scholarly journals Illegal long-line fishing and albatross extinction risk

Oryx ◽  
2016 ◽  
Vol 52 (2) ◽  
pp. 336-345 ◽  
Author(s):  
Gohar A. Petrossian ◽  
Rolf A. de By ◽  
Ronald V. Clarke
Keyword(s):  
Extinction Risk ◽  
Red List ◽  
Mitigation Measures ◽  
Bird Conservation ◽  
Fishing Activity ◽  
Illegal Fishing ◽  
Country Level ◽  
Long Line ◽  
Southern Bluefin Tuna ◽  
Risk Areas

AbstractBirds are commonly entangled in long-line fisheries, and increases in long-line fishing activity have consistently caused declines in seabird populations. Environmental criminology would posit that the risk of such declines is greater in the case of illegal long-line fisheries, which are less likely to implement bycatch mitigation measures. To investigate this possibility we examined the overlap between data on illegal fishing and albatross at-sea occurrence ranges. Moderate correlations were found between mean exposure to illegal fishing and the Red List status of albatross species, but none were found between Red List status and total fishing pressure. A second analysis overlaid albatross at-sea occurrence ranges with long-lining data for the member countries of the Convention on Conservation of Southern Bluefin Tuna to compare the effect of exposure to legal and illegal hooks on Red List status. Lacking a better measure, Country A's hooks were used as a proxy for illegal hooks. Critically Endangered and Endangered species were 12 and 3.4 times more exposed to illegal hooks, respectively, than Near Threatened species, whereas there was no relationship between Red List status and exposure to legal hooks. Country-level analyses confirmed these findings, which provide evidence that illegal long-line fishing poses a particular threat to the survival of albatrosses. The findings suggest that the bird conservation lobby should work closely with fisheries authorities to tackle illegal fishing, and that research should identify the highest risk areas of overlap between illegal fishing and albatross at-sea ranges.

TBE in Romania

2020 ◽  
Keyword(s):  
Surveillance System ◽  
Epidemiological Survey ◽  
Passive Surveillance ◽  
Notifiable Disease ◽  
Territorial Expansion ◽  
Country Level ◽  
Regular Screening ◽  
Passive Surveillance System ◽  
Natural Foci ◽  
Risk Areas

Based on an epidemiological survey,1 human TBEV neuroinfections may have an endemic emergent course, and natural foci are in full territorial expansion. Identified risk areas are Tulcea district, Transylvania, at the base of the Carpathian Mountains and the Transylvanian Alps.2,3 TBE has been a notifiable disease since 1996. Surveillance of TBE is not done at the country level, only regionally in some counties (northern/central/western part, close to Hungary). The passive surveillance system was implemented in 2008. However, there is no regular screening and the relative risk of contracting this disease is unknown. In 1999, an outbreak of TBE in humans was recorded with a total of at least 38 human cases.4

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 The dynamics underlying avian extinction trajectories forecast a wave of extinctions

2019 ◽  
Vol 15 (12) ◽  
pp. 20190633 ◽  
Author(s):  
Melanie J. Monroe ◽  
Stuart H. M. Butchart ◽  
Arne O. Mooers ◽  
Folmer Bokma
Keyword(s):  
Extinction Risk ◽  
Population Decline ◽  
Bird Species ◽  
Iucn Red List ◽  
Red List ◽  
Extinction Rate ◽  
Critically Endangered Species ◽  
Extinction Rates ◽  
Historical Times ◽  
Risk Categories

Population decline is a process, yet estimates of current extinction rates often consider just the final step of that process by counting numbers of species lost in historical times. This neglects the increased extinction risk that affects a large proportion of species, and consequently underestimates the effective extinction rate. Here, we model observed trajectories through IUCN Red List extinction risk categories for all bird species globally over 28 years, and estimate an overall effective extinction rate of 2.17 × 10 −4 /species/year. This is six times higher than the rate of outright extinction since 1500, as a consequence of the large number of species whose status is deteriorating. We very conservatively estimate that global conservation efforts have reduced the effective extinction rate by 40%, but mostly through preventing critically endangered species from going extinct rather than by preventing species at low risk from moving into higher-risk categories. Our findings suggest that extinction risk in birds is accumulating much more than previously appreciated, but would be even greater without conservation efforts.

scholarly journals Regional Red List assessment of tree species in upper montane forests of the Tropical Andes

Oryx ◽  
2015 ◽  
Vol 49 (3) ◽  
pp. 397-409 ◽  
Author(s):  
Natalia Tejedor Garavito ◽  
Adrian C. Newton ◽  
Sara Oldfield
Keyword(s):  
Tree Species ◽  
Expert Knowledge ◽  
Extinction Risk ◽  
Plant Species Richness ◽  
Iucn Red List ◽  
Red List ◽  
Conservation Strategies ◽  
Tropical Andes ◽  
Conservation Assessment ◽  
Distribution Maps

AbstractThe Tropical Andes are characterized by a high level of endemism and plant species richness but are under pressure from human activities. We present the first regional conservation assessment of upper montane tree species in this region. We identified 3,750 tree species as occurring in this region, of which 917 were excluded because of a lack of data on their distribution. We identified a subset of 129 taxa that were restricted to higher elevations (> 1,500 m) but occurred in more than one country, thus excluding local endemics evaluated in previous national assessments. Distribution maps were created for each of these selected species, and extinction risk was assessed according to the IUCN Red List categories and criteria (version 3.1), drawing on expert knowledge elicited from a regional network of specialists. We assessed one species, Polylepis microphylla, as Critically Endangered, 47 species as Endangered and 28 as Vulnerable. Overall, 60% of the species evaluated were categorized as threatened, or 73% if national endemics are included. It is recommended that extinction risk assessments for tree species be used to inform the development of conservation strategies in the region, to avoid further loss of this important element of biodiversity.

scholarly journals The changing fates of the world's mammals

2011 ◽  
Vol 366 (1578) ◽  
pp. 2598-2610 ◽  
Author(s):  
Michael Hoffmann ◽  
Jerrold L. Belant ◽  
Janice S. Chanson ◽  
Neil A. Cox ◽  
John Lamoreux ◽  
...  
Keyword(s):  
Captive Breeding ◽  
Extinction Risk ◽  
Conservation Status ◽  
Iucn Red List ◽  
Red List ◽  
Mammal Species ◽  
International Union ◽  
The Status ◽  
Conservation Actions ◽  
In The Wild

A recent complete assessment of the conservation status of 5487 mammal species demonstrated that at least one-fifth are at risk of extinction in the wild. We retrospectively identified genuine changes in extinction risk for mammals between 1996 and 2008 to calculate changes in the International Union for Conservation of Nature (IUCN) Red List Index (RLI). Species-level trends in the conservation status of mammalian diversity reveal that extinction risk in large-bodied species is increasing, and that the rate of deterioration has been most accelerated in the Indomalayan and Australasian realms. Expanding agriculture and hunting have been the main drivers of increased extinction risk in mammals. Site-based protection and management, legislation, and captive-breeding and reintroduction programmes have led to improvements in 24 species. We contextualize these changes, and explain why both deteriorations and improvements may be under-reported. Although this study highlights where conservation actions are leading to improvements, it fails to account for instances where conservation has prevented further deteriorations in the status of the world's mammals. The continued utility of the RLI is dependent on sustained investment to ensure repeated assessments of mammals over time and to facilitate future calculations of the RLI and measurement against global targets.

scholarly journals Evaluating the extinction risk of Ligusticum canbyi (Osha): Using the IUCN Red List

2018 ◽  
Author(s):  
H Moothoo ◽  
DJ Leaman ◽  
WL Applequist ◽  
PN Brown
Keyword(s):  
Extinction Risk ◽  
Iucn Red List ◽  
Red List

scholarly journals ANALYSIS 16S RDNA OF THE TURTLES IN FORECLOSURE CAGES AT PADEI LAUT, CENTRAL SULAWESI, INDONESIA

2017 ◽  
Vol 23 (1) ◽  
pp. 39
Author(s):  
Adriani Sri Nastiti ◽  
Masayu Rahmia Anwar Putri ◽  
Joni Haryadi ◽  
Arif Wibowo ◽  
Ngurah N Wiadnyana
Keyword(s):  
Carapace Length ◽  
Genetic Relationships ◽  
Chelonia Mydas ◽  
Iucn Red List ◽  
Red List ◽  
Marine Turtle ◽  
Green Turtles ◽  
Illegal Fishing ◽  
Central Sulawesi

Marine turtle is one of the protected aquatic animals as listed in CITES Appendix and IUCN red list. However, illegal fishing of marine turtle is still occurred Padei Laut Village, in Morowali Regency, Central Sulawesi Province, Indonesia. The research aims to study the population of marine turtle based on the carapace length and the genetic relationships. Data of carapace length was measured in-situ and genetic analysis was used mitochondrial DNA. The results showed that the carapace (ten samples which was green turtles/Chelonia mydas) was ranges between 42-102 cm; 91% of samples was immature and 9% was mature. Moreover, it also revealed that those turtles resembled by 99.98% of genetic similarity.

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