19 research outputs found
Developing Important Marine Mammal Area Criteria: Learning From Ecologically or Biologically Significant Areas and Key Biodiversity Areas
1. This paper explores how criteria to identify important marine mammal areas (IMMAs) could be developed, and nested in existing global criteria. This process would consider 134 species of marine mammals. 2. Particular attention is given to two suites of global criteria to identify areas important for the persistence of marine biodiversity: Ecologically or Biologically Significant Areas (EBSAs) developed through the Convention on Biological Diversity (CBD), and Key Biodiversity Areas (KBAs) in revision through the International Union for the Conservation of Nature (IUCN). They are seen as mutually complementary in the development of IMMAs. 3. The specificities necessary for identifying important areas at scales below the global level may vary according to the region, the biophysical requirements of distinct populations, and available data. Refining and testing the applicability of these global criteria on marine mammals at both regional and national scales will be necessary. 4. Combining area-based measures with non-spatial management actions will likely be the optimal approach for ensuring marine mammal persistence given their highly migratory nature and widespread life-history stages. 5. Capacity to enact IMMAs is strengthened by the existence of professional marine mammal associations and networks, and the recently formed IUCN Marine Mammal Protected Areas Task Force (MMPATF). The MMPATF is planning further development of IMMA criteria through joint work with the International Committee on Marine Mammal Protected Areas (ICMMPA)
Global conservation status of marine pufferfishes (Tetraodontiformes: Tetraodontidae)
Puffers are biologically and ecologically fascinating fishes best known for their unique morphology and arsenal of defenses including inflation and bioaccumulation of deadly neurotoxins. These fishes are also commercially, culturally, and ecologically important in many regions. One-hundred-and-fifty-one species of marine puffers were assessed against the International Union for Conservation of Nature (IUCN) Red List Criteria at a 2011 workshop held in Xiamen, China. Here we present the first comprehensive review of puffer geographic and depth distribution, use and trade, and habitats and ecology and a summary of the global conservation status of marine puffers, determined by applying the International Union for Conservation of Nature (IUCN) Red List Criteria. The majority (77%) of puffers were assessed as Least Concern, 15% were Data Deficient, and 8% were threatened (Critically Endangered, Endangered or Vulnerable) or Near Threatened. Of the threatened species, the majority are limited-ranging habitat specialists which are primarily affected by habitat loss due to climate change and coastal development. However, one threatened puffer (Takifugu chinensis ā CR) and four Near Threatened puffers, also in the genus Takifugu (which contains 24 species total), are wide-ranging habitat generalists which are commercially targeted in the international puffer trade. A disproportionate number of species of conservation concern are found along the coast of eastern Asia, from Japan to the South China Sea, with the highest concentration in the East China Sea. Better management of fishing and other conservation efforts are needed for commercially fished Takifugu species in this region. Taxonomic issues within the Tetraodontidae confound accurate reporting and produce a lack of resolution in species distributions. Resolution of taxonomy will enable more accurate assessment of the conservation status of many Data Deficient puffers
Applying a ridge-to-reef framework to support watershed, water quality, and community-based fisheries management in American Samoa
Water quality and fisheries exploitation are localized, chronic stressors that impact coral reef condition and resilience. Yet, quantifying the relative contribution of individual stressors and evaluating the degree of human impact to any particular reef are difficult due to the inherent variation in biological assemblages that exists across and within island scales. We developed a framework to first account for island-scale variation in biological assemblages, and then evaluate the condition of 26 reefs adjacent to watersheds in Tutuila, American Samoa. Water quality data collected over 1Ā year were first linked with watershed characteristics such as land use and human population. Dissolved inorganic nitrogen (DIN) concentrations were best predicted by total human population and disturbed land for watersheds with over 200 humans kmā»Ā², providing a predictive threshold for DIN enrichment attributed to human populations. Coral reef assemblages were next partitioned into three distinct reeftypes to account for inherent variation in biological assemblages and isolate upon local stressors. Regression models suggested that watershed characteristics linked with DIN and fishing access best predicted ecological condition scores, but their influences differed. Relationships were weakest between coral assemblages and watershed-based proxies of DIN, and strongest between fish assemblages and distances to boat harbors and wave energy (i.e., accessibility). While we did not explicitly address the potential recursivity between fish and coral assemblages, there was a weak overall correlation between these ecological condition scores. Instead, the more complex, recursive nature between reef fish and habitats was discussed with respect to bottom-up and top-down processes, and several ongoing studies that can better help address this topic into the future were identified. The framework used here showed the spatial variation of stressor influence, and the specific assemblage attributes influenced by natural and anthropogenic drivers which aims to guide a local ridge-to-reef management strategy
Catchment to sea connection: impacts of terrestrial run-off on benthic ecosystems in American Samoa
Variation in water quality can directly affect the composition of benthic assemblages on coral reefs. Yet, few studies have directly quantified nutrient and suspended particulate matter (SPM) to examine their potential impacts on benthic community structure, especially around high oceanic islands. We assessed the spatio-temporal variation of nutrients and SPM across six sites in American Samoa over a 12-month period and used exploratory path analysis to relate dissolved inorganic nutrients, land use, and natural and anthropogenic drivers to benthic assemblages on adjacent shallow reefs. Multivariate analyses showed clear gradients in nutrient concentrations, sediment accumulation and composition, and benthic structure across watersheds. Instream nutrients and land uses positively influenced reef flat nutrient concentrations, while benthic assemblages were best predicted by wave exposure, runoff, stream phosphate and dissolved inorganic nitrogen loads. Identifying locality-specific drivers of water quality and benthic condition can support targeted management in American Samoa and in other high islands
Feeding classification of parrotfishes and surgeonfishes based on dietary targets and post-digestive processes.
<p>Feeding classification of parrotfishes and surgeonfishes based on dietary targets and post-digestive processes.</p
Global species richness patterns.
<p>a. Species richness of parrotfishes of the world. b. Species richness of surgeonfishes of the world.</p
Percentage of destroyed and declining reef in each species' range vs Red List Category.
<p>Center lineā=āmedian value, box boundariesā=ā25<sup>th</sup> and 75<sup>th</sup> percentiles, whiskersā=ā10<sup>th</sup> and 90<sup>th</sup> percentiles, black dotsā=āoutliers.</p
Percentage of parrotfishes and surgeonfishes in each habitat type.
<p>Percentage of parrotfishes and surgeonfishes in each habitat type.</p
Red List Category by Proportion of MPA in each species' range.
<p>Center lineā=āmedian value, box boundariesā=ā25<sup>th</sup> and 75<sup>th</sup> percentiles, whiskersā=ā10<sup>th</sup> and 90<sup>th</sup> percentiles, black dotsā=āoutliers.</p