Informing Decisions on an Extremely Data Poor Species Facing Imminent Extinction
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Informing decisions on an extremely data poor species facing imminent extinction M ATTHEW J. GRAINGER,DUSIT N GOPRASERT P HILIP J.K. MC G OWAN and T OMMASO S AVINI Abstract Some of the species that are believed to have the Convention on Biological Diversity’s Strategic Plan for highest probability of extinction are also amongst the Biodiversity – (Secretariat of the Convention on most poorly known, and this makes it extremely difficult Biological Diversity, ) and target . of the to decide how to spend scarce resources. Assessments of UN’s Sustainable Development Goals (UN Sustainable conservation status made on the basis of loss or degradation Development Knowledge Platform, ). Our understand- of habitat and lack of records may provide compelling indi- ing of how high the probability of extinction is for individual cations of a decline in geographical range and population species is variable, as is our ability to identify places that size, but they do not help identify where conservation action should be priorities for action. In some instances, species might be best targeted. Methods for assessing the probabil- are well known and easily detectable, meaning that there ity of extinction and for modelling species’ distributions is a sound basis for identifying where and how to act. For exist, but their data requirements often exceed the informa- other species, however, it is extremely difficult to be confi- tion that is available for some of the most urgent conserva- dent about their proximity to extinction, let alone decide tion cases. Here we use all available information (localities, where searches should be focused or where conservation in- expert information, climate and landcover) about a high- terventions should be implemented. This variation in our priority Vietnamese bird species (Edwards’s pheasant understanding is typically a result of variable information Lophura edwardsi) to assess objectively the probability of about species, across both space and time, which, in turn, its persistence, and where surveys or other conservation ac- is attributable to factors such as detectability (Bibby et al., tion should be targeted. It is clear that the species is on the ), search effort (Boakes et al., ) and how well infor- threshold of extinction and there is an urgent need to survey mation is documented and made accessible (Boakes et al., Bach Ma National Park (including the extension) and to b). consider surveying Ke Go Nature Reserve. This approach South-east Asia has been highlighted as a region where has potential to help identify where conservation action there is both a high risk of extinction of many vertebrate should be targeted for other Critically Endangered species species (e.g. Hoffmann et al., ) and a severe lack of in- for which there is an extreme scarcity of information. formation on where and how to act to prevent their extinc- tion (Duckworth et al., ). These concerns led to a call for Keywords Data, Edwards’s pheasant, extinction, Lophura urgent action to address the threats facing tropical Asia’s edwardsi, optimal linear estimator, Siamese fireback, silver species, at the World Conservation Congress (IUCN, pheasant ), and the establishment of the Asian Species Action Partnership (ASAP, ). For many of these species the available data on location or ecology are few, and they are often considered to be of Introduction poor quality, which typically refers to old records for pecies that are considered to be close to extinction which the date and location are uncertain. Using these re- Sare often a target for conservation action. This may in- cords without critical appraisal of the nature of this uncer- volve dedicated action by conservation organizations, tainty could result in subjective assessments of where a working nationally or internationally (e.g. the Alliance for species may still occur, what its habitat is and where searches Zero Extinction, and BirdLife International through its should be focused. ’ Preventing Extinctions Programme), or the establishment Since Edwards s pheasant Lophura edwardsi was recate- of global policy targets, such as Aichi Target of the gorized as Critically Endangered on the IUCN Red List in there has been increasing attention to its conservation. It is vital, therefore, that as much information as possible, MATTHEW J. GRAINGER and PHILIP J.K. MCGOWAN (Corresponding author) School even if of unknown quality, is used as the basis for defining of Biology, Newcastle University, Newcastle upon Tyne NE1 7RU, UK ’ E-mail [email protected] the species status and deciding what conservation action should be undertaken. Here we make use of all available in- DUSIT NGOPRASERT and TOMMASO SAVINI Conservation Ecology Programme, King ’ Mongkut’s University of Technology Thonburi, Bangkok, Thailand formation to model the potential for extinction of Edwards s Received January . Revision requested February . pheasant and compare this with the two other Lophura spe- Accepted May . First published online August . cies inhabiting the same area. We then examine the spatial Oryx, 2019, 53(3), 484–490 © 2017 Fauna & Flora International doi:10.1017/S0030605317000813 Downloaded from https://www.cambridge.org/core. IP address: 170.106.40.139, on 28 Sep 2021 at 22:46:57, subject to the Cambridge Core terms of use, available at https://www.cambridge.org/core/terms. https://doi.org/10.1017/S0030605317000813 Data poor species facing extinction 485 uncertainty associated with the location data to determine if Modelling time to extinction a species distribution model could be produced to guide sur- vey effort. Finally, we produce a Bayesian model to predict The optimal linear estimator (Cooke, ; Roberts & Solow, ’ current habitat availability and identify sites where the spe- ; Solow, ), or Cooke s estimator (Collen et al., cies may still occur. ), is a non-parametric extinction date estimator. The approach is based on the Weibull distribution, a two- parameter model that has its origin in engineering risk analysis (Solow, ; Collen et al., ). The technique The study species: Edwards’s pheasant is considered robust where the probability of observing a In Edwards’s pheasant was uplisted to Critically species is low, and it does not assume that sighting effort Endangered (BirdLife International, ) because of the has been equal over time (Rivadeneira et al., ). Even lack of recent records (the last being a poached individual when the assumptions are not met fully because of the real- in ; one record in is unconfirmed and another ities of search effort and data availability, the optimal linear is of a captive individual with an unknown history; S.P. estimator is broadly accurate (Collen et al., ; Clements Mahood & J.C. Eames, pers. comm.), extremely high hunt- et al., ). Its prediction of time to extinction (TE) based ing pressure, and habitat fragmentation and degradation on the k most recent sightings is described by Solow ( ). throughout its known range (BirdLife International, ). There is uncertainty regarding how best to determine k. All of this led to increasing concern for the survival of the In theory it should be only the most recent sightings (Solow, species. Since , searches have been conducted at some ), but Collen et al. ( ) showed that increasing the potential sites but no evidence of the species’ existence has number of sightings used (tested to a maximum of sight- been found, although other Galliformes species have been ings) increases the accuracy of prediction. However, the ’ recorded (Pham & Le, ). First described in , records large gap in the sighting record of Edwards s pheasant dur- of the species are restricted to central Vietnam (Ha Tinh, ing the First Indochina War and the subsequent Vietnam – Quang Binh, Quang Tri, Thua Thein Hue Provinces), an War ( ) invalidates the assumptions of the optimal area long considered to be of conservation concern because linear estimator if applied to a series of records that spans of high endemism and the high level of threat to which spe- this gap (C. Clements, pers. comm., December ) and cies are subjected (Eames et al., ). Two other forms of so we used only the most recent records ( onwards). The Lophura were thought to be closely related species until re- data for this analysis consisted of the year of each confirmed cently, but are now considered to be conspecific: the imper- observation and a test year ( ). We used the package ial pheasant L. imperialis has been shown to be a naturally sExtinct (Clements, )inRv. (R Development occurring hybrid of Edwards’s pheasant and the silver Core Team, ) to calculate the optimal linear estimator ’ pheasant L. nycthemera (Hennache et al., ), and the for Edwards s pheasant and two congeneric species, the sil- Vietnamese pheasant L. hatinhensis is now considered to ver pheasant and the Siamese fireback L. diardi, which are be an inbred form of Edwards’s pheasant (Hennache extant in the region. Data for these other Lophura pheasants et al., ). Henceforth we refer to all forms of the species were also extracted from Boakes et al. ( a), with more re- as Edwards’s pheasant. The species went unrecorded be- cent records extracted from the Global Biodiversity tween the early s and late s, during which time Information Facility (GBIF, ). much of its suspected habitat was further defoliated and de- graded (BirdLife International, ). Spatial uncertainty We suspect that there is positional uncertainty associated Methods with some, if not all, of the location points and that for some records this is up to km (some locations were re- Location data ported as the nearest commune, village or district centre). Positional uncertainty in species distribution models has Geo-referenced location data for Edwards’s pheasant were been evaluated for cases in which errors were known and extracted from the Galliformes database of Boakes et al. relatively small (, km), and found to have little effect (a). As noted above, records previously ascribed to L. (Graham et al., ; Johnson & Gillingham, ). hatinhensis and L.