scholarly journals Morphological traits of reef corals predict extinction risk but not conservation status

2021 ◽  
Author(s):  
Nussaïbah B. Raja ◽  
Andreas Lauchstedt ◽  
John M. Pandolfi ◽  
Sun W. Kim ◽  
Ann F. Budd ◽  
...  
Keyword(s):  
Morphological Traits ◽  
Extinction Risk ◽  
Conservation Status ◽  
Reef Corals

scholarly journals Can Morphology Predict the Conservation Status of Iguanian Lizards?

2020 ◽  
Vol 60 (2) ◽  
pp. 535-548 ◽  
Author(s):  
Donald B Miles
Keyword(s):  
Morphological Traits ◽  
Biological Diversity ◽  
Linear Models ◽  
Extinction Risk ◽  
Conservation Status ◽  
Rapid Assessment ◽  
Ann Model ◽  
Functional Link ◽  
Threat Status ◽  
Risk Of Extinction

Synopsis The integrity of regional and local biological diversity is under siege as a result of multiple anthropogenic threats. The conversion of habitats, such as rain forests, into agricultural ecosystems, reduces the area available to support species populations. Rising temperatures and altered rainfall patterns lead to additional challenges for species. The ability of conservation biologists to ascertain the threats to a species requires data on changes in distribution, abundance, life history, and ecology. The International Union for the Conservation of Nature (IUCN) uses these data to appraise the extinction risk for a species. However, many species remain data deficient (DD) or unassessed. Here, I use 14 morphological traits related to locomotor function, habitat, and feeding to predict the threat status of over 400 species of lizards in the infraorder Iguania. Morphological traits are an ideal proxy for making inferences about a species’ risk of extinction. Patterns of morphological covariation have a known association with habitat use, foraging behavior, and physiological performance across multiple taxa. Results from phylogenetic general linear models revealed that limb lengths as well as head characters predicted extinction risk. In addition, I used an artificial neural network (ANN) technique to generate a classification function based on the morphological traits of species with an assigned IUCN threat status. The network approach identified eight morphological traits as predictors of extinction risk, which included head and limb characters. The best supported model had a classification accuracy of 87.4%. Moreover, the ANN model predicted >18% of DD/not assessed species were at risk of extinction. The predicted assessments were supported by other sources of threat status, for example, Convention on International Trade in Endangered Species appendices. Because of the functional link between morphology, performance, and ecology, an ecomorphological approach may be a useful tool for rapid assessment of DD or poorly known species.

scholarly journals Global extinction risk for seahorses, pipefishes and their near relatives (Syngnathiformes)

Oryx ◽  
2021 ◽  
pp. 1-10
Author(s):  
Riley A. Pollom ◽  
Gina M. Ralph ◽  
Caroline M. Pollock ◽  
Amanda C.J. Vincent
Keyword(s):  
Threatened Species ◽  
Habitat Degradation ◽  
Extinction Risk ◽  
Conservation Status ◽  
Field Research ◽  
Selective Extraction ◽  
Iucn Red List ◽  
Point Estimate ◽  
Conservation Action ◽  
Data Deficient

Abstract Few marine taxa have been comprehensively assessed for their conservation status, despite heavy pressures from fishing, habitat degradation and climate change. Here we report on the first global assessment of extinction risk for 300 species of syngnathiform fishes known as of 2017, using the IUCN Red List criteria. This order of bony teleosts is dominated by seahorses, pipefishes and seadragons (family Syngnathidae). It also includes trumpetfishes (Aulostomidae), shrimpfishes (Centriscidae), cornetfishes (Fistulariidae) and ghost pipefishes (Solenostomidae). At least 6% are threatened, but data suggest a mid-point estimate of 7.9% and an upper bound of 38%. Most of the threatened species are seahorses (Hippocampus spp.: 14/42 species, with an additional 17 that are Data Deficient) or freshwater pipefishes of the genus Microphis (2/18 species, with seven additional that are Data Deficient). Two species are Near Threatened. Nearly one-third of syngnathiformes (97 species) are Data Deficient and could potentially be threatened, requiring further field research and evaluation. Most species (61%) were, however, evaluated as Least Concern. Primary threats to syngnathids are (1) overexploitation, primarily by non-selective fisheries, for which most assessments were determined by criterion A (Hippocampus) and/or (2) habitat loss and degradation, for which assessments were determined by criterion B (Microphis and some Hippocampus). Threatened species occurred in most regions but more are found in East and South-east Asia and in South African estuaries. Vital conservation action for syngnathids, including constraining fisheries, particularly non-selective extraction, and habitat protection and rehabilitation, will benefit many other aquatic species.

scholarly journals Conservation Status of Marine Biodiversity in Oceania: An Analysis of Marine Species on the IUCN Red List of Threatened Species

2011 ◽  
Vol 2011 ◽  
pp. 1-14 ◽  
Author(s):  
Beth A. Polidoro ◽  
Cristiane T. Elfes ◽  
Jonnell C. Sanciangco ◽  
Helen Pippard ◽  
Kent E. Carpenter
Keyword(s):  
Threatened Species ◽  
Environmental Changes ◽  
Extinction Risk ◽  
Conservation Status ◽  
Marine Species ◽  
Iucn Red List ◽  
Red List ◽  
Marine Biodiversity ◽  
Conservation Priorities ◽  
Conservation Action

Given the economic and cultural dependence on the marine environment in Oceania and a rapidly expanding human population, many marine species populations are in decline and may be vulnerable to extinction from a number of local and regional threats. IUCN Red List assessments, a widely used system for quantifying threats to species and assessing species extinction risk, have been completed for 1190 marine species in Oceania to date, including all known species of corals, mangroves, seagrasses, sea snakes, marine mammals, sea birds, sea turtles, sharks, and rays present in Oceania, plus all species in five important perciform fish groups. Many of the species in these groups are threatened by the modification or destruction of coastal habitats, overfishing from direct or indirect exploitation, pollution, and other ecological or environmental changes associated with climate change. Spatial analyses of threatened species highlight priority areas for both site- and species-specific conservation action. Although increased knowledge and use of newly available IUCN Red List assessments for marine species can greatly improve conservation priorities for marine species in Oceania, many important fish groups are still in urgent need of assessment.

scholarly journals Increasing accuracy: The advantage of using open access species occurrence database in the Red List assessment

2020 ◽  
Vol 21 (8) ◽  
Author(s):  
Iyan Robiansyah ◽  
Wita Wardani
Keyword(s):  
Open Access ◽  
Extinction Risk ◽  
Conservation Status ◽  
Iucn Red List ◽  
Red List ◽  
Suitable Habitat ◽  
Herbarium Specimens ◽  
Species Occurrence ◽  
Extent Of Occurrence ◽  
Area Of Occupancy

Abstract. Robiansyah I, Wardani W. 2020. Increasing accuracy: The advantage of using open access species occurrence database in the Red List assessment. Biodiversitas 21: 3658-3664. IUCN Red List is the most widely used instrument to assess and advise the extinction risk of a species. One of the criteria used in IUCN Red List is geographical range of the species assessed (criterion B) in the form of extent of occurrence (EOO) and/or area of occupancy (AOO). While this criterion is presumed to be the easiest to be completed as it is based mainly on species occurrence data, there are some assessments that failed to maximize freely available databases. Here, we reassessed the conservation status of Cibotium arachnoideum, a tree fern distributed in Sumatra and Borneo. This species was previously assessed by Praptosuwiryo (2020, Biodiversitas 21 (4): 1379-1384) which classified the species as Endangered (EN) under criteria B2ab(i,ii,iii); C2a(ii). Using additional data from herbarium specimens recorded in the Global Biodiversity Information Facility (GBIF) website and from peer-reviewed scientific papers, in the present paper we show that C. arachnoideum has a larger extent of occurrence (EOO) and area of occupancy (AOO), more locations and different conservation status compared to those in Praptosuwiryo (2020). Our results are supported by the predicted suitable habitat map of C. arachnoideum produced by MaxEnt modelling method. Based on our assessment, we propose the category of Vulnerable (VU) C2a(i) as the global conservation status for C. arachnoideum. Our study implies the advantage of using open access databases to increase the accuracy of extinction risk assessment under the IUCN Red List criteria in regions like Indonesia, where adequate taxonomical information is not always readily available.

scholarly journals Addressing Uncertainties in Machine Learning Predictions of Conservation Status

2019 ◽  
Vol 3 ◽  
Author(s):  
Barnaby Walker ◽  
Tarciso Leão ◽  
Steven Bachman ◽  
Eve Lucas ◽  
Eimear Nic Lughadha
Keyword(s):  
Machine Learning ◽  
Natural History ◽  
Extinction Risk ◽  
Conservation Status ◽  
Red List ◽  
Learning Models ◽  
Species Occurrence ◽  
Voucher Specimens ◽  
Machine Learning Models ◽  
Occurrence Records

Extinction risk assessments are increasingly important to many stakeholders (Bennun et al. 2017) but there remain large gaps in our knowledge about the status of many species. The IUCN Red List of Threatened Species (IUCN 2019, hereafter Red List) is the most comprehensive assessment of extinction risk. However, it includes assessments of just 7% of all vascular plants, while 18% of all assessed animals lack sufficient data to assign a conservation status. The wide availability of species occurrence information through digitised natural history collections and aggregators such as the Global Biodiversity Information Facility (GBIF), coupled with machine learning methods, provides an opportunity to fill these gaps in our knowledge. Machine learning approaches have already been proposed to guide conservation assessment efforts (Nic Lughadha et al. 2018), assign a conservation status to species with insufficient data for a full assessment (Bland et al. 2014), and predict the number of threatened species across the world (Pelletier et al. 2018). The wide range in sources of species occurrence records can lead to data quality issues, such as missing, imprecise, or mistaken information. These data quality issues may be compounded in databases that aggregate information from multiple sources: many such records derive from field observations (78% for plant species in GBIF; Meyer et al. 2016) largely unsupported by voucher specimens that would allow confirmation or correction of their identification. Even where voucher specimens do exist, different taxonomic or geographic information can be held for a single collection event represented by duplicate specimens deposited in different natural history collections. Tools are available to help clean species occurrence data, but these cannot deal with problems like specimen misidentification, which previous work (Nic Lughadha et al. 2019) has shown to have a large impact on preliminary assessments of conservation status. Machine learning models based on species occurrence records have been reported to predict with high accuracy the conservation status of species. However, given the black-box nature of some of the better machine learning models, it is unclear how well these accuracies apply beyond the data on which the models were trained. Practices for training machine learning models differ between studies, but more interrogation of these models is required if we are to know how much to trust their predictions. To address these problems, we compare predictions made by a machine learning model when trained on specimen occurrence records that have benefitted from minimal or more thorough cleaning, with those based on records from an expert-curated database. We then explore different techniques to interrogate machine learning models and quantify the uncertainty in their predictions.

scholarly journals Density and population viability of coastal marten: a rare and geographically isolated small carnivore

2017 ◽  
Author(s):  
Mark A Linnell ◽  
Katie Moriarty ◽  
David S Green ◽  
Taal Levi
Keyword(s):  
Population Size ◽  
Extinction Risk ◽  
Conservation Status ◽  
Population Viability Analysis ◽  
Credible Interval ◽  
The United States ◽  
Population Viability ◽  
Coastal Forests ◽  
Private Lands ◽  
Geographically Isolated

Pacific martens (Martes caurina) in coastal forests of Oregon and northern California in the United States are rare and geographically isolated, prompting a petition for listing under the Endangered Species Act. If listed, regulations have the potential to substantially influence land-use decisions and forestry on public and private lands, but no estimates of population size, density, and viability of remnant marten populations are available for evaluating their conservation status. We used GPS telemetry, territory mapping, and spatial mark-recapture to estimate population size and density within the current extent of Pacific martens in central Oregon, within coastal forest in the Oregon dunes national recreational area. We then estimated population viability at differing levels of human-caused mortality (e.g. roadkill). We estimated 63 adult martens (95% Credible Interval: 58-73) and 73 (range: 46-91) potential territories across two subpopulations separated by a large barrier (Umpqua River). Marten density was 1.02 per km2, the highest reported in North America. Using population viability analysis, extinction risk for a subpopulation of 30 martens ranged from 34% to 100% with two or more annual human-caused mortalities. Absent broad-scale restoration of forest to conditions which support marten populations, limiting human-caused mortalities would likely have the greatest conservation impact.

scholarly journals Conservation status of polar bears ( Ursus maritimus ) in relation to projected sea-ice declines

2016 ◽  
Vol 12 (12) ◽  
pp. 20160556 ◽  
Author(s):  
Eric V. Regehr ◽  
Kristin L. Laidre ◽  
H. Resit Akçakaya ◽  
Steven C. Amstrup ◽  
Todd C. Atwood ◽  
...  
Keyword(s):  
Sea Ice ◽  
Polar Bear ◽  
Extinction Risk ◽  
Conservation Status ◽  
Iucn Red List ◽  
Arctic Sea Ice ◽  
Polar Bears ◽  
Near Term ◽  
Conservation Assessments ◽  
Global Population

Loss of Arctic sea ice owing to climate change is the primary threat to polar bears throughout their range. We evaluated the potential response of polar bears to sea-ice declines by (i) calculating generation length (GL) for the species, which determines the timeframe for conservation assessments; (ii) developing a standardized sea-ice metric representing important habitat; and (iii) using statistical models and computer simulation to project changes in the global population under three approaches relating polar bear abundance to sea ice. Mean GL was 11.5 years. Ice-covered days declined in all subpopulation areas during 1979–2014 (median −1.26 days year −1 ). The estimated probabilities that reductions in the mean global population size of polar bears will be greater than 30%, 50% and 80% over three generations (35–41 years) were 0.71 (range 0.20–0.95), 0.07 (range 0–0.35) and less than 0.01 (range 0–0.02), respectively. According to IUCN Red List reduction thresholds, which provide a common measure of extinction risk across taxa, these results are consistent with listing the species as vulnerable. Our findings support the potential for large declines in polar bear numbers owing to sea-ice loss, and highlight near-term uncertainty in statistical projections as well as the sensitivity of projections to different plausible assumptions.

Rediscovery of Oocephalus foliosus (Hyptidinae—Lamiaceae): notes on taxonomy and conservation of a species endemic to the campo rupestre of Central Brazil

Phytotaxa ◽  
2021 ◽  
Vol 525 (2) ◽  
pp. 156-162
Author(s):  
ARTHUR DE SOUZA SOARES ◽  
RAQUEL NEGRÃO ◽  
RAYMOND MERVYN HARLEY ◽  
JOSÉ FLORIANO BARÊA PASTORE ◽  
JOMAR GOMES JARDIM
Keyword(s):  
19Th Century ◽  
Extinction Risk ◽  
Conservation Status ◽  
Small Population ◽  
Species Description ◽  
Second Step ◽  
Campo Rupestre ◽  
Central Brazil ◽  
Surrounding Areas ◽  
Narrow Area

Oocephalus foliosus was described in the first half of 19th century, based on a collection from central Goiás state, Brazil, being collected again only three times in surrounding areas. Although this species seems to be rare and endemic to a narrow area, it has never been listed on any threatened list or had its conservation status assessed. Recently, we recorded a small population of O. foliosus in the Pireneus peak, an area of campo rupestre located in the municipality of Pirenópolis, Goiás, allowing us to improve the species description, assess its extinction risk and comment on its taxonomy. Also, a second step lectotypification was needed to the species and is here proposed.

scholarly journals Estimating the global conservation status of more than 15,000 Amazonian tree species

2015 ◽  
Vol 1 (10) ◽  
pp. e1500936 ◽  
Author(s):  
Hans ter Steege ◽  
Nigel C. A. Pitman ◽  
Timothy J. Killeen ◽  
William F. Laurance ◽  
Carlos A. Peres ◽  
...  
Keyword(s):  
Protected Areas ◽  
Tree Species ◽  
Large Scale ◽  
Gap Analysis ◽  
Extinction Risk ◽  
Conservation Status ◽  
Iucn Red List ◽  
Distribution Models ◽  
Threatened Plant Species ◽  
The Tropics

Estimates of extinction risk for Amazonian plant and animal species are rare and not often incorporated into land-use policy and conservation planning. We overlay spatial distribution models with historical and projected deforestation to show that at least 36% and up to 57% of all Amazonian tree species are likely to qualify as globally threatened under International Union for Conservation of Nature (IUCN) Red List criteria. If confirmed, these results would increase the number of threatened plant species on Earth by 22%. We show that the trends observed in Amazonia apply to trees throughout the tropics, and we predict that most of the world’s >40,000 tropical tree species now qualify as globally threatened. A gap analysis suggests that existing Amazonian protected areas and indigenous territories will protect viable populations of most threatened species if these areas suffer no further degradation, highlighting the key roles that protected areas, indigenous peoples, and improved governance can play in preventing large-scale extinctions in the tropics in this century.

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