Key terms and concepts in the IUCN Red List Criteria. The IUCN Red List of Threatened Species

Transcription

1 Key terms and concepts in the IUCN Red List Criteria The IUCN Red List of Threatened Species

2 Rabb s Fringe-limbed Treefrog Ecnomiohyla rabborum Photo Brad Wilson Range: Known from 3-4 sites in the immediate vicinity of the town Critically El Valle de Antón, Endangered between A2ace;B1ab(iii) m in central Panama. Suspected to be endemic to this area. Population: Based on: Was never common, but after detection of the chytrid Drastic fungus population in the region decline 2006, over has become past 3 much harder to find. generations, Previously 1-2 inferred males could from be the heard apparent calling per night; only one individual has been heard since chytrid was detected. disappearance of most of the population Threats: Chytrid fungus in the area; some ongoing forest clearing. Restricted range combined with continuing Conservation: decline in Attempts extent and at captive quality breeding of habitat. have been unsuccessful. Surveys are conducted regularly.

3 Population Size (mature individuals only) Subpopulations Population

4 Key terms and concepts Generation Length Used to scale time-based measurements to account for different survival and reproduction rates e.g. 50% population decline measured over 3 generations Only a few of us are assessed using this criterion!

5 Key terms and concepts Generation Length Several definitions (all acceptable): Average age of parents of the current cohort (i.e., newborn individuals in the population) Mean age at which a cohort of newborns produce offspring Age at which 50% total reproductive output is achieved Mean age of parents in a population at the stable age distribution Time required for the population to increase by the replacement rate Scales time-based measurements to account for different survival/reproduction rates. Reflects turnover rate of breeders. Always use natural generation length. See the User Guidelines for methods of calculating generation length (worksheet available on request)

6 Key terms and concepts Reduction Reduction is a decline in population size of at least the % stated in criterion A over the specified time period. Population Size Time Continuing Decline Continuing Decline is a recent, current or projected future decline which is liable to continue unless remedial measures are taken.

7 Extreme Fluctuations Key terms and concepts Population size or distribution area varies widely, rapidly and frequently (typically tenfold increase or decrease) Population Size 25,000 20,000 15,000 10,000 5,000 0 Jan (yr 1) July (yr 1) Jan (yr 2) July (yr 2) Jan (yr 3) July (yr 3) Jan (yr 4) July (yr 4) Jan (yr 5) July (yr 5) Jan (yr 6) July (yr 6) Real changes in total population size (e.g., dormant eggs/seeds damaged or lost) therefore extreme fluctuation

8 Extreme Fluctuations Key terms and concepts Population Size July (yr 1) Jan (yr 2) July (yr 2) Jan (yr 3) July (yr 3) Jan (yr 4) July (yr 4) Jan (yr 5) Natural seasonal fluctuations flux of individuals between different life stages. Not real changes in total population size, therefore not extreme fluctuation

9 Severely Fragmented Key terms and concepts Most individuals (>50%) found in small, isolated subpopulations between which there is very little dispersal. These subpopulations may be too small to be viable. Taxa with highly mobile adult stages or producing large numbers of small, mobile diaspores can disperse more easily and are not so vulnerable to isolation through fragmented habitats. Taxa producing small numbers of diaspores (or none at all), or only large ones are less able to disperse over wide areas and are more easily isolated.

10 Severely Fragmented Key terms and concepts Most individuals (>50%) found in small, isolated subpopulations between which there is very little dispersal. These subpopulations may be too small to be viable. Taxa with highly mobile adult stages or producing large numbers of small, mobile diaspores can disperse more easily and are not so vulnerable to isolation through fragmented habitats. Remember 3 conditions! 1) Occurs in fragmented habitat patches 2) Poor dispersal capacity Taxa producing small numbers of diaspores (or none at all), or only large ones are less able to disperse over wide areas and are more easily isolated. 3) 50% in fragmented and isolated habitat patches

11 Key terms and concepts Extent of Occurrence Area of Occupancy Extent of Occurrence: area within the shortest continuous imaginary boundary drawn around all known, inferred, or projected sites presently occupied by the taxon. EOO the species range. Area of Occupancy: area within the extent of occurrence which is actually occupied by the taxon (measured by overlaying a 2x2 km grid and counting number of occupied cells).

12 Key terms and concepts EOO AOO

13 Key terms and concepts Extent of Occurrence Comparison of taxa with same AOO but different EOO a single threatening event is more likely to impact the taxon with the smaller EOO: Threatening event AOO = 10x4 = 40 km 2 EOO = 44 km² AOO = 10x4 = 40 km 2 EOO = 105 km²

14 Key terms and concepts Extent of Occurrence Comparison of taxa with same AOO but different EOO a single threatening event is more likely to impact the taxon with the smaller EOO: AOO = 7x4 = 28 km 2 EOO = 28 km² AOO = 8x4 = 32 km 2 EOO = 82 km²

15 Key terms and concepts Extent of Occurrence Migratory species: summer summer summer winter EOO

16 Area of Occupancy Key terms and concepts Linear habitats: AOO measurement must be consistent with threshold values in most cases, use 2x2 km grid for AOO estimates. AOO can be measured as the smallest area essential at any stage to the survival

17 For the sake of continuity Key terms and concepts Amphibian EOO and AOO are calculated as the total area of mapped polygons, instead of with a minimum convex polygon or 2x2 grid until further notice.

18 Key terms and concepts Location Location is a geographically or ecologically distinct area in which a single threatening event can rapidly affect all individuals of the taxon. If there are no plausible threats, do not consider locations at all.

19 Key terms and concepts Location Group exercise Invasive species 1 population 2 subpopulations 2 locations 1 affected 1 unaffected

20 Key terms and concepts Location Group exercise Pollution 1 global population 2 subpopulations 4 locations 1 affected 3 unaffected Groupings of the species affected by a single pollution event

21 Key terms and concepts Location Amphibian example: Callixalus pictus Distribution: This species is known only from the Itombwe and Kabobo highlands of eastern Democratic Republic of Congo. It has never been found below 2,100 m asl, and is rare below 2,400 m asl. Its range, taken as a proxy for extent of occurrence (EOO), has been estimated as 6,722 km 2 and it is considered to be confined to two threat-defined locations. There have been no recent, confirmed records of this species (E. Greenbaum and M. Menegon pers, comm June 2012). Its area of occupancy (AOO) is estimated at approximately 1,500 km 2 based on the forested area above 2,400 m asl.

22 Key terms and concepts Location Amphibian example: Callixalus pictus Threats: It appears to be restricted to unprotected habitats that are being lost due to agriculture, livestock farming, wood extraction, and expanding human settlements. There are current efforts to create protected areas to reduce these threats. 1 global population 2 subpopulations Same threats to both subpopulations 2 locations

23 Key terms and concepts Location Amphibian example: Boulengerula niedeni Distribution: This species is known between 1,000-1,504 m asl (Malonza et al. 2010) on Sagala Hill, in the Taita Hills, southeastern Kenya. This mountain block is isolated from other similar habitat by the arid Tsavo plains Threats: Very little natural forest remains on Sagalla Hill, but it is not clear whether or not these caecilians might sometimes benefit from low intensity agriculture. The top of Sagalla Hill is covered by eucalyptus and pine plantations, which is contributing to ground water depletion and substantial changes to the soil, and the species has not been found under these conditions.

24 Key terms and concepts Location Amphibian example: Boulengerula niedeni Location: Its range is perceived as comprising two threat-defined locations, one above and one below the eucalyptus plantation. 1 global population 1 plausible threat 2 locations

25 Key terms and concepts Location If most serious threat does not affect entire distribution: can use other threats to count locations in areas not affected by most serious threat. Pollution Fishing Pollution Future: Dam 5 locations please document them!

26 Key terms and concepts Quantitative Analysis Quantitative Analysis is any form of analysis which estimates the extinction probability of a taxon based on known life history, habitat requirements, threats and any specified management options (e.g., Population Viability Analysis (PVA)).

27 Dealing with Change and Uncertainty The IUCN Red List of Threatened Species

28 The IUCN Categories Extinct (EX) Extinct in the Wild (EW) Red List Categories + Possibly Extinct CR(PE) or CR(PEW) Adequate data Threatened categories Critically Endangered (CR) Endangered (EN) Vulnerable (VU) Extinction Risk All species Evaluated Near Threatened (NT) Least Concern (LC) Data Deficient (DD) _ Not Evaluated (NE)

29 Red List Categories Extinct (EX) A taxon is Extinct when there is no reasonable doubt that the last individual has died Extinct in the Wild (EW) Dodo, Raphus cucullatus A taxon is Extinct in the Wild when it is known only to survive in cultivation, in captivity or as a naturalized population (or populations) well outside the past range Photo Craig Hilton-Taylor Franklinia, Franklinia alatamaha

30 Red List Categories A taxon is threatened when the best available evidence indicates that it meets any of the criteria A to E for the thresholds stated in one of the three threatened categories: Critically Endangered, Endangered or Vulnerable. Critically Endangered (CR) CR taxa are considered to be facing an extremely high risk of extinction in the wild Endangered (EN) EN taxa are considered to be facing a very high risk of extinction in the wild Photo Wendy Strahm Mandrinette, Hibiscus fragilis Black-browed Albatross, Thalassarche melanophrys Vulnerable (VU) Photo Tony Palliser VU taxa are considered to be facing a high risk of extinction in the wild Photo Craig Hilton- Taylor Golden Pagoda, Mimetes chrysanthus

31 Red List Categories A taxon is threatened when the best available evidence indicates that it meets any of the criteria A to E for the thresholds stated in one of the three threatened categories: Critically Endangered, Endangered or Vulnerable. Critically Endangered (CR) CR taxa are considered to be facing an extremely high risk of extinction in the wild Endangered (EN) EN taxa are considered to be facing a very high risk of extinction in the wild Critically Endangered (Possibly Extinct) Photo Wendy Strahm Possibly Extinct tag developed to Mandrinette, Hibiscus fragilis identify CR taxa that are likely already EX but for Black-browed which Albatross, Thalassarche confirmation is required melanophrys Vulnerable (VU) Photo Tony Palliser VU taxa are considered to be facing a high risk of extinction in the wild Photo Craig Hilton- Taylor Golden Pagoda, Mimetes chrysanthus

32 Red List Categories Near Threatened (NT) A taxon is Near Threatened when it has been evaluated against the criteria and does not qualify for CR, EN or VU now, but is close to qualifying for or is likely to qualify for a threatened category in the near future Least Concern (LC) Photo H. Fraga Macaronesian Laurel, Laurus azorica A taxon is Least Concern when it has been evaluated against the criteria and does not qualify for CR, EN, VU or NT. Widespread and abundant taxa are included in this category Olive Baboon, Papio anumbis Photo Caroline Pollock

33 Red List Categories Data Deficient (DD) A taxon is Data Deficient when there is inadequate information to make a direct, or indirect, assessment of its risk of extinction based on its distribution and/or population status Tree Tomato Solanum [Cyphomandra] betacea Not Evaluated (NE) A taxon is Not Evaluated when it has not yet been evaluated against the criteria

34 Red List Categories Data Deficient (DD) Not Evaluated (NE) Although DD and NE are not threatened categories, taxa classed as DD or NE should NOT be considered as not threatened

35 A Nature of the Criteria CRITERIA Population reduction THREATENED CATEGORIES B Restricted geographic range Critically Endangered (CR) C Small population size & decline Quantitative thresholds Endangered (EN) D E Very small or restricted population Quantitative analysis Vulnerable (VU)

36 Why use multiple criteria? Not all the criteria are appropriate to all taxa All taxa being assessed must be evaluated against each criterion Meeting any one of the criteria qualifies a taxon for listing at that level of threat All criteria met at the highest level of threat should be listed

37 Red List Categories Changing Red List Category There are various reasons for a species to change category: NON-GENUINE status change New information Taxonomic changes Incorrect data used previously Criteria revision (version 2.3 (1994) versus version 3.1 (2001)) Knowledge of the criteria GENUINE status change

38 Red List Categories Genuine deterioration Red List Status LC NT VU Genuine deterioration in status: uplist to higher threat category immediately EN CR Time

39 Genuine Improvements: The Five Year Rule Red List status Downlist to lower threat category only when the higher category thresholds have not been met for FIVE years NT VU CR EN CR Time (yrs) First assessment: CR CR thresholds no longer met 5 years Reassess and Can reassess and update documentation, but category must remain as for first assessment : CR alter status appropriately

40 Data Quality & Uncertainty The IUCN Red List of Threatened Species

41 Red List Documentation All species in the Red List have supporting documentation Justifies the selected category and criteria Allows analysis of Red List data (information coded using standard Classification Schemes) Taxonomy including authority details Common names Red List Category and Criteria Countries of occurrence Map of distribution Rationale for the assessment (supporting the criteria used) Names of assessors & contributors Habitat preferences (text & codes) Major Threats (text and codes) Conservation Measures in place & needed (text and codes) Trade and Use Citations list Reasons for any category changes 41

42 Data quality & uncertainty Dealing with a lack of high quality data The threatened categories use quantitative thresholds BUT a lack of high quality data should not deter assessors from applying the IUCN criteria.

43

44 Data quality & uncertainty Observed Observed information is directly based on well-documented observations of all known individuals in the population. For example: entire global population occurs in only one area and all individuals counted each year Year 3 Year population 4 population = 15 = 8 Year Year 2 population 1 population = 17 = 19 Observed reduction of 58% over 4 years

45 Data quality & uncertainty Estimated Estimated information is based on calculations that may involve assumptions and/or interpolations in time (in the past). For example: repeated surveys of sample sites across total range A B C Date Site A Site B Site C Site D All Population size estimate across total range , , , D Sampling sites Estimated 65% reduction between 2005 and 2008

46 Data quality & uncertainty Projected Projected information is the same as estimated, but the variable of interest is extrapolated in time towards the future For example: repeated surveys of sample sites across total range with knowledge of ongoing causes of population decline A B C Population size Projected future decline based on habitat loss continuing at same rate as in the past D Estimated past decline based on collected data 10 yrs ago now 10 yrs in future

47 Data quality & uncertainty Inferred Inferred information is based on variables that are indirectly related to the variable of interest, but in the same general type of units (e.g. number of individuals or area or number of subpopulations). Relies on more assumptions than estimated data. For example: Past and current population sizes are not known, but trade figures for that species have declined over time. Fresh Fish Inferred continuing decline in population size based on decline in trade statistics for this species

48 Data quality & uncertainty Suspected Suspected information is based on circumstantial evidence, or on variables in different types of units. In general, this can be based on any factor related to population abundance or distribution. For example: Rate of habitat loss is known, but past and current population sizes are unknown. Population size??? Suspected population reduction of e.g., >50% based on 75% of habitat being lost Population size?? Could infer a continuing decline in population size, but suspect a reduction at a specific rate (%)

49 Data quality & uncertainty Dealing with data uncertainty Uncertainty in the data itself (different to the lack of data) should also be considered in a Red List assessment For example: A species has a range of population size estimates from 3 separate studies. Study A: Population size = (Endangered) Study B: Population size = (Endangered or Vulnerable) Study C: Population size = (Vulnerable)

50 Data quality & uncertainty Dealing with data uncertainty 1. Record the range of possible values based on the available studies: Based on the studies A, B and C, the current population size is between 100 and State the range of potential Red List Categories that may be used based on the range of data: Critically Endangered Endangered Vulnerable 3. Select one of these categories using all available information (on population size, trends, habitat status, ongoing threats, etc.) to justify your decision: Critically Endangered Endangered Vulnerable EN

51 Data quality & uncertainty Dealing with data uncertainty 1. Record the range of possible values based on the available studies: Based on the studies A, B and C, the current population size is between 100 and 410 The Red List Guidelines request us to use precautionary but realistic attitude toward uncertainty 2. State the range of potential Red List Categories that may be used based on the range of data: Critically Endangered Endangered Vulnerable 3. Select one of these categories using all available information (on population size, trends, habitat status, ongoing threats, etc.) to justify your decision: Critically Endangered Endangered Vulnerable EN

52 Data quality & uncertainty Dealing with data uncertainty 4. Species with VERY uncertain data (suggesting in a very wide range of potential categories) should be listed as Data Deficient. CR EN VU NT LC Data Deficient

53 Data quality & uncertainty Attitudes towards uncertainty Sources of uncertainty (Akçakaya et al. 2000): Semantic uncertainty Measurement error Natural variability Uncertainty can lead to differing assessments because different aspects of uncertainty are emphasized Precautionary Evidentiary