Published Objects Coral reef benthic and fish surveys in Papua New Guinea fascinator 5c6a9ae1867f83a35916e341f730290d 2019-03-15T12:53:43Z ["<p>Surveys of reef sites in fished versus tabu (community closures) areas in both Madang and Manus Provinces, Papua New Guinea. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>Surveys of reef sites in fished versus tabu (community closures) areas in both Madang and Manus Provinces, Papua New Guinea. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "brief", "<p>These surveys were conducted in 2009 by Nick Graham and Fraser Januchowski-Hartley of James Cook University. At each site replicate 50m transects were surveyed at both 8m and 2m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location tabu areas had been closed for varying lengths of time and were either fished for feasts annually or opened for longer periods of time. The data are being used to evaluate these management systems and to link to socio-economic data collected by Joshua Cinner at these and other sites.</p>", "<p>These surveys were conducted in 2009 by Nick Graham and Fraser Januchowski-Hartley of James Cook University. At each site replicate 50m transects were surveyed at both 8m and 2m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location tabu areas had been closed for varying lengths of time and were either fished for feasts annually or opened for longer periods of time. The data are being used to evaluate these management systems and to link to socio-economic data collected by Joshua Cinner at these and other sites.</p>", "full", "full", ""] ["<p>Surveys of reef sites in fished versus tabu (community closures) areas in both Madang and Manus Provinces, Papua New Guinea. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>Surveys of reef sites in fished versus tabu (community closures) areas in both Madang and Manus Provinces, Papua New Guinea. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "brief", "<p>These surveys were conducted in 2009 by Nick Graham and Fraser Januchowski-Hartley of James Cook University. At each site replicate 50m transects were surveyed at both 8m and 2m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location tabu areas had been closed for varying lengths of time and were either fished for feasts annually or opened for longer periods of time. The data are being used to evaluate these management systems and to link to socio-economic data collected by Joshua Cinner at these and other sites.</p>", "<p>These surveys were conducted in 2009 by Nick Graham and Fraser Januchowski-Hartley of James Cook University. At each site replicate 50m transects were surveyed at both 8m and 2m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location tabu areas had been closed for varying lengths of time and were either fished for feasts annually or opened for longer periods of time. The data are being used to evaluate these management systems and to link to socio-economic data collected by Joshua Cinner at these and other sites.</p>", "full", "full", ""] Coral reef benthic and fish surveys in the Chagos Archipelago fascinator 546ce1571827d60996dc5a539410a948 2019-03-15T12:57:10Z ["<p>Surveys of 18 reef sites around the northern atolls of the Chagos Archipelago, British Indian Ocean Territory. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>Surveys of 18 reef sites around the northern atolls of the Chagos Archipelago, British Indian Ocean Territory. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "brief", "<p>These surveys were conducted in 2010 by Nick Graham and Morgan Pratchett of James Cook University. At each of the 18 sites 4 replicate 50m transects were surveyed at both 9m and 3m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location has been largely unfished and uninhabited since the early 1970’s. The data are being used to make comparisons to other reef systems across the Indian Ocean to assess this fairly pristine site to more degraded reefs elsewhere.</p>", "<p>These surveys were conducted in 2010 by Nick Graham and Morgan Pratchett of James Cook University. At each of the 18 sites 4 replicate 50m transects were surveyed at both 9m and 3m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location has been largely unfished and uninhabited since the early 1970’s. The data are being used to make comparisons to other reef systems across the Indian Ocean to assess this fairly pristine site to more degraded reefs elsewhere.</p>", "full", "full", ""] ["<p>Surveys of 18 reef sites around the northern atolls of the Chagos Archipelago, British Indian Ocean Territory. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>Surveys of 18 reef sites around the northern atolls of the Chagos Archipelago, British Indian Ocean Territory. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "brief", "<p>These surveys were conducted in 2010 by Nick Graham and Morgan Pratchett of James Cook University. At each of the 18 sites 4 replicate 50m transects were surveyed at both 9m and 3m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location has been largely unfished and uninhabited since the early 1970’s. The data are being used to make comparisons to other reef systems across the Indian Ocean to assess this fairly pristine site to more degraded reefs elsewhere.</p>", "<p>These surveys were conducted in 2010 by Nick Graham and Morgan Pratchett of James Cook University. At each of the 18 sites 4 replicate 50m transects were surveyed at both 9m and 3m depth. Coral and other benthic cover were surveyed using point intercept methodology, while fish were surveyed using 50*5m belt transect UVC. The location has been largely unfished and uninhabited since the early 1970’s. The data are being used to make comparisons to other reef systems across the Indian Ocean to assess this fairly pristine site to more degraded reefs elsewhere.</p>", "full", "full", ""] Coral reef benthic and fish surveys in the Inner Seychelles fascinator a858bdc7a8116bff35db8558a25c2cb7 2019-03-15T12:55:21Z ["brief", "full", "full", "<p>Surveys of 21 reef sites around the inner granitic islands of the Seychelles. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>Surveys of 21 reef sites around the inner granitic islands of the Seychelles. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>These surveys were first conducted in 1994 by Simon Jennings, now at the Centre for Environment, Fisheries and Aquaculture Science in the UK, and have been subsequently repeated in 2005, 2008 and 2011 by Nick Graham of James Cook University and Shaun Wilson, now at the Western Australian Department for Environment and Conservation. In each year 7 sites on granitic reefs, 7 sites on continuous carbonate reefs, and 7 sites on patch reefs were surveyed. 16 replicate surveys were conducted at each reef site. 9 of the 21 sites are within no-take marine protected areas, while the remaining 12 sites are open to fishing. The data have been used to assess the effectiveness of fisheries management in Seychelles, and more recently to evaluate the impact of the 1998 climate change driven coral mortality event which killed up to 90% of the corals on these reefs.</p>", "<p>These surveys were first conducted in 1994 by Simon Jennings, now at the Centre for Environment, Fisheries and Aquaculture Science in the UK, and have been subsequently repeated in 2005, 2008 and 2011 by Nick Graham of James Cook University and Shaun Wilson, now at the Western Australian Department for Environment and Conservation. In each year 7 sites on granitic reefs, 7 sites on continuous carbonate reefs, and 7 sites on patch reefs were surveyed. 16 replicate surveys were conducted at each reef site. 9 of the 21 sites are within no-take marine protected areas, while the remaining 12 sites are open to fishing. The data have been used to assess the effectiveness of fisheries management in Seychelles, and more recently to evaluate the impact of the 1998 climate change driven coral mortality event which killed up to 90% of the corals on these reefs.</p>", ""] ["brief", "full", "full", "<p>Surveys of 21 reef sites around the inner granitic islands of the Seychelles. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>Surveys of 21 reef sites around the inner granitic islands of the Seychelles. Benthic cover of corals and other organisms were quantified along with the abundance diversity and size of reef associated fishes.</p>", "<p>These surveys were first conducted in 1994 by Simon Jennings, now at the Centre for Environment, Fisheries and Aquaculture Science in the UK, and have been subsequently repeated in 2005, 2008 and 2011 by Nick Graham of James Cook University and Shaun Wilson, now at the Western Australian Department for Environment and Conservation. In each year 7 sites on granitic reefs, 7 sites on continuous carbonate reefs, and 7 sites on patch reefs were surveyed. 16 replicate surveys were conducted at each reef site. 9 of the 21 sites are within no-take marine protected areas, while the remaining 12 sites are open to fishing. The data have been used to assess the effectiveness of fisheries management in Seychelles, and more recently to evaluate the impact of the 1998 climate change driven coral mortality event which killed up to 90% of the corals on these reefs.</p>", "<p>These surveys were first conducted in 1994 by Simon Jennings, now at the Centre for Environment, Fisheries and Aquaculture Science in the UK, and have been subsequently repeated in 2005, 2008 and 2011 by Nick Graham of James Cook University and Shaun Wilson, now at the Western Australian Department for Environment and Conservation. In each year 7 sites on granitic reefs, 7 sites on continuous carbonate reefs, and 7 sites on patch reefs were surveyed. 16 replicate surveys were conducted at each reef site. 9 of the 21 sites are within no-take marine protected areas, while the remaining 12 sites are open to fishing. The data have been used to assess the effectiveness of fisheries management in Seychelles, and more recently to evaluate the impact of the 1998 climate change driven coral mortality event which killed up to 90% of the corals on these reefs.</p>", ""] Cross-scale habitat structure driven by coral species composition on tropical reefs fascinator f92a4e6836efc5daaae62c4910fb7994 2020-08-13T04:39:56Z ["<p>This data set contains observational data collected at Lizard Island, Great Barrier Reef, Australia in September 2015: Tab 1: Structural complexity data Tab 2: Benthic composition data</p><p>The full methodology is available in the Open Access publication from the Related Publications link below.</p>", "<p>This data set contains observational data collected at Lizard Island, Great Barrier Reef, Australia in September 2015: Tab 1: Structural complexity data Tab 2: Benthic composition data</p><p>The full methodology is available in the Open Access publication from the Related Publications link below.</p>", "brief", "<p>This dataset is available as a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "<p>This dataset is available as a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "note", ""] ["<p>This data set contains observational data collected at Lizard Island, Great Barrier Reef, Australia in September 2015: Tab 1: Structural complexity data Tab 2: Benthic composition data</p><p>The full methodology is available in the Open Access publication from the Related Publications link below.</p>", "<p>This data set contains observational data collected at Lizard Island, Great Barrier Reef, Australia in September 2015: Tab 1: Structural complexity data Tab 2: Benthic composition data</p><p>The full methodology is available in the Open Access publication from the Related Publications link below.</p>", "brief", "<p>This dataset is available as a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "<p>This dataset is available as a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "note", ""] Data from: Regime shifts shorten food chains for mesopredators with potential sublethal effects fascinator fb2a6bb29c03f974911bed50b5c7f2dd 2019-03-15T12:55:05Z ["<p>Dryad dataset consists of morphological, stable isotope, gut content and lipid data for Cephalopholis argus collected in the Seychelles Inner Island group.</p><p>Abstract [Related Publication]: 1. Predator populations are in decline globally. Exploitation, as well as habitat degradation and associated changes in prey availability are key drivers of this process of trophic downgrading. In the short term, longevity and dietary adaptability of large-bodied consumers can mask potential sub-lethal effects of a changing prey base, producing a delayed effect that may be difficult to detect.</p><p>2. In coral reef ecosystems, regime shifts from coral- to algae-dominated states caused by coral bleaching significantly alter the assemblage of small-bodied reef fish associated with a reef. The effects of this changing prey community on reef-associated mesopredators remains poorly understood.</p><p>3. This study found that the total diversity, abundance and biomass of piscivorous mesopredators was lower on regime-shifted reefs than recovering reefs, 16 years after the 1998 mass coral bleaching event.</p><p>4. We used stable isotope analyses to test for habitat-driven changes in the trophic niche occupied by a key piscivorous fishery target species on reefs that had regime-shifted or recovered following climatic disturbance. Using morphometric indices, histology, and lipid analyses, we also investigated whether there were sub-lethal costs for fish on regime-shifted reefs.</p><p>5. Stable isotopes demonstrated that fish from regime-shifted reefs fed further down the food chain, compared to recovering reefs. Lower densities of hepatocyte vacuoles in fish from regime-shifted reefs, and reduced lipid concentrations in spawning females from these reefs, indicated a reduction in energy stores, constituting a sub-lethal and potential delayed effect on populations.</p><p>6. Reduced energy reserves in mesopredators could lead to energy allocation trade-offs, and decreased growth rates, fecundity, and survivorship, resulting in potential population declines in the longer term.</p><p>The full methodology is available in the publication shown in the Related Publications link below.</p>", "full", "<p>Dryad dataset consists of morphological, stable isotope, gut content and lipid data for Cephalopholis argus collected in the Seychelles Inner Island group.</p><p>Abstract [Related Publication]: 1. Predator populations are in decline globally. Exploitation, as well as habitat degradation and associated changes in prey availability are key drivers of this process of trophic downgrading. In the short term, longevity and dietary adaptability of large-bodied consumers can mask potential sub-lethal effects of a changing prey base, producing a delayed effect that may be difficult to detect.</p><p>2. In coral reef ecosystems, regime shifts from coral- to algae-dominated states caused by coral bleaching significantly alter the assemblage of small-bodied reef fish associated with a reef. The effects of this changing prey community on reef-associated mesopredators remains poorly understood.</p><p>3. This study found that the total diversity, abundance and biomass of piscivorous mesopredators was lower on regime-shifted reefs than recovering reefs, 16 years after the 1998 mass coral bleaching event.</p><p>4. We used stable isotope analyses to test for habitat-driven changes in the trophic niche occupied by a key piscivorous fishery target species on reefs that had regime-shifted or recovered following climatic disturbance. Using morphometric indices, histology, and lipid analyses, we also investigated whether there were sub-lethal costs for fish on regime-shifted reefs.</p><p>5. Stable isotopes demonstrated that fish from regime-shifted reefs fed further down the food chain, compared to recovering reefs. Lower densities of hepatocyte vacuoles in fish from regime-shifted reefs, and reduced lipid concentrations in spawning females from these reefs, indicated a reduction in energy stores, constituting a sub-lethal and potential delayed effect on populations.</p><p>6. Reduced energy reserves in mesopredators could lead to energy allocation trade-offs, and decreased growth rates, fecundity, and survivorship, resulting in potential population declines in the longer term.</p><p>The full methodology is available in the publication shown in the Related Publications link below.</p>", "<p>This data set is available from Dryad in MS Excel (.xlsx) format. Dryad data package: Hempson TN, Graham NAJ, MacNeil AM, Bodin N, Wilson SK (2017) Data from: Regime shifts shorten food chains for mesopredators with potential sublethal effects. Dryad Digital Repository. <a href="https://doi.org/10.5061/dryad.bq4nn">https://doi.org/10.5061/dryad.bq4nn</a></p>", "note", "<p>This data set is available from Dryad in MS Excel (.xlsx) format. Dryad data package: Hempson TN, Graham NAJ, MacNeil AM, Bodin N, Wilson SK (2017) Data from: Regime shifts shorten food chains for mesopredators with potential sublethal effects. Dryad Digital Repository. <a href="https://doi.org/10.5061/dryad.bq4nn">https://doi.org/10.5061/dryad.bq4nn</a></p>", ""] ["<p>Dryad dataset consists of morphological, stable isotope, gut content and lipid data for Cephalopholis argus collected in the Seychelles Inner Island group.</p><p>Abstract [Related Publication]: 1. Predator populations are in decline globally. Exploitation, as well as habitat degradation and associated changes in prey availability are key drivers of this process of trophic downgrading. In the short term, longevity and dietary adaptability of large-bodied consumers can mask potential sub-lethal effects of a changing prey base, producing a delayed effect that may be difficult to detect.</p><p>2. In coral reef ecosystems, regime shifts from coral- to algae-dominated states caused by coral bleaching significantly alter the assemblage of small-bodied reef fish associated with a reef. The effects of this changing prey community on reef-associated mesopredators remains poorly understood.</p><p>3. This study found that the total diversity, abundance and biomass of piscivorous mesopredators was lower on regime-shifted reefs than recovering reefs, 16 years after the 1998 mass coral bleaching event.</p><p>4. We used stable isotope analyses to test for habitat-driven changes in the trophic niche occupied by a key piscivorous fishery target species on reefs that had regime-shifted or recovered following climatic disturbance. Using morphometric indices, histology, and lipid analyses, we also investigated whether there were sub-lethal costs for fish on regime-shifted reefs.</p><p>5. Stable isotopes demonstrated that fish from regime-shifted reefs fed further down the food chain, compared to recovering reefs. Lower densities of hepatocyte vacuoles in fish from regime-shifted reefs, and reduced lipid concentrations in spawning females from these reefs, indicated a reduction in energy stores, constituting a sub-lethal and potential delayed effect on populations.</p><p>6. Reduced energy reserves in mesopredators could lead to energy allocation trade-offs, and decreased growth rates, fecundity, and survivorship, resulting in potential population declines in the longer term.</p><p>The full methodology is available in the publication shown in the Related Publications link below.</p>", "full", "<p>Dryad dataset consists of morphological, stable isotope, gut content and lipid data for Cephalopholis argus collected in the Seychelles Inner Island group.</p><p>Abstract [Related Publication]: 1. Predator populations are in decline globally. Exploitation, as well as habitat degradation and associated changes in prey availability are key drivers of this process of trophic downgrading. In the short term, longevity and dietary adaptability of large-bodied consumers can mask potential sub-lethal effects of a changing prey base, producing a delayed effect that may be difficult to detect.</p><p>2. In coral reef ecosystems, regime shifts from coral- to algae-dominated states caused by coral bleaching significantly alter the assemblage of small-bodied reef fish associated with a reef. The effects of this changing prey community on reef-associated mesopredators remains poorly understood.</p><p>3. This study found that the total diversity, abundance and biomass of piscivorous mesopredators was lower on regime-shifted reefs than recovering reefs, 16 years after the 1998 mass coral bleaching event.</p><p>4. We used stable isotope analyses to test for habitat-driven changes in the trophic niche occupied by a key piscivorous fishery target species on reefs that had regime-shifted or recovered following climatic disturbance. Using morphometric indices, histology, and lipid analyses, we also investigated whether there were sub-lethal costs for fish on regime-shifted reefs.</p><p>5. Stable isotopes demonstrated that fish from regime-shifted reefs fed further down the food chain, compared to recovering reefs. Lower densities of hepatocyte vacuoles in fish from regime-shifted reefs, and reduced lipid concentrations in spawning females from these reefs, indicated a reduction in energy stores, constituting a sub-lethal and potential delayed effect on populations.</p><p>6. Reduced energy reserves in mesopredators could lead to energy allocation trade-offs, and decreased growth rates, fecundity, and survivorship, resulting in potential population declines in the longer term.</p><p>The full methodology is available in the publication shown in the Related Publications link below.</p>", "<p>This data set is available from Dryad in MS Excel (.xlsx) format. Dryad data package: Hempson TN, Graham NAJ, MacNeil AM, Bodin N, Wilson SK (2017) Data from: Regime shifts shorten food chains for mesopredators with potential sublethal effects. Dryad Digital Repository. <a href="https://doi.org/10.5061/dryad.bq4nn">https://doi.org/10.5061/dryad.bq4nn</a></p>", "note", "<p>This data set is available from Dryad in MS Excel (.xlsx) format. Dryad data package: Hempson TN, Graham NAJ, MacNeil AM, Bodin N, Wilson SK (2017) Data from: Regime shifts shorten food chains for mesopredators with potential sublethal effects. Dryad Digital Repository. <a href="https://doi.org/10.5061/dryad.bq4nn">https://doi.org/10.5061/dryad.bq4nn</a></p>", ""] Expert interview data for a risk assessment of spawning aggregation fisheries fascinator f50d493d62a314b4a37ba1df1e7fde46 2019-03-15T12:57:51Z ["<p>A predictive framework was developed for assessing risk of overfishing in spawning aggregation fisheries. The bivariate framework is based on intrinsic and extrinsic indicators, for which scales of vulnerability were developed. A global selection of fisheries was assessed by experts, who scored each indicator during interviews. This dataset contains those expert scores. Also, indicators were weighted for their importance in terms of conferring vulnerability to overfishing. Weightings are also included in the dataset. </p>", "<p>A predictive framework was developed for assessing risk of overfishing in spawning aggregation fisheries. The bivariate framework is based on intrinsic and extrinsic indicators, for which scales of vulnerability were developed. A global selection of fisheries was assessed by experts, who scored each indicator during interviews. This dataset contains those expert scores. Also, indicators were weighted for their importance in terms of conferring vulnerability to overfishing. Weightings are also included in the dataset. </p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "note", ""] ["<p>A predictive framework was developed for assessing risk of overfishing in spawning aggregation fisheries. The bivariate framework is based on intrinsic and extrinsic indicators, for which scales of vulnerability were developed. A global selection of fisheries was assessed by experts, who scored each indicator during interviews. This dataset contains those expert scores. Also, indicators were weighted for their importance in terms of conferring vulnerability to overfishing. Weightings are also included in the dataset. </p>", "<p>A predictive framework was developed for assessing risk of overfishing in spawning aggregation fisheries. The bivariate framework is based on intrinsic and extrinsic indicators, for which scales of vulnerability were developed. A global selection of fisheries was assessed by experts, who scored each indicator during interviews. This dataset contains those expert scores. Also, indicators were weighted for their importance in terms of conferring vulnerability to overfishing. Weightings are also included in the dataset. </p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "note", ""] Multi-species grouper spawning aggregation fishery study in Papua New Guinea fascinator bc1f7ce02cd02469db9127ee084b7e29 2020-08-12T02:38:21Z ["<p>This dataset contains spawning aggregation fish density and fishery data for two species of grouper (Epinephelus fuscoguttatus and E. polyphekadion) at a site in New Ireland Province, Papua New Guinea. Over two spawning months in 2013, fish aggregation density was estimated by divers conducting (point-count) underwater visual census surveys. A fishery targeting the two species of grouper at the spawning site was observed over the same period, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes numbers of boats and fishers, hook size, and depth of fishing for catches.</p>", "<p>This dataset contains spawning aggregation fish density and fishery data for two species of grouper (Epinephelus fuscoguttatus and E. polyphekadion) at a site in New Ireland Province, Papua New Guinea. Over two spawning months in 2013, fish aggregation density was estimated by divers conducting (point-count) underwater visual census surveys. A fishery targeting the two species of grouper at the spawning site was observed over the same period, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes numbers of boats and fishers, hook size, and depth of fishing for catches.</p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "note", ""] ["<p>This dataset contains spawning aggregation fish density and fishery data for two species of grouper (Epinephelus fuscoguttatus and E. polyphekadion) at a site in New Ireland Province, Papua New Guinea. Over two spawning months in 2013, fish aggregation density was estimated by divers conducting (point-count) underwater visual census surveys. A fishery targeting the two species of grouper at the spawning site was observed over the same period, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes numbers of boats and fishers, hook size, and depth of fishing for catches.</p>", "<p>This dataset contains spawning aggregation fish density and fishery data for two species of grouper (Epinephelus fuscoguttatus and E. polyphekadion) at a site in New Ireland Province, Papua New Guinea. Over two spawning months in 2013, fish aggregation density was estimated by divers conducting (point-count) underwater visual census surveys. A fishery targeting the two species of grouper at the spawning site was observed over the same period, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes numbers of boats and fishers, hook size, and depth of fishing for catches.</p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document format (.ods)</p>", "note", ""] PhD thesis data: Variation in structure and function of reef fish assemblages among distinct coral habitats, by Laura E. Richardson (2018) fascinator 4cf8d8690a368dab419385d5746e0fb2 2020-03-02T07:00:31Z ["<p>Dataset for phD thesis: Variation in structure and function of reef fish assemblages among distinct coral habitats, by Laura E. Richardson (2018)</p>", "brief", "<p>Dataset for phD thesis: Variation in structure and function of reef fish assemblages among distinct coral habitats, by Laura E. Richardson (2018)</p>", "<p><strong>Introduction [from the Thesis Abstract]:</strong> Anthropogenic disturbances are altering the abundance and distribution of organisms across biomes, disrupting the function and stability of ecosystems, and the goods and services they provide. On tropical coral reefs, global climate change and a range of local stressors are reducing populations of habitat-building corals, resulting in unprecedented coral loss and marked shifts in coral species dominance due to differential susceptibilities of coral taxa to disturbance. However, the extent to which shifts in coral species composition will alter the organization of associated organisms and undermine the resilience of coral reefs remains unclear. This thesis exploited a natural experiment on reefs surrounding Lizard Island, Australia, where multiple taxonomically distinct coral habitats existed, characterised by dominance of differing coral taxa, to assess the influence of coral species composition on the structure, function and resilience of reef fish assemblages. Specifically, the four data chapters of this thesis (2–5) addressed the following questions: (1) How does coral species composition affect the cross-scale structural complexity of coral reef habitats? (2) How does the functional diversity of reef fish assemblages vary among taxonomically distinct coral habitats? (3) To what extent does pre-disturbance coral species composition influence the susceptibility of reef fish assemblages to coral bleaching events? (4) Do critical herbivory functions (browsing and grazing) vary among distinct coral habitats?</p><p>This data collection consists of a spreadsheet saved in both MS Excel (.xlsx) and Open Document (.ods) formats. The files contain 18 worksheets for the data chapters 2-5:</p><p><strong>Chapter 2: Cross-scale habitat structure driven by coral species composition on tropical reefs</strong></p><ul><li>Ch2 Benthos data</li><li>Ch2 cross-scale complexity</li></ul><p>This data has been previously published in the Tropical Data Hub and is available from the link below. The full methodology is available from the 'Related Publication' link. </p><p>Richardson, L. (2017). Cross-scale habitat structure driven by coral species composition on tropical reefs. James Cook University. [Data Files] <a href="http://dx.doi.org/10.4225/28/593893efcb5cb">http://dx.doi.org/10.4225/28/593893efcb5cb</a></p><p><strong>Chapter 3: Structural complexity mediates functional structure of reef fish assemblages among coral habitats</strong></p><ul><li>Ch3 site info</li><li>Ch3 benthos data</li><li>Ch3 fish data</li><li>Ch3 traits matrix</li><li>Ch 3 benthos diversity</li><li>Ch3 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 4: Mass coral bleaching causes biotic homogenization of reef fish assemblages</strong></p><ul><li>Ch4 benthos data</li><li>Ch4 fish data</li><li>Ch4 traits matrix</li><li>Ch4 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 5: Differential response of key ecosystem processes to coral composition</strong></p><ul><li>Ch5 benthos data</li><li>Ch5 herbivore fish data</li><li>Ch5 assay data</li><li>Ch5 MA [macroalgal assay] video bite rates</li><li>Ch5 turf assay data</li><li>Ch5 productivity data - unused</li></ul><p>The full methodology is available in the author's thesis and in the Related Publication (published in the Proceedings of the Royal Society B: Biological Sciences, 2020)</p>", "full", "<p><strong>Introduction [from the Thesis Abstract]:</strong> Anthropogenic disturbances are altering the abundance and distribution of organisms across biomes, disrupting the function and stability of ecosystems, and the goods and services they provide. On tropical coral reefs, global climate change and a range of local stressors are reducing populations of habitat-building corals, resulting in unprecedented coral loss and marked shifts in coral species dominance due to differential susceptibilities of coral taxa to disturbance. However, the extent to which shifts in coral species composition will alter the organization of associated organisms and undermine the resilience of coral reefs remains unclear. This thesis exploited a natural experiment on reefs surrounding Lizard Island, Australia, where multiple taxonomically distinct coral habitats existed, characterised by dominance of differing coral taxa, to assess the influence of coral species composition on the structure, function and resilience of reef fish assemblages. Specifically, the four data chapters of this thesis (2–5) addressed the following questions: (1) How does coral species composition affect the cross-scale structural complexity of coral reef habitats? (2) How does the functional diversity of reef fish assemblages vary among taxonomically distinct coral habitats? (3) To what extent does pre-disturbance coral species composition influence the susceptibility of reef fish assemblages to coral bleaching events? (4) Do critical herbivory functions (browsing and grazing) vary among distinct coral habitats?</p><p>This data collection consists of a spreadsheet saved in both MS Excel (.xlsx) and Open Document (.ods) formats. The files contain 18 worksheets for the data chapters 2-5:</p><p><strong>Chapter 2: Cross-scale habitat structure driven by coral species composition on tropical reefs</strong></p><ul><li>Ch2 Benthos data</li><li>Ch2 cross-scale complexity</li></ul><p>This data has been previously published in the Tropical Data Hub and is available from the link below. The full methodology is available from the 'Related Publication' link. </p><p>Richardson, L. (2017). Cross-scale habitat structure driven by coral species composition on tropical reefs. James Cook University. [Data Files] <a href="http://dx.doi.org/10.4225/28/593893efcb5cb">http://dx.doi.org/10.4225/28/593893efcb5cb</a></p><p><strong>Chapter 3: Structural complexity mediates functional structure of reef fish assemblages among coral habitats</strong></p><ul><li>Ch3 site info</li><li>Ch3 benthos data</li><li>Ch3 fish data</li><li>Ch3 traits matrix</li><li>Ch 3 benthos diversity</li><li>Ch3 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 4: Mass coral bleaching causes biotic homogenization of reef fish assemblages</strong></p><ul><li>Ch4 benthos data</li><li>Ch4 fish data</li><li>Ch4 traits matrix</li><li>Ch4 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 5: Differential response of key ecosystem processes to coral composition</strong></p><ul><li>Ch5 benthos data</li><li>Ch5 herbivore fish data</li><li>Ch5 assay data</li><li>Ch5 MA [macroalgal assay] video bite rates</li><li>Ch5 turf assay data</li><li>Ch5 productivity data - unused</li></ul><p>The full methodology is available in the author's thesis and in the Related Publication (published in the Proceedings of the Royal Society B: Biological Sciences, 2020)</p>", ""] ["<p>Dataset for phD thesis: Variation in structure and function of reef fish assemblages among distinct coral habitats, by Laura E. Richardson (2018)</p>", "brief", "<p>Dataset for phD thesis: Variation in structure and function of reef fish assemblages among distinct coral habitats, by Laura E. Richardson (2018)</p>", "<p><strong>Introduction [from the Thesis Abstract]:</strong> Anthropogenic disturbances are altering the abundance and distribution of organisms across biomes, disrupting the function and stability of ecosystems, and the goods and services they provide. On tropical coral reefs, global climate change and a range of local stressors are reducing populations of habitat-building corals, resulting in unprecedented coral loss and marked shifts in coral species dominance due to differential susceptibilities of coral taxa to disturbance. However, the extent to which shifts in coral species composition will alter the organization of associated organisms and undermine the resilience of coral reefs remains unclear. This thesis exploited a natural experiment on reefs surrounding Lizard Island, Australia, where multiple taxonomically distinct coral habitats existed, characterised by dominance of differing coral taxa, to assess the influence of coral species composition on the structure, function and resilience of reef fish assemblages. Specifically, the four data chapters of this thesis (2–5) addressed the following questions: (1) How does coral species composition affect the cross-scale structural complexity of coral reef habitats? (2) How does the functional diversity of reef fish assemblages vary among taxonomically distinct coral habitats? (3) To what extent does pre-disturbance coral species composition influence the susceptibility of reef fish assemblages to coral bleaching events? (4) Do critical herbivory functions (browsing and grazing) vary among distinct coral habitats?</p><p>This data collection consists of a spreadsheet saved in both MS Excel (.xlsx) and Open Document (.ods) formats. The files contain 18 worksheets for the data chapters 2-5:</p><p><strong>Chapter 2: Cross-scale habitat structure driven by coral species composition on tropical reefs</strong></p><ul><li>Ch2 Benthos data</li><li>Ch2 cross-scale complexity</li></ul><p>This data has been previously published in the Tropical Data Hub and is available from the link below. The full methodology is available from the 'Related Publication' link. </p><p>Richardson, L. (2017). Cross-scale habitat structure driven by coral species composition on tropical reefs. James Cook University. [Data Files] <a href="http://dx.doi.org/10.4225/28/593893efcb5cb">http://dx.doi.org/10.4225/28/593893efcb5cb</a></p><p><strong>Chapter 3: Structural complexity mediates functional structure of reef fish assemblages among coral habitats</strong></p><ul><li>Ch3 site info</li><li>Ch3 benthos data</li><li>Ch3 fish data</li><li>Ch3 traits matrix</li><li>Ch 3 benthos diversity</li><li>Ch3 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 4: Mass coral bleaching causes biotic homogenization of reef fish assemblages</strong></p><ul><li>Ch4 benthos data</li><li>Ch4 fish data</li><li>Ch4 traits matrix</li><li>Ch4 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 5: Differential response of key ecosystem processes to coral composition</strong></p><ul><li>Ch5 benthos data</li><li>Ch5 herbivore fish data</li><li>Ch5 assay data</li><li>Ch5 MA [macroalgal assay] video bite rates</li><li>Ch5 turf assay data</li><li>Ch5 productivity data - unused</li></ul><p>The full methodology is available in the author's thesis and in the Related Publication (published in the Proceedings of the Royal Society B: Biological Sciences, 2020)</p>", "full", "<p><strong>Introduction [from the Thesis Abstract]:</strong> Anthropogenic disturbances are altering the abundance and distribution of organisms across biomes, disrupting the function and stability of ecosystems, and the goods and services they provide. On tropical coral reefs, global climate change and a range of local stressors are reducing populations of habitat-building corals, resulting in unprecedented coral loss and marked shifts in coral species dominance due to differential susceptibilities of coral taxa to disturbance. However, the extent to which shifts in coral species composition will alter the organization of associated organisms and undermine the resilience of coral reefs remains unclear. This thesis exploited a natural experiment on reefs surrounding Lizard Island, Australia, where multiple taxonomically distinct coral habitats existed, characterised by dominance of differing coral taxa, to assess the influence of coral species composition on the structure, function and resilience of reef fish assemblages. Specifically, the four data chapters of this thesis (2–5) addressed the following questions: (1) How does coral species composition affect the cross-scale structural complexity of coral reef habitats? (2) How does the functional diversity of reef fish assemblages vary among taxonomically distinct coral habitats? (3) To what extent does pre-disturbance coral species composition influence the susceptibility of reef fish assemblages to coral bleaching events? (4) Do critical herbivory functions (browsing and grazing) vary among distinct coral habitats?</p><p>This data collection consists of a spreadsheet saved in both MS Excel (.xlsx) and Open Document (.ods) formats. The files contain 18 worksheets for the data chapters 2-5:</p><p><strong>Chapter 2: Cross-scale habitat structure driven by coral species composition on tropical reefs</strong></p><ul><li>Ch2 Benthos data</li><li>Ch2 cross-scale complexity</li></ul><p>This data has been previously published in the Tropical Data Hub and is available from the link below. The full methodology is available from the 'Related Publication' link. </p><p>Richardson, L. (2017). Cross-scale habitat structure driven by coral species composition on tropical reefs. James Cook University. [Data Files] <a href="http://dx.doi.org/10.4225/28/593893efcb5cb">http://dx.doi.org/10.4225/28/593893efcb5cb</a></p><p><strong>Chapter 3: Structural complexity mediates functional structure of reef fish assemblages among coral habitats</strong></p><ul><li>Ch3 site info</li><li>Ch3 benthos data</li><li>Ch3 fish data</li><li>Ch3 traits matrix</li><li>Ch 3 benthos diversity</li><li>Ch3 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 4: Mass coral bleaching causes biotic homogenization of reef fish assemblages</strong></p><ul><li>Ch4 benthos data</li><li>Ch4 fish data</li><li>Ch4 traits matrix</li><li>Ch4 FD [functional diversity] data</li></ul><p>The full methodology is available in the Related Publication.</p><p><strong>Chapter 5: Differential response of key ecosystem processes to coral composition</strong></p><ul><li>Ch5 benthos data</li><li>Ch5 herbivore fish data</li><li>Ch5 assay data</li><li>Ch5 MA [macroalgal assay] video bite rates</li><li>Ch5 turf assay data</li><li>Ch5 productivity data - unused</li></ul><p>The full methodology is available in the author's thesis and in the Related Publication (published in the Proceedings of the Royal Society B: Biological Sciences, 2020)</p>", ""] Rabbitfish fishery and spawning aggregation surveys in the Seychelles fascinator 9c5e42533362311d376cecf071f3f1fc 2019-03-15T12:57:57Z ["<p>This dataset contains fish density and fishery data for a rabbitfish species (Siganus sutor) in the Republic of Seychelles. Fish density was estimated at spawning aggregations and in non-reproductive habitat between November 2013 and May 2014 using 20 min timed-swim surveys by divers using stereo-video. From 60 random samples of resulting video frames, two metrics of density were derived: MaxN and Presence. On the same days as fish density surveys, observations of two fishers targeting the species using fish traps were also undertaken, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes fishing effort density, soak time, trap type and fishing depth. Underwater visibility data were also derived from survey video data, while an index of current strength was derived from satellite altimeter and scatterometer data.</p>", "<p>This dataset contains fish density and fishery data for a rabbitfish species (Siganus sutor) in the Republic of Seychelles. Fish density was estimated at spawning aggregations and in non-reproductive habitat between November 2013 and May 2014 using 20 min timed-swim surveys by divers using stereo-video. From 60 random samples of resulting video frames, two metrics of density were derived: MaxN and Presence. On the same days as fish density surveys, observations of two fishers targeting the species using fish traps were also undertaken, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes fishing effort density, soak time, trap type and fishing depth. Underwater visibility data were also derived from survey video data, while an index of current strength was derived from satellite altimeter and scatterometer data.</p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "note", ""] ["<p>This dataset contains fish density and fishery data for a rabbitfish species (Siganus sutor) in the Republic of Seychelles. Fish density was estimated at spawning aggregations and in non-reproductive habitat between November 2013 and May 2014 using 20 min timed-swim surveys by divers using stereo-video. From 60 random samples of resulting video frames, two metrics of density were derived: MaxN and Presence. On the same days as fish density surveys, observations of two fishers targeting the species using fish traps were also undertaken, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes fishing effort density, soak time, trap type and fishing depth. Underwater visibility data were also derived from survey video data, while an index of current strength was derived from satellite altimeter and scatterometer data.</p>", "<p>This dataset contains fish density and fishery data for a rabbitfish species (Siganus sutor) in the Republic of Seychelles. Fish density was estimated at spawning aggregations and in non-reproductive habitat between November 2013 and May 2014 using 20 min timed-swim surveys by divers using stereo-video. From 60 random samples of resulting video frames, two metrics of density were derived: MaxN and Presence. On the same days as fish density surveys, observations of two fishers targeting the species using fish traps were also undertaken, with individual fisher catch and effort data collected and used to estimate catch-per-unit-effort. Other fishery information collected includes fishing effort density, soak time, trap type and fishing depth. Underwater visibility data were also derived from survey video data, while an index of current strength was derived from satellite altimeter and scatterometer data.</p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "note", ""] The role of fisher knowledge on the susceptibility of spawning aggregations to fishing: interview data from Papua New Guinea fascinator ac1cc727b5a795e16f31faa87c8cd8e8 2019-03-15T12:55:46Z ["<p>Data from interview-based survey of small-scale fishers in Papua New Guinea</p>", "<p>Data from interview-based survey of small-scale fishers in Papua New Guinea</p>", "brief", "<p>Structured interviews designed to assess fisher knowledge of reef fish aggregation behaviour, to collect information on fishing practices and to score key socioeconomic variables. The study was designed to assess the role of fisher knowledge in conferring vulnerability of fish aggregations to fishing and to quantify factors associated with heterogeneity in knowledge. Small-scale fishers were surveyed in the communities of Ahus island (Manus Province), Wadau and Muluk (Karkar island, Madang Province) in October 2012. </p>", "<p>Structured interviews designed to assess fisher knowledge of reef fish aggregation behaviour, to collect information on fishing practices and to score key socioeconomic variables. The study was designed to assess the role of fisher knowledge in conferring vulnerability of fish aggregations to fishing and to quantify factors associated with heterogeneity in knowledge. Small-scale fishers were surveyed in the communities of Ahus island (Manus Province), Wadau and Muluk (Karkar island, Madang Province) in October 2012. </p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "note", ""] ["<p>Data from interview-based survey of small-scale fishers in Papua New Guinea</p>", "<p>Data from interview-based survey of small-scale fishers in Papua New Guinea</p>", "brief", "<p>Structured interviews designed to assess fisher knowledge of reef fish aggregation behaviour, to collect information on fishing practices and to score key socioeconomic variables. The study was designed to assess the role of fisher knowledge in conferring vulnerability of fish aggregations to fishing and to quantify factors associated with heterogeneity in knowledge. Small-scale fishers were surveyed in the communities of Ahus island (Manus Province), Wadau and Muluk (Karkar island, Madang Province) in October 2012. </p>", "<p>Structured interviews designed to assess fisher knowledge of reef fish aggregation behaviour, to collect information on fishing practices and to score key socioeconomic variables. The study was designed to assess the role of fisher knowledge in conferring vulnerability of fish aggregations to fishing and to quantify factors associated with heterogeneity in knowledge. Small-scale fishers were surveyed in the communities of Ahus island (Manus Province), Wadau and Muluk (Karkar island, Madang Province) in October 2012. </p>", "full", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "<p>This dataset consists of a spreadsheet in MS Excel (.xlsx) and Open Document formats (.ods)</p>", "note", ""] Trophic interactions among key target reef fish in Kenya fascinator 4797aba4d091cc22ca822f208c3e6600 2020-02-28T04:49:05Z ["<p>Trophic interactions (i.e., predator-prey relationships) among key target reef fish in Kenya.</p>", "brief", "<p>Trophic interactions (i.e., predator-prey relationships) among key target reef fish in Kenya.</p>", "<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears employed in five study sites along the Kenyan coast.</p><p>To determine which species were caught by each gear type being used by fishers within these sites, we used a long-term fish catch dataset collected by the Wildlife Conservation Society. The dataset included surveys from 25 landing sites along the Kenyan coast conducted continuously between 2010 and 2016. For each observation, onsite observers identified landed catch at the species level in addition to the gear used. Observers were present at landing stations every sampling day before the arrival of boats and stayed until the entire landing process was concluded. Although all patrols were conducted during daylight hours, the sampling method does not exclude catches attributed to nighttime fishing activities, as observers also intercepted fishers returning from their overnight fishing, ensuring that each gear used at each site was sampled and that each species landed was recorded. The number of patrols conducted per month were not stratified, but similar intervals of sampling were maintained within this randomized block design to detect long-term catch trends. Data was collected at least 8 days per month, translating to a total of 599 sampling days over the survey period and an observed total of 19,467 individual fish caught across all gear types. Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore focused on species comprising the majority of the total catch for each gear type, excluding all species that comprised less than 1% of the total catch. This resulted in 36 key target reef fish species. Trophic interactions capturing predator-prey relationships among the 36 key target reef fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). The corresponding ecological network is thus undirected, with edges representing trophic interactions between fish species. Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.    </p>", "full", "<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears employed in five study sites along the Kenyan coast.</p><p>To determine which species were caught by each gear type being used by fishers within these sites, we used a long-term fish catch dataset collected by the Wildlife Conservation Society. The dataset included surveys from 25 landing sites along the Kenyan coast conducted continuously between 2010 and 2016. For each observation, onsite observers identified landed catch at the species level in addition to the gear used. Observers were present at landing stations every sampling day before the arrival of boats and stayed until the entire landing process was concluded. Although all patrols were conducted during daylight hours, the sampling method does not exclude catches attributed to nighttime fishing activities, as observers also intercepted fishers returning from their overnight fishing, ensuring that each gear used at each site was sampled and that each species landed was recorded. The number of patrols conducted per month were not stratified, but similar intervals of sampling were maintained within this randomized block design to detect long-term catch trends. Data was collected at least 8 days per month, translating to a total of 599 sampling days over the survey period and an observed total of 19,467 individual fish caught across all gear types. Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore focused on species comprising the majority of the total catch for each gear type, excluding all species that comprised less than 1% of the total catch. This resulted in 36 key target reef fish species. Trophic interactions capturing predator-prey relationships among the 36 key target reef fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). The corresponding ecological network is thus undirected, with edges representing trophic interactions between fish species. Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.    </p>", "<p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", "note", "<p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", ""] ["<p>Trophic interactions (i.e., predator-prey relationships) among key target reef fish in Kenya.</p>", "brief", "<p>Trophic interactions (i.e., predator-prey relationships) among key target reef fish in Kenya.</p>", "<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears employed in five study sites along the Kenyan coast.</p><p>To determine which species were caught by each gear type being used by fishers within these sites, we used a long-term fish catch dataset collected by the Wildlife Conservation Society. The dataset included surveys from 25 landing sites along the Kenyan coast conducted continuously between 2010 and 2016. For each observation, onsite observers identified landed catch at the species level in addition to the gear used. Observers were present at landing stations every sampling day before the arrival of boats and stayed until the entire landing process was concluded. Although all patrols were conducted during daylight hours, the sampling method does not exclude catches attributed to nighttime fishing activities, as observers also intercepted fishers returning from their overnight fishing, ensuring that each gear used at each site was sampled and that each species landed was recorded. The number of patrols conducted per month were not stratified, but similar intervals of sampling were maintained within this randomized block design to detect long-term catch trends. Data was collected at least 8 days per month, translating to a total of 599 sampling days over the survey period and an observed total of 19,467 individual fish caught across all gear types. Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore focused on species comprising the majority of the total catch for each gear type, excluding all species that comprised less than 1% of the total catch. This resulted in 36 key target reef fish species. Trophic interactions capturing predator-prey relationships among the 36 key target reef fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). The corresponding ecological network is thus undirected, with edges representing trophic interactions between fish species. Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.    </p>", "full", "<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears employed in five study sites along the Kenyan coast.</p><p>To determine which species were caught by each gear type being used by fishers within these sites, we used a long-term fish catch dataset collected by the Wildlife Conservation Society. The dataset included surveys from 25 landing sites along the Kenyan coast conducted continuously between 2010 and 2016. For each observation, onsite observers identified landed catch at the species level in addition to the gear used. Observers were present at landing stations every sampling day before the arrival of boats and stayed until the entire landing process was concluded. Although all patrols were conducted during daylight hours, the sampling method does not exclude catches attributed to nighttime fishing activities, as observers also intercepted fishers returning from their overnight fishing, ensuring that each gear used at each site was sampled and that each species landed was recorded. The number of patrols conducted per month were not stratified, but similar intervals of sampling were maintained within this randomized block design to detect long-term catch trends. Data was collected at least 8 days per month, translating to a total of 599 sampling days over the survey period and an observed total of 19,467 individual fish caught across all gear types. Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore focused on species comprising the majority of the total catch for each gear type, excluding all species that comprised less than 1% of the total catch. This resulted in 36 key target reef fish species. Trophic interactions capturing predator-prey relationships among the 36 key target reef fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). The corresponding ecological network is thus undirected, with edges representing trophic interactions between fish species. Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.    </p>", "<p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", "note", "<p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", ""] Trophic interactions among key target reef fish in Papua New Guinea fascinator fcd75f1524b7ef3bfb1ea75b8cfeceb0 2020-06-17T00:46:29Z ["<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears (with the exception of gillnets) employed on a Papua New Guinean island in the Manus Province.</p><p>Gillnets were excluded because there are strong traditional customs that limit when gillnets can be used and by whom (thus, only a handful of households have rights to use gillnets, and in practice, gillnets are seldom used in this location). To determine which species were caught by each gear type being used by fishers, catch surveys were performed during the day and night at landing sites (i.e., approaching fishers as they returned from fishing activities) and local markets and involved photographing the catch (using a scale) and recording the gear used. We made sure fish were not double-counted by obtaining fishing trip details at the start of each catch survey (e.g., fisher, start time of fishing trip, or hours fishing). Catch photographs were analysed by sizing and identifying individual fish species to the lowest taxonomic level possible. A total of 2469 individual fish and 5 different gears (handline, speargun, trolling line, simple spear, and gillnets) were recorded during our sampling period. Gillnet catch was subsequently excluded from the analyses as discussed above. As catch data was collected at one point in time rather than continuously throughout the year, it is possible that some species-gear interactions were not measured. Catch composition included reef associated-fish, invertebrates, and pelagic fish (e.g., tuna and sharks). Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore only included fish identified to the species-level that corresponded at least to 1% of each gears catch, resulting in a total of 60 primary target fish species. Trophic interactions capturing predator-prey relationships among the 60 primary target fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.</p><p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", "full", "<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears (with the exception of gillnets) employed on a Papua New Guinean island in the Manus Province.</p><p>Gillnets were excluded because there are strong traditional customs that limit when gillnets can be used and by whom (thus, only a handful of households have rights to use gillnets, and in practice, gillnets are seldom used in this location). To determine which species were caught by each gear type being used by fishers, catch surveys were performed during the day and night at landing sites (i.e., approaching fishers as they returned from fishing activities) and local markets and involved photographing the catch (using a scale) and recording the gear used. We made sure fish were not double-counted by obtaining fishing trip details at the start of each catch survey (e.g., fisher, start time of fishing trip, or hours fishing). Catch photographs were analysed by sizing and identifying individual fish species to the lowest taxonomic level possible. A total of 2469 individual fish and 5 different gears (handline, speargun, trolling line, simple spear, and gillnets) were recorded during our sampling period. Gillnet catch was subsequently excluded from the analyses as discussed above. As catch data was collected at one point in time rather than continuously throughout the year, it is possible that some species-gear interactions were not measured. Catch composition included reef associated-fish, invertebrates, and pelagic fish (e.g., tuna and sharks). Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore only included fish identified to the species-level that corresponded at least to 1% of each gears catch, resulting in a total of 60 primary target fish species. Trophic interactions capturing predator-prey relationships among the 60 primary target fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.</p><p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", ""] ["<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears (with the exception of gillnets) employed on a Papua New Guinean island in the Manus Province.</p><p>Gillnets were excluded because there are strong traditional customs that limit when gillnets can be used and by whom (thus, only a handful of households have rights to use gillnets, and in practice, gillnets are seldom used in this location). To determine which species were caught by each gear type being used by fishers, catch surveys were performed during the day and night at landing sites (i.e., approaching fishers as they returned from fishing activities) and local markets and involved photographing the catch (using a scale) and recording the gear used. We made sure fish were not double-counted by obtaining fishing trip details at the start of each catch survey (e.g., fisher, start time of fishing trip, or hours fishing). Catch photographs were analysed by sizing and identifying individual fish species to the lowest taxonomic level possible. A total of 2469 individual fish and 5 different gears (handline, speargun, trolling line, simple spear, and gillnets) were recorded during our sampling period. Gillnet catch was subsequently excluded from the analyses as discussed above. As catch data was collected at one point in time rather than continuously throughout the year, it is possible that some species-gear interactions were not measured. Catch composition included reef associated-fish, invertebrates, and pelagic fish (e.g., tuna and sharks). Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore only included fish identified to the species-level that corresponded at least to 1% of each gears catch, resulting in a total of 60 primary target fish species. Trophic interactions capturing predator-prey relationships among the 60 primary target fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.</p><p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", "full", "<p>Trophic interactions (i.e., predator-prey relationships) among target reef fish comprising the majority of catch by all fishing gears (with the exception of gillnets) employed on a Papua New Guinean island in the Manus Province.</p><p>Gillnets were excluded because there are strong traditional customs that limit when gillnets can be used and by whom (thus, only a handful of households have rights to use gillnets, and in practice, gillnets are seldom used in this location). To determine which species were caught by each gear type being used by fishers, catch surveys were performed during the day and night at landing sites (i.e., approaching fishers as they returned from fishing activities) and local markets and involved photographing the catch (using a scale) and recording the gear used. We made sure fish were not double-counted by obtaining fishing trip details at the start of each catch survey (e.g., fisher, start time of fishing trip, or hours fishing). Catch photographs were analysed by sizing and identifying individual fish species to the lowest taxonomic level possible. A total of 2469 individual fish and 5 different gears (handline, speargun, trolling line, simple spear, and gillnets) were recorded during our sampling period. Gillnet catch was subsequently excluded from the analyses as discussed above. As catch data was collected at one point in time rather than continuously throughout the year, it is possible that some species-gear interactions were not measured. Catch composition included reef associated-fish, invertebrates, and pelagic fish (e.g., tuna and sharks). Most gears used in multispecies coral reef fisheries incidentally catch a number of species infrequently. We therefore only included fish identified to the species-level that corresponded at least to 1% of each gears catch, resulting in a total of 60 primary target fish species. Trophic interactions capturing predator-prey relationships among the 60 primary target fish species were estimated based on a combination of diet, relative body size, and habitat use (likelihood of encounter). Diet and body size (maximum length) data were taken from FishBase, and broad patterns of habitat use (i.e., pelagic, demersal, coral-dominated, macroalgal bed) were estimated from published records and expert first-hand knowledge of coral reef ecologists at the ARC Centre of Excellence for Coral Reef Studies at James Cook University, Australia. Detail on the specific fish species consumed from analyses of gut contents is largely unavailable, yet piscivorous coral reef fish are known to be generalists in terms of the species they consume. We thus took a conservative approach, considering one species to prey on another if its diet was predominantly piscivorous, its body length was large (ca. ≥ 2 times) compared to that of the prey species, and the two species occupied a similar habitat. We did not identify potential predatory links for any species whose diet was not primarily piscivorous as any likely predation on other targeted species was likely to be too infrequent to have a meaningful effect on prey populations.</p><p>This dataset consists of a trophic matrix in comma-separated values (.csv) format.</p>", ""]