e., diversity, abundance, and biomass of coral reef fishes at three trophic levels. The results showed for the first time that the covers of other fauna, coral rubbles, and soft corals were the three most important predictor variables for nearly all coral reef fish variables. Other fauna cover was the important predictor for all 11 coral reef fish variables. Coral rubble cover was the predictor for ten variables, but carnivore fish abundance. Soft coral cover was a good predictor for corallivore, carnivore, and targeted fishes. Despite important predictors for corallivore and carnivore fish variables, hard coral cover was not the critical predictor for herbivore fish variables. The other important predictor variables with a consistent pattern were dead coral covered with algae and rocks. Dead coral covered with algae was an important predictor for herbivore fishes, while the rock was good for only carnivore fishes.
참고문헌 (40)
- Agudo-Adriani EA, "Structural complexity and benthic cover explain reef-scale variability of fish assemblages in Los Roques National Park, Venezuela", Front Mar Sci, 6, pp.690~ (2019)
- Arias-González JE, "A coral-algal phase shift in Mesoamerica not driven by changes in herbivorous fish abundance", PLOS ONE, 12, pp.e0174855~ (2017)
- Bachtiar I, "Differential impacts of 2016 coral bleaching on coral reef benthic communities at Sekotong Bay, Lombok Barat, Indonesia", Biodiversitas, 20, pp.570~575 (2019)
- Imam Bachtiar, "Biak and Wakatobi reefs are the two hottest hotspots of coral reef fish diversity and abundance in the Indonesian Archipelago", Fisheries and Aquatic Sciences, 25(11), pp.549~558 (2022), 한국수산과학회[DOI]
- Imam Bachtiar, "Practical Resilience Index for Coral Reef Assessment", Ocean Science Journal, 54(1), pp.117~127 (2019), 한국해양과학기술원[DOI]
- Beaman RJ, "Mapping the seafloor for habitat characterization: GAC special paper 47", pp.247~264 (2007), Geological Association of Canada
- Cabral RB, "How important are coral reefs to food security in the Philippines? Diving deeper than national aggregates and averages", Mar Policy, 91, pp.136~141 (2018)
- Chadwick NE, "Coral reefs: an ecosystem in transition", pp.347~371 (2011), Springer
- Epstein HE, "Are soft coral habitats unfavourable? A closer look at the association between reef fishes and their habitat", Environ Biol Fishes, 102, pp.479~497 (2019)
- Foo SA, "Impacts of pollution, fishing pressure, and reef rugosity on resource fish biomass in West Hawaii", Ecol Appl, 31, pp.e2213~ (2021)
- Froese R, "FishBase 2000: concepts, designs and data sources" (2000), International Center for Living Aquatic Resources Management
- Gilmour JP, "Recovery of an isolated coral reef system following severe disturbance", Science, 340, pp.69~71 (2013)
- Graham NAJ, "Coral mortality versus structural collapse as drivers of corallivorous butterflyfish decline", Biodivers Conserv, 18, pp.3325~3336 (2009)
- Harborne AR, "The effectiveness of different meso-scale rugosity metrics for predicting intra-habitat variation in coral-reef fish assemblages", Environ Biol Fishes, 94, pp.431~442 (2012)
- Hoegh-Guldberg O, "Securing a long-term future for coral reefs", Trends Ecol Evol, 33, pp.936~944 (2018)
- Huntington BE, "Corals fail to recover at a Caribbean marine reserve despite ten years of reserve designation", Coral Reefs, 30, pp.1077~1085 (2011)
- Jennings S, "Impacts of predator depletion by fishing on the biomass and diversity of non-target reef fish communities", Coral Reefs, 16, pp.71~82 (1997)
- Kohler KE, "Coral point count with Excel extensions(CPCe) : a visual basic program for the determination of coral and substrate coverage using random point count methodology", Comput Geosci, 32, pp.1259~1269 (2006)
- Malik SAA, "Chemical defense against microfouling by allelopathic active metabolites of Halymenia floresii(Rhodophyta)", J Appl Phycol, 32, pp.2673~2687 (2020)
- Mellin C, "Environmental and spatial predictors of species richness and abundance in coral reef fishes", Glob Ecol Biogeogr, 19, pp.212~222 (2010)
- Morais RA, "Pelagic subsidies underpin fish productivity on a degraded coral reef", Curr Biol, 29, pp.1521~1527 (2019)
- Nanami A, "Spatial distribution and feeding substrate of butterflyfishes (family Chaetodontidae) on an Okinawan coral reef", PeerJ, 8, pp.e9666~ (2020)
- Newman MJH, "Structure of Caribbean coral reef communities across a large gradient of fish biomass", Ecol Lett, 9, pp.1216~1227 (2006)
- Parravicini V, "Global patterns and predictors of tropical reef fish species richness", Ecography, 36, pp.1254~1262 (2013)
- Richardson LE, "Structural complexity mediates functional structure of reef fish assemblages among coral habitats", Environ Biol Fishes, 100, pp.193~207 (2017)
- Ruppert JLW, "Human activities as a driver of spatial variation in the trophic structure of fish communities on Pacific coral reefs", Glob Change Biol, 24, pp.e67~e79 (2018)
- Russ GR, "Coral cover a stronger driver of reef fish trophic biomass than fishing", Ecol Appl, 31, pp.e02224~ (2021)
- Sancelme T, "Contrasting patterns in the abundance of fish communities targeted by fishers on two coral reefs in southern Mozambique", Afr J Mar Sci, 42, pp.95~107 (2020)
- Sartori G, "Coral reef carnivorous fish biomass relates to oceanographic features depending on habitat and prey preference", Mar Environ Res, 172, pp.105504~ (2021)
- Sequeira AMM, "Transferability of predictive models of coral reef fish species richness", J Appl Ecol, 53, pp.64~72 (2016)
- Stuart-Smith RD, "Ecosystem restructuring along the Great Barrier Reef following mass coral bleaching", Nature, 560, pp.92~96 (2018)
- Syms C, "Soft corals exert no direct effects on coral reef fish assemblages", Oecologia, 127, pp.560~571 (2001)
- Teh LSL, "Time discounting and the overexploitation of coral reefs", Environ Resour Econ, 61, pp.91~114 (2015)
- Thompson DM, "Variability in oceanographic barriers to coral larval dispersal : do currents shape biodiversity?", Prog Oceanogr, 165, pp.110~122 (2018)
- Tootell JS, "Distribution, behavior, and condition of herbivorous fishes on coral reefs track algal resources", Oecologia, 181, pp.13~24 (2016)
- Wen CKC, "Patterns of recruitment and microhabitat associations for three predatory coral reef fishes on the southern Great Barrier Reef, Australia", Coral Reefs, 32, pp.389~398 (2013)
- Williams ID, "Can herbivore management increase the persistence of Indo-Pacific coral reefs?", Front Mar Sci, 6, pp.557~ (2019)
- Wismer S, "Young fishes persist despite coral loss on the Great Barrier Reef", Commun Biol, 2, pp.456~ (2019)
- Wolfe K, "The biology and ecology of coral rubble and implications for the future of coral reefs", Coral Reefs, 40, pp.1769~1806 (2021)
- Yulianto I, "Improvement of fish length estimates for underwater visual census of reef fish biomass", J Appl Ichthyol, 31, pp.308~314 (2015)