Главная Manuals Guidelines for Using the IUCN Red List Categories and Criteria Version 15.1 (July 2022)
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Guidelines for Using the IUCN Red List
Categories and Criteria
Version 15.1
(July 2022)
Prepared by the Standards and Petitions Committee
of the IUCN Species Survival Commission.
Citation: IUCN Standards and Petitions Committee. 2022. Guidelines for Using the IUCN
Red List Categories and Criteria. Version 15.1. Prepared by the Standards and Petitions
Committee. Downloadable from
https://www.iucnredlist.org/documents/RedListGuidelines.pdf.
THE IUCN RED LIST OF THREATENED SPECIES™
Contents
1.
INTRODUCTION
4
2.
AN OUTLINE OF THE RED LIST CATEGORIES AND CRITERIA
4
2.1 TAXONOMIC LEVEL AND SCOPE OF THE CATEGORIZATION PROCESS
4
2.1.1
Taxonomic scale of categorization
4
2.1.2
Geographical scale of categorization
6
2.1.3
Introduced taxa and subpopulations
7
2.1.4
Managed subpopulations
8
2.2 NATURE OF THE CATEGORIES
8
2.2.1
Transfer between categories
11
2.3 NATURE OF THE CRITERIA
14
2.3.1
The quantitative thresholds
16
2.4 CONSERVATION PRIORITIES AND ACTIONS
18
2.5 DOCUMENTATION
18
3.
DATA QUALITY
19
3.1 DATA AVAILABILITY, INFERENCE, SUSPICION AND PROJECTION
19
3.2 UNCERTAINTY
22
3.2.1
Types of uncertainty
22
3.2.2
Representing uncertainty
23
3.2.3
Dispute tolerance and risk tolerance
23
3.2.4
Dealing with uncertainty
24
3.2.5
Documenting uncertainty and interpreting listings
24
3.2.6
Uncertainty and the application of the categories Data Deficient and Near Threatened
24
4.
DEFINITIONS OF TERMS USED IN THE CRITERIA AND THEIR CALCULATION
24
4.1 POPULATION AND POPULATION SIZE (CRITERIA A, C AND D)
25
4.2 SUBPOPULATIONS (CRITERIA B AND C)
25
4.3 MATURE INDIVIDUALS (CRITERIA A, B, C AND D)
25
4.3.1
Notes on defining mature individuals
26
4.3.2
Clonal colonial organisms
27
4.3.3
Fishes
28
4.3.4
Sex-changing organisms
28
4.3.5
Trees
29
4.4 GENERATION (CRITERIA A, C1 AND E)
29
4.5 REDUCTION (CRITERION A)
32
4.5.1
Calculating population reduction using statistical methods
32
4.5.2
Calculating population reduction using population models
37
4.5.3
Taxa with widely distributed or multiple subpopulations
37
4.5.4
Estimating overall reduction
38
4.5.5
Dealing with uncertainty
41
4.5.6
Fluctuations vs. reduction
43
4.6 CONTINUING DECLINE (CRITERIA B AND C)
44
4.7 EXTREME FLUCTUATIONS (CRITERIA B AND C2)
45
4.8 SEVERELY FRAGMENTED (CRITERION B)
48
4.9 EXTENT OF OCCURRENCE (CRITERIA A AND B)
49
4.10 AREA OF OCCUPANCY (CRITERIA A, B AND D)
52
4.10.1 Problems of scale
53
4.10.2 Methods for estimating AOO
54
4.10.3 The appropriate scale
54
4.10.4 Scale-area relationships
54
4.10.5 Scale correction factors
55
4.10.6 "Linear" habitat
58
4.10.7 AOO and EOO based on habitat maps and models
58
4.10.8 Effect of sampling effort and detectability on estimates of AOO
60
4.10.9 Complementarity of AOO, EOO and number of locations
60
4.11 LOCATION (CRITERIA B AND D)
61
4.12 QUANTITATIVE ANALYSIS (CRITERION E)
62
5.
GUIDELINES FOR APPLYING CRITERION A
62
5.1 THE BASIS OF REDUCTIONS
64
Red List Guidelines
3
5.2 THE USE OF TIME CAPS IN CRITERION A
66
5.3 HOW TO APPLY CRITERION A4
66
5.4 REDUCTION FOLLOWED BY SHORT-TERM STABILIZATION OR INCREASE: THE 'SKI-JUMP' EFFECT
67
5.5 HISTORICAL REDUCTION FOLLOWED BY LONG-TERM STABILIZATION: SEVERELY DEPLETED
POPULATIONS
67
5.6 FISHERIES
68
5.6.1
Fisheries management and extinction risk
68
5.6.2
Technical aspects of using criterion A for fisheries
69
5.7 LONG-LIVED TAXA
69
5.8 RELATIONSHIP BETWEEN LOSS OF HABITAT AND POPULATION REDUCTION
69
6.
GUIDELINES FOR APPLYING CRITERION B
70
7.
GUIDELINES FOR APPLYING CRITERION C
71
8.
GUIDELINES FOR APPLYING CRITERION D
72
8.1 TAXA KNOWN ONLY FROM THE TYPE LOCALITY
73
8.2 EXAMPLE OF APPLYING CRITERION D
73
8.3 EXAMPLE OF APPLYING CRITERION D2
73
9.
GUIDELINES FOR APPLYING CRITERION E
73
9.1 WHAT IS EXTINCTION?
74
9.2 WHICH METHOD CAN BE USED?
74
9.3 ARE THERE SUFFICIENT DATA?
75
9.4 MODEL COMPONENTS AND PARAMETERS
75
9.4.1
Density dependence
76
9.4.2
Temporal variability
76
9.4.3
Spatial variability
76
9.5 INCORPORATING UNCERTAINTY
77
9.6 DOCUMENTATION REQUIREMENTS
77
10. GUIDELINES FOR APPLYING THE CATEGORIES DD, NT AND NE
77
10.1 WHEN TO USE THE CATEGORY NEAR THREATENED
77
10.2 NOT EVALUATED AND DATA DEFICIENT
79
10.3 WHEN TO USE DATA DEFICIENT
79
10.4 WHEN NOT TO USE DATA DEFICIENT
80
11. GUIDELINES FOR APPLYING THE EXTINCT CATEGORIES AND TAG
81
11.1 THE EXTINCT CATEGORIES (EX AND EW)
81
11.2
‘POSSIBLY EXTINCT’ TAGS FOR CRITICALLY ENDANGERED TAXA
82
11.3 ASSIGNING TAXA TO EX OR CR(PE)
83
11.3.1 The Threats Model
84
11.3.2 The Records and Surveys Model
85
11.3.3 Interpreting the model results
86
11.4 CALCULATING THE NUMBER OF EXTINCT SPECIES AND EXTINCTION RATES
87
12. GUIDELINES FOR THREATENING PROCESSES
88
12.1 GLOBAL CLIMATE CHANGE
88
12.1.1 Time horizons
89
12.1.2 Suggested steps for applying the criteria under climate change
90
12.1.3 Mechanisms
92
12.1.4 Very restricted distribution and plausibility and immediacy of threat (VU D2)
92
12.1.5 Definition of "Location" under climate change (B1, B2, D2)
94
12.1.6 Severe fragmentation (B1, B2, and C2)
95
12.1.7 Extreme fluctuations (B1, B2, and C2)
96
12.1.8 Inferring population reduction and continuing decline (A3, A4, B1, B2, C2)
96
12.1.9 Inferring reductions from bioclimatic models (A3, A4)
96
12.1.10 Inferring reductions from demographic change
97
12.1.11 Estimating extinction risk quantitatively with coupled habitat and population models (E)
98
12.1.12 Using bioclimate models
99
13. REFERENCES
103
14. APPENDIX: SUMMARY OF CHANGES TO THE GUIDELINES
111
Red List Guidelines
4
1. Introduction
The IUCN Red List Categories and Criteria were first published in 1994 following six years
of research and broad consultation (IUCN 1994). The 1994 IUCN Categories and Criteria were
developed to improve objectivity and transparency in assessing the conservation status of
species, and therefore to improve consistency and understanding among users. The 1994
categories and criteria were applied to a large number of species in compiling the 1996 Red
List of Threatened Animals. The assessment of many species for the 1996 Red List drew
attention to certain areas of difficulty, which led IUCN to initiate a review of the 1994
categories and criteria, which was undertaken during 1998 to 1999. This review was completed
and the IUCN Red List Categories and Criteria (version 3.1) are now published (IUCN 2001,
2012b).
This document provides guidelines to the application of version 3.1 of the categories and
criteria, and in so doing addresses many of the issues raised in the process of reviewing the
1994 categories and criteria. This document explains how the criteria should be applied to
determine whether a taxon belongs in a category of threat, and gives examples from different
taxonomic groups to illustrate the application of the criteria. These guidelines also provide
detailed explanations of the definitions of the many terms used in the criteria. The guidelines
should be used in conjunction with the official IUCN Red List Categories and Criteria booklet
(IUCN 2001, 2012b).
We expect to review and update these guidelines periodically, and input from all users of the
IUCN Red List Categories and Criteria are welcome. We especially welcome IUCN Specialist
Groups and Red List Authorities to submit examples that are illustrative of these guidelines.
We expect that the changes to these guidelines will be mostly additions of detail and not
changes in substance. In addition, we do not expect the IUCN Red List Criteria to be revised
in the near future, because a stable system is necessary to allow comparisons over time.
2. An Outline of the Red List Categories and Criteria
2.1 Taxonomic level and scope of the categorization process
2.1.1 Taxonomic scale of categorization
The criteria may be applied to any taxonomic unit at or below the species level. In these
guidelines, the terms ‘taxon’ and ‘taxa’ are used to represent species or lower taxonomic
levels, including forms that are not yet fully described, and excluding humans. There is
sufficient range among the different criteria to enable appropriate listing of taxa from the
complete taxonomic spectrum, with the exception of micro-organisms. In presenting the
results of applying criteria, the taxonomic unit used (species, subspecies, etc.) should be
specified. It should be noted that taxa below the rank of variety (e.g., forma, morph, cultivar),
are NOT included on the IUCN Red List, with the exception of assessments of subpopulations.
An assessment of the full species is required before assessments of taxa below the species
level (subspecies, variety or subpopulation) can be included on the IUCN Red List.
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5
Subpopulations: If a subpopulation assessed under the criteria is not isolated (i.e., if it may be
exchanging individuals with other subpopulations), its assessments must follow the regional
guidelines (IUCN 2003, 2012a). In addition, it must be a biological subpopulation (i.e., not
defined by political or national boundaries). Although the regional guidelines can in principle
be applied at any geographical scale, application within very small geographical areas is
strongly discouraged. The smaller the subpopulation as a proportion of the global population
of the species, the more often the subpopulation will exchange individuals with other
subpopulations. Therefore, the assessment of extinction risk based on the criteria would
become more unreliable (IUCN 2003, 2012a). See also Geographical scale of categorization
below.
Newly described species: The inclusion of newly described species on the IUCN Red List is
addressed on a case-by-case basis. The designated IUCN Red List Authority and/or IUCN
Global Species Programme staff (including staff from partner institutions working on Global
Species Assessment projects) will consult with relevant experts to ascertain how widely
accepted these are.
Undescribed species: The listing of undescribed species on the IUCN Red List is discouraged,
but in exceptional circumstances these may be included. There must be a clear conservation
benefit to justify the inclusion of such listings, or in the case of projects to completely assess
a taxonomic group, undescribed species that are listed as Least Concern (LC) or Data Deficient
(DD) may only be included if there is clear evidence that work is underway to describe the
species concerned and that the new species will be widely accepted. The new species
description should be published within four years of an undescribed species being included on
the IUCN Red List; if it is not published or is not in press after that time, the assessment will
be removed. For an undescribed species to be included on the IUCN Red List the following
conditions must be met:
There must be general agreement that the undescribed form is a clearly circumscribed
species
There must be a clear indication that work is underway to describe the species (e.g., a
draft manuscript in preparation or a paper with the new description already submitted
for publication)
Clear distribution information must be provided
Listing the undescribed species will potentially aid in its conservation
Specimen reference numbers (voucher collection details) must be provided to enable
the species to be traced without confusion
The museum, herbarium or other institution holding the collection/s and the individual/s
responsible for the proposal must be identified
Undescribed species sometimes have a local common name, if so this should be
provided, but if not, a recognizable common name should be coined, so that it can be
used to clearly indicate the identity of this taxon without any implication about scientific
validity.
Undescribed species are presented on the IUCN Red List by using the generic name and the
abbreviation sp. or sp. nov., sometimes followed by a provisional name in inverted commas
(e.g., Philautus sp. nov. 'Kalpatta'). Voucher collection details (collector’s name, specimen
number and institution where housed) must be provided so that they can be cited under the
Taxonomic Notes section of the species’ account on the Red List web site. Instances may
Red List Guidelines
6
arise where there are valid reasons for voucher collection details to be withheld. If this is
clearly indicated and justified by the assessor(s) concerned, the voucher information will be
suppressed from the public version of the species account. However, in such cases the voucher
information must still be supplied for the assessment to be accepted, and this information will
be held in confidence.
Undescribed species assessed as Least Concern (LC) or Data Deficient (DD) are not included
on the IUCN Red List as there is little conservation benefit to such listings.
Undescribed infraspecific taxa are not included on the IUCN Red List.
In summary, assessments of the following taxa may be included on the IUCN Red List
Species
Subspecies
Varieties (only for plants)
Subpopulations (provided certain conditions as described above are met)
Undescribed species (provided certain conditions as described above are met, and they
are not listed as LC or DD)
Assessments of the following taxa may NOT be included on the IUCN Red List
Taxa assessed locally, nationally or regionally unless they are global or subpopulation
assessments (see “Subpopulation” above, and section 2.1.2)
Hybrids (except for apomictic plant hybrids, which are treated as 'species')
Infraspecific ranks such as formas, morphs, subvarieties, varieties of subspecies,
cultivars, etc.
Domesticated taxa (in the case where a taxon comprises both domesticated and wild
individuals, only the wild population may be assessed and included; feral animals
derived from a domesticated source should not be included)
Taxa known to have gone Extinct before 1500 CE
Undescribed species assessed as Data Deficient or Least Concern (except in the case of
complete global assessments for a taxonomic group, see above)
Undescribed infraspecific taxa
Assessments of higher taxa (i.e., above the species level).
2.1.2 Geographical scale of categorization
The IUCN criteria are designed for global taxon assessments. However, many people are
interested in applying them to subsets of global data, especially at regional, national or local
levels. To do this it is important to refer to guidelines prepared by the IUCN SSC Regional
Applications Working Group (e.g., Gärdenfors et al. 2001; IUCN 2003, 2012a; Miller et al.
2007). When applied at national or regional levels it must be recognized that a global category
may not be the same as a national or regional category for a particular taxon. For example,
taxa classified as Least Concern globally might be Critically Endangered within a particular
region where numbers are very small or declining, perhaps only because they are at the
margins of their global range. Conversely, taxa classified as Vulnerable on the basis of their
global declines in numbers or range might, within a particular region where their populations
are stable, not even nearly meet the criteria for Vulnerable, i.e. be Least Concern. Although
this appears illogical, it is a result of the structure of the criteria. When such a situation occurs,
Red List Guidelines
7
interactions among sub-units should be carefully considered when planning conservation
actions.
Although the criteria (along with regional guidelines; IUCN 2012a) may be applied at any
geographical scale, application within very restricted geographical areas is strongly
discouraged (IUCN 2012a). In a small region, a wide-ranging taxon will frequently exchange
individuals with neighbouring regions, leading to unreliable assessments (IUCN 2012a).
It is also important to note that in any regional or national applications of the criteria, an
assessment of taxa endemic to that region or nation will be a global assessment; in these cases
great care must be taken to check that a global assessment has not already been undertaken by
an IUCN SSC Red List Authority (RLA), and that the final categorization is agreed with the
relevant RLA; see the regional guidelines for more details (IUCN 2003, 2012a).
2.1.3 Introduced taxa and subpopulations
In addition to wild subpopulations (see section 2.1.4) inside the natural range of a taxon, the
categorization process should also be applied to wild subpopulations resulting from
introductions outside the natural range, if all of the following conditions are met:
(a) The known or likely intent of the introduction was to reduce the extinction risk of the taxon
being introduced. In cases where the intent is unclear, the assessors should weigh the
available evidence to determine the most likely intent.
(b) The introduced subpopulation is geographically close to the natural range of the taxon.
What is considered to be geographically close enough should be determined by the
assessor, considering factors such as the area of the natural range, the nature of the
landscape separating the natural and the introduced range, and whether the taxon could
have dispersed to the introduced range without the effects of human impacts such as habitat
loss and fragmentation. For example, an introduced subpopulation in a continent distant
from the natural range would not qualify. On the other hand, most introduced
subpopulations within the same ecoregion as the natural range would qualify.
(c) The introduced subpopulation has produced viable offspring (i.e., offspring that have
reached maturity or are likely to do so).
(d) At least five years have passed since the introduction.
In cases where such introduced subpopulations are included in the assessment, assessors must
state and justify their inclusion in the assessment supporting documentation.
In some cases, taxa have successfully expanded their natural ranges into urban or semi-urban
areas, e.g., primates, foxes and some birds. In these instances urban areas should be considered
as part of the natural range, as the taxa have not been introduced.
In addition to taxa within their natural range and subpopulations resulting from introductions
outside the taxon’s natural range that conform to the conditions above (also referred to as
"benign introductions"), the criteria should also be applied to self-sustaining translocated or
re-introduced subpopulations (within the taxon’s natural range), regardless of the original goal
of such translocations or re-introductions. In such cases, the listing should indicate whether all
or part of the assessed population has been introduced. Also, in such cases, conditions (a) and
(b) above are not relevant, but conditions (c) and (d) must be met.
Red List Guidelines
8
2.1.4 Managed subpopulations
The IUCN Red List assessment should only be applied to wild populations. There is a
continuum of management intensities, from captive populations in zoos, aquaria and botanical
gardens to populations not benefiting from any conservation measure. Clearly, captive
populations are not considered "wild" and would be excluded from a Red List assessment (i.e.,
data from such populations are not considered in determining the species' status, except for
EW). On the other hand, subpopulations of many species are dependent on conservation
measures (such as protected areas) that are largely directed at mitigating human impacts. Such
subpopulations are generally considered "wild", and the data from such subpopulations are
used in Red List assessments. In between these are subpopulations that are managed at
moderate levels of intensity (Redford et al. 2011). For these subpopulations, the definition of
"wild" may be based on the intensity of management, and the expected viability of the
subpopulation without the management.
Subpopulations dependent on direct intervention are not considered wild, if they would go
extinct within 10 years without “intensive” management such as:
• providing most of the food needs of most individuals in the subpopulation;
• regularly supplementing the population from captive stock to prevent imminent extinction;
• breeding manipulations, such as cross-fostering and down-brooding (i.e., removing extra
chicks from large broods and giving to foster parents); or
• providing ongoing intensive veterinary care to most individuals.
Managed subpopulations are considered wild if the management is for counter-acting the
effects of human threats, such as:
• protected areas;
• anti-poaching patrols;
• providing artificial shelters (e.g., nest boxes for birds, roosting sites for bats);
• providing preventative treatments against disease outbreaks;
• preventing natural vegetation succession to maintain the species' habitat;
• translocating individuals between existing subpopulations (also see section 2.1.3);
• control measures against non-native competitors or predators, including the establishment
of exclusion fences, such as those used to keep out invasive predators;
• control measures against native competitors or predators if such species have increased
because of human activities (e.g., removing cowbird which have increased because of
habitat fragmentation); or
• occasionally supplementing the population from captive stock to increase genetic
variability.
This delineation of "wild" from "not wild" roughly corresponds to the difference between
"lightly managed species" and "intensively managed species" as defined by Redford et al.
(2011).
2.2 Nature of the categories
There are nine clearly defined categories into which every taxon in the world (excluding
micro-organisms) can be classified (Figure 2.1). Complete definitions of the categories are
given in Box 2.1. The first two categories in Figure 2.1 are relatively self-explanatory. Extinct
means that there is no reasonable doubt that the last individual has died. Extinct in the Wild
Red List Guidelines
9
means that the taxon is extinct in its natural habitat (see Introduced taxa above). The following
three categories, Critically Endangered, Endangered and Vulnerable, are assigned to taxa
on the basis of quantitative criteria that are designed to reflect varying degrees of threat of
extinction; taxa in any of these three categories are collectively referred to as ‘threatened’.
These criteria will be discussed further in the next section. The category Near Threatened is
applied to taxa that do not qualify as threatened now, but may be close to qualifying as
threatened, and to taxa that do not currently meet the criteria for a threatened category, but are
likely to do so if ongoing conservation actions abate or cease.
The category Least Concern is applied to taxa that do not qualify (and are not close to
qualifying) as threatened or Near Threatened. It is important to emphasize that "least concern"
simply means that, in terms of extinction risk, these species are of lesser concern than species
in other threat categories. It does not imply that these species are of no conservation concern.
Figure 2.1. Structure of the IUCN Red List Categories
Red List Guidelines
10
Box 2.1. The IUCN Red List Categories
EXTINCT (EX)
A taxon is Extinct when there is no reasonable doubt that the last individual has died. A taxon is presumed
Extinct when exhaustive surveys in known and/or expected habitat, at appropriate times (diurnal, seasonal,
annual), throughout its historic range have failed to record an individual. Surveys should be over a time frame
appropriate to the taxon’s life cycles and life form.
EXTINCT IN THE WILD (EW)
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. A taxon is presumed Extinct in the Wild when exhaustive
surveys in known and/or expected habitat, at appropriate times (diurnal, seasonal, annual), throughout its historic
range have failed to record an individual. Surveys should be over a time frame appropriate to the taxon's life
cycle and life form.
CRITICALLY ENDANGERED (CR)
A taxon is Critically Endangered when the best available evidence indicates that it meets any of the criteria A to
E for Critically Endangered, and it is therefore considered to be facing an extremely high risk of extinction in the
wild.
ENDANGERED (EN)
A taxon is Endangered when the best available evidence indicates that it meets any of the criteria A to E for
Endangered, and it is therefore considered to be facing a very high risk of extinction in the wild.
VULNERABLE (VU)
A taxon is Vulnerable when the best available evidence indicates that it meets any of the criteria A to E for
Vulnerable, and it is therefore considered to be facing a high risk of extinction in the wild.
NEAR THREATENED (NT)
A taxon is Near Threatened when it has been evaluated against the criteria but does not qualify for Critically
Endangered, Endangered or Vulnerable now, but is close to qualifying for or is likely to qualify for a threatened
category in the near future.
LEAST CONCERN (LC)
A taxon is Least Concern when it has been evaluated against the criteria and does not qualify for Critically
Endangered, Endangered, Vulnerable or Near Threatened. Widespread and abundant taxa are often included in
this category.
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. A taxon in this category may be well studied,
and its biology well known, but appropriate data on abundance and/or distribution are lacking. Data Deficient is
therefore not a category of threat. Listing of taxa in this category indicates that more information is required and
acknowledges the possibility that future research will show that threatened classification is appropriate. It is
important to make positive use of whatever data are available. In many cases great care should be exercised in
choosing between DD and a threatened status. If the range of a taxon is suspected to be relatively circumscribed,
or a considerable period of time has elapsed since the last record of the taxon, threatened status may well be
justified.
NOT EVALUATED (NE)
A taxon is Not Evaluated when it is has not yet been evaluated against the criteria.
Red List Guidelines
11
The remaining two categories do not reflect the threat status of taxa. The category Data
Deficient highlights taxa for which sufficient information is lacking to make a sound status
assessment. The inclination to assess taxa as Data Deficient may be very strong; it should be
emphasized that assessors must use all data available in full when making a Red List
assessment. Precise information on scarce taxa is usually lacking, and although the criteria
are highly quantitative and defined, one can use projections, assumptions and inferences (as
long as they are explicitly stated and clearly justified) to place a taxon in the appropriate
category. Since Data Deficient is not a category of threat, taxa placed in this category may
not be so obviously targets for conservation action, although their needs might be very great.
Assessors should use whatever information is available and relevant to make assessments and
place taxa into the Data Deficient category only when there is really no alternative. Guidance
on handling uncertainty is especially relevant in the case of poorly known taxa (see section
3.2). The category Not Evaluated applies to taxa that have not yet been evaluated against the
Red List Criteria.
The term “red-listed” is not defined in IUCN (2001), and is not used in this document owing
to ambiguity as to whether this includes Least Concern species or not, given that species
assessed as Least Concern are included on the IUCN Red List. To refer to species that have
assessments on the IUCN Red List, the phrase “assessed for the IUCN Red List” can be used.
To refer to species that are Extinct in the Wild, threatened and Near Threatened (i.e., EW, CR,
EN, VU, NT), the phrase “species of elevated conservation concern” may be used.
2.2.1 Transfer between categories
The following rules govern the movement of taxa between categories:
A. A taxon may be moved from a category of higher threat to a category of lower threat if and
when none of the criteria of the higher category has been met for five years or more (i.e., if
the taxon has qualified for a lower threat category for at least five years, regardless of when
the previous assessment was published). Thus, the 5-year period commences when the data
show that the taxon no longer meets the criteria for the category in which it is currently
listed; this is not necessarily the date of the previous assessment. If it is not possible to
identify the year in which the taxon qualified for the lower threat category, then the current
assessment year is used as the start of the 5-year period. However, if the taxon is being
moved from EW as a result of the establishment of a re-introduced population, this period
must be five years or until viable offspring are produced, whichever is the longer.
B. If the original classification is found to have been erroneous, the taxon may be transferred
to the appropriate category or removed from the threatened categories altogether, without
delay. However, in this case, the taxon should be re-evaluated against all the criteria to
clarify its status.
C. Transfer from categories of lower to higher risk should be made without delay.
D. The reason for a transfer between categories must be documented as one of the following:
Genuine change:
Red List Guidelines
12
Genuine (recent). The change in category is the result of a genuine status change that has
taken place since the previous assessment. For example, the change is due to an
increase in the rate of decline, a decrease in population or range size or habitat, or
declines in these for the first time (owing to increasing/new threats) and therefore
new thresholds are met relating to the IUCN Red List Criteria.
Genuine (since first assessment). This applies to taxa assessed at least three times, and is
used to assign genuine category changes to the appropriate time period to calculate
the Red List Index. The change in category is the result of a genuine status change
that took place prior to the last assessment, but since the first assessment and that has
only just been detected owing to new information or new documentation. If this new
information had been available earlier, the new category would have been assigned
during the previous assessment(s). When this code is used, the appropriate time
period (between previous assessments) in which the status change occurred needs to
be indicated. [See example below]
Nongenuine change:
Criteria revision. The change in category is the result of the revision of the IUCN Red List
Criteria (e.g., 1994 v. 2001 versions). These largely relate to criteria A2, A3, A4, D2
and the removal of the 'Conservation Dependent' category.
New information. The change in category is the result of better knowledge about the taxon,
e.g. owing to new or newly synthesized information about the status of the taxon (e.g.,
better estimates for population size, range size or rate of decline).
Taxonomy. The new category is different from the previous owing to a taxonomic change
adopted during the period since the previous assessment. Such changes include:
newly split (e.g., the taxon is newly elevated to species level), newly lumped (the
taxon is recognized following lumping of two previously recognized taxa), and no
longer valid/recognized (either the taxon is no longer valid e.g. because it is now
considered to be a hybrid or variant, form or subspecies of another species, or the
previously recognized taxon differs from a currently recognized one as a result of a
split or lump).
Misinterpretation of the criteria (‘Knowledge of criteria’ in SIS). The previous category
was applied in error because the assessor(s) misunderstood the IUCN Red List
Criteria.
Incorrect data. The previous category was applied in error because incorrect data were used
(e.g., the data referred to a different taxon).
Other. The change in category is the result of other reasons not easily covered by the above,
and/or requires further explanation. Examples include change in assessor’s attitude
to risk and uncertainty (as defined in section 3.2.3) and changes in this guidelines
document.
No change: When there is no change in category, one of the following must be specified.
Same category and criteria. In other words, no change in the listing.
Same category but change in criteria. For example, a change from EN A2 to EN D.
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Determining the appropriate reason for change often requires careful consideration. Many
category changes result from a combination of improved knowledge and some element of
genuine deterioration or improvement in status. In such cases, “genuine” should only be
assigned if the amount of genuine change (e.g., population size change, decline rate change,
range size change, etc.) is sufficient on its own to cross the relevant Red List Category
threshold. Genuine and non-genuine reasons for change should never be coded at the same
time.
e.g. Species A previously qualified as Endangered (D) with a population estimated to be 150 individuals; it
is reassessed as Vulnerable (D1) because its population is now estimated to number 400 individuals; the new
estimate is partly a result of the discovery of a new stable subpopulation numbering 50 individuals, and
partly because the previously known subpopulation increased from 150 to 350 individuals. The genuine
increase is sufficient to have taken the total population over the threshold for Vulnerable, so the category
change is coded as Genuine (recent), and Nongenuine (New information) should not be coded as the reason
for change in this case.
e.g. Species B previously qualified as Endangered (D) with a population estimated to be 150 individuals; it
is reassessed as Vulnerable (D1) because its population is now estimated to number 400 individuals; the new
estimate is partly a result of the discovery of a new stable subpopulation numbering 200 individuals, and
partly because the previously known subpopulation increased from 150 to 200 individuals. The genuine
increase in this case is insufficient to have taken the total population over the threshold for Vulnerable, (it
should have qualified as Vulnerable in the previous assessment also) so the reason for the category change
is coded as Nongenuine (New information), and not as Genuine (recent) in this case.
In cases where a category change results from a combination of taxonomic splitting and
genuine change, the change should be coded as Taxonomy if the currently recognised taxon
would have qualified for the higher or lower Red List category previously; otherwise it should
be coded Genuine (recent).
e.g. Species C previously qualified as VU D1 with a total population estimated to number 600 individuals.
It is then split into species D (540 individuals and stable) and species E (now only 40 individuals, having
declined from 60 individuals in the previous assessment). This category change for species E (previously
‘Not Recognized’ but now CR C1) should be coded as Genuine (recent) because it would have qualified as
Endangered D in the previous assessment. (Species D would be classified as VU D1)
All Genuine (recent) or Genuine (since first assessment) category changes should be supported
with appropriate notes to justify why the change is coded as genuine.
e.g. Mauritius Kestrel Falco punctatus was downlisted from CR in 1988 to EN in 1994; this was coded as
Genuine (recent) with the note: “Population increased from eight pairs in 1987-1988 to 56-68 pairs in 1994
as a result of a ban on hunting”.
e.g. Montserrat Oriole Icterus oberi was uplisted from NT in 1994 to CR in 2000; this was coded as Genuine
(recent) with the note: “In the early 1990s, this species occurred throughout the three main forested hill
ranges on the island, but volcanic eruptions in 1995-1997 destroyed two-thirds of remaining habitat. Recent
evidence suggests that the decline may now have halted, and the population is estimated at c.100-400 pairs”.
e.g. Ethiopian Bush-crow Zavattariornis stresemanni was uplisted from Vulnerable to Endangered in 2005.
This category change was coded as Genuine (since first assessment), with the genuine change assigned to
the 1994-2000 period, and the note “Encounter rates declined 80% between 1989 and 2003. Assuming
declines began in 1989, the cumulative decline would have exceeded 50% over 10 years for the first time
during the period 1994-2000”.
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2.3 Nature of the criteria
There are five quantitative criteria that are used to determine whether a taxon is threatened or
not, and if threatened, which category of threat it belongs in
(Critically Endangered,
Endangered or Vulnerable) (Table 2.1). These criteria are based around the biological
indicators of populations that are threatened with extinction, such as rapid population decline
or very small population size. Most of the criteria also include subcriteria that must be used
to justify more specifically the listing of a taxon under a particular category. For example, a
taxon listed as “Vulnerable C2a(ii)” has been placed in the Vulnerable category because its
population is fewer than 10,000 mature individuals (criterion C) and the population is
undergoing a continuing decline and all its mature individuals are in one subpopulation
(subcriterion a(ii) of criterion C2).
The five criteria are:
A. Population size reduction (past, present and/or projected)
B. Geographic range size, and fragmentation, few locations, decline or fluctuations
C. Small and declining population size and fragmentation, fluctuations, or few
subpopulations
D. Very small population or very restricted distribution
E. Quantitative analysis of extinction risk (e.g., Population Viability Analysis)
To list a particular taxon in any of the categories of threat, only one of the criteria, A, B, C, D,
or E needs to be met. However, a taxon should be assessed against as many criteria as available
data permit, and the listing should be annotated by as many criteria as are applicable for a
specific category of threat. For example, Critically Endangered: A2cd; B1ab(iv,v); C2a(i).
Only the criteria for the highest category of threat that the taxon qualifies for should be listed.
For example, if a taxon qualifies for criteria A, B, and C in the Vulnerable and Endangered
category and only criterion A in the Critically Endangered category, then only the criterion A
met in the Critically Endangered category should be listed (the highest category of threat).
Assessors are encouraged to document criteria under which a species meets lower threat
categories, because such information is critical to recovery planning.
Although the criteria for each of the categories of threat are based on quantitative thresholds,
the system remains relatively flexible to ensure that taxa for which there is very little
information can also be assessed. This has been achieved by incorporating inference,
suspicion and projection into the assessment process. Therefore, the person conducting an
assessment is expected to use the best available information in combination with inference,
suspicion and projection to test a taxon against the criteria. However, if inference, suspicion
and projection are used, the assumptions made must be documented. If there is any reasonable
concern that a taxon is threatened with extinction in the near future, it should qualify for the
criteria of one of the categories of threat.
Table 2.1. Summary of the five criteria (A-E) used to evaluate if a taxon belongs in a threatened category (Critically
Endangered, Endangered or Vulnerable).
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Listing under the highest category of threat (instead of, for instance, averaging extinction risk
across the five criteria) ensures a more precautionary approach to making urgent decisions based
on limited information. It also bases the overall risk assessment on the factors that are most critical
to species persistence. This approach is akin to emergency room doctors focusing their assessment
of patients on the most severe symptoms, instead of an average, where the positive symptoms
cancel out the negative ones (Collen et al. 2016). The five criteria (A-E) are derived from a wide
review aimed at detecting risk factors across the broad range of organisms and the diverse life
histories they exhibit. The criteria are aimed at detecting symptoms of endangerment rather than
causes. Consequently, the criteria are applicable to any threatening process that results in
symptoms such as past and future population decline, small population sizes, and small geographic
distributions. A taxon may be classified as threatened even if a threatening process cannot be
identified. Regardless of the nature of threats, assessments must follow IUCN (2001, 2012b) and
these guidelines to ensure valid application of the criteria. However, different threats, especially
new threats or poorly understood processes such as global climate change may require further
guidance in the application of definitions and criteria. Section 12 provides guidance specific to
different threats.
Some studies suggest that when taxa are evaluated under all five criteria, there is a tendency for
them to be listed under criteria A to D rather than under E. There are several possible reasons for
this. First, a reliable assessment under criterion E generally requires more data and analysis, and
in practice the process may often be incomplete. Second, even if each criterion on average
corresponds to an identical risk of extinction, the probability that a specific species meets at least
one of four criteria will be higher than the probability that it meets one criterion. Third, the
thresholds in criteria A to D may be more precautionary. This would be justified because they are
based on partial information and are often used in data-poor situations, whereas criterion E can
(and should) incorporate all factors that influence population dynamics. In data-poor situations,
where data permit only one or two of criteria A-D to be assessed, it would be very easy to ‘miss’
taxa that should be listed (Keith et al. 2000); in other words, the listing errors will be wider under
A-D, so their thresholds should be more precautionary. Even so, it should be noted that while
some studies suggest that criteria A-D are more precautionary than criterion E (e.g., Gärdenfors
2000), other studies indicate that criteria A-D may not be very precautionary, particularly when
data are limited (e.g., Keith et al. 2004).
2.3.1 The quantitative thresholds
The quantitative values presented in the criteria associated with threatened categories were
developed through wide consultation, and they are set at what are judged to be appropriate levels
(i.e., levels that generate informative threat categories spanning the range of extinction
probabilities; see below). Broad consistency between them was sought. The process and the
technical background to the IUCN Red List system, and the fundamental biological processes
underlying population decline and extinction that the criteria are based on, are described by Mace
et al. (2008).
The quantitative values establish the thresholds between the Red List Categories CR and EN, EN
and VU, and VU and NT. One misconception about the criteria has been that these thresholds are
arbitrary. There is subjectivity in the establishment of boundaries among the categories of risk,
and no theoretical reason why they should not be subjective (Collen et al. 2016). In fact, they have
to be subjective, because they divide extinction risk, a continuous metric, into categorical blocks.
Thus, their numerical values can only be based on practical, not theoretical, considerations.
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Two types of practical considerations are relevant. The first is the usefulness or conservation-
relevance of the resulting list of species in different threat categories. The continuum could have
been divided differently, resulting in very few species, or a large majority of species, in one of the
threat categories. In terms of informing conservation, this would not have been very useful. The
current proportions of species in the three threatened categories show that the current boundaries
are reasonable: both for fully assessed groups and for groups for which a random subset of species
has been assessed, the proportion of taxa in each category is neither negligible nor overwhelming,
meeting the Red List’s goal to provide an informative index of extinction risk (Collen et al. 2016).
The second type of practical consideration involves limitations due to data availability and quality.
For instance, the highest threshold for criterion A is set at 90% because if it were set any closer to
100% reduction, the taxon may go extinct before it can be classified as CR. The lowest threshold
is set at 30%; it was increased from 20% in the previous version of the criteria (ver. 2.3; IUCN
1994) better to differentiate fluctuations from reductions. The remaining thresholds are then
distributed more-or-less evenly between 30% and 90%. Similar considerations apply to the time
horizon of criterion A, which needs to be long enough to allow actual declines to be detected and
declines to be distinguished from fluctuations. The time horizon also needs to be short enough to
allow reliable estimation, and to represent substantial extinction risk at a given overall decline. In
terms of the spatial metrics, the thresholds balance the need for precision and the reality of the
coarseness of spatial data for most taxa. For instance, the thresholds of area of occupancy (AOO)
could have been set lower, but that would have required a more precise metric (a grid size smaller
than the 2 2 km grid recommended; see section 4.10), which is impractical for many taxa.
An important attribute of the numerical thresholds in the criteria is that there is a single set of
thresholds that applies to all taxa, allowing comparability across taxa. Of course, different taxa
have different characteristics, and this variability is accounted for by using bespoke definitions,
i.e., parameter definitions that incorporate life history characteristics of the taxon (such as the
definition of the number of mature individuals). These definitions take into account the life history
of the species; in addition, the criteria incorporate life history by scaling population responses to
threatening processes with generation length to accommodate variation in population turnover
(although, for practicality, the time horizon for future declines is limited to 100 years, regardless
of generation length). Failure to consider correctly the definitions causes the majority of mistakes
and misconceptions regarding the use of these standardized metrics. As a result, much of these
guidelines (e.g., all of section 4) is devoted to definitions of terms and parameters used in the
criteria.
Another important attribute of the numerical thresholds in the criteria is that they are exclusively
tied to the definitions of the corresponding variables. In other words, comparing a measured value
against a threshold requires that the value is measured as defined in IUCN (2001, 2012b) and in
these guidelines. A common type of mistake is applying these thresholds to values of variables
that are not calculated according to the definitions given here. For example, applying criterion A
thresholds of reduction to declines over periods other than three generations/10 years (e.g., Shoo
et al. 2005) would result in risk estimates that are not consistent with the Red List Categories (for
other examples, see Akçakaya et al. 2006). Even when there are good reasons for measuring
reduction over a different period (see section 4.5.1), the measured value must be scaled to the
correct period before it can be compared to the criterion A thresholds. Similarly, applying the
AOO thresholds to areas measured at high resolution (e.g., Cardoso et al. 2011), or applying the
extent of occurrence (EOO) thresholds to areas calculated according to the definition of AOO
(e.g., Ocampo-Peñuela et al. 2016) would result in threat categories that are not comparable to the
Red List Categories, and hence invalid application of the criteria. Consequently, the areas
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computed must be measured according to the definitions of AOO and EOO (or they must be scaled
up or down as appropriate) before they can be compared to the thresholds of these variables. For
further information, see sections 4.10.3 and 4.10.7.
2.4 Conservation priorities and actions
The category of threat is not necessarily sufficient to determine priorities for conservation action.
The category of threat simply provides an assessment of the extinction risk under current
circumstances, whereas a system for assessing priorities for action will include numerous other
factors concerning conservation action such as costs, logistics, chances of success, and other
biological characteristics (Mace and Lande 1991). The Red List should therefore not be interpreted
as a means of priority setting (IUCN 2001, 2012b). The difference between measuring threats and
assessing conservation priorities needs to be appreciated. However, assessment of taxa using Red
List Criteria represents a critical first step in setting priorities for conservation action.
Many taxa assessed under the IUCN Red List Criteria will already be subject to some level of
conservation action. The criteria for the threatened categories are to be applied to a taxon whatever
the level of conservation action affecting it, and any conservation measures must be included with
the assessment documentation. It is important to emphasize here that a taxon may require
conservation action even if it is not listed as threatened, and that effectively conserved threatened
taxa may, as their status improves over time, cease to qualify for listing.
2.5 Documentation
All assessments should be documented. Threatened classifications should state the criteria and
subcriteria that are met. For example, for a taxon listed as Endangered A2cd, the criterion A2
indicates that the taxon has declined by 50% or more in the last 10 years or three generations
(whichever is longer) and the subcriteria indicate that the decline in mature individuals has been
caused by a decline in EOO, AOO, and/or the quality of habitat, as well as exploitation. Clearly
listing the subcriteria provides the reasoning for placing a taxon in a specific category, and if
necessary, the reasoning can be re-examined. No assessment at a threatened category or NT can
be accepted for the IUCN Red List as valid unless at least one criterion and any qualifying
subcriteria are given. If more than one criterion or subcriterion is met for the highest threat
category, then each should be listed. Criteria meeting lower categories of threat should also be
documented in the assessment Rationale. If a re-evaluation indicates that the documented criterion
is no longer met, this should not result in automatic reassignment to a lower category of threat
(downlisting). Instead, the taxon should be re-evaluated against all the criteria to clarify its status.
The factors responsible for qualifying the taxon against the criteria, especially where inference,
suspicion and projection are used, should be documented. All data used in a listing must be either
referenced to a publication that is available in the public domain, or else be made available. Full
documentation requirements are given in Annex 3 of the IUCN Red List Categories and Criteria
(Version 3.1) (IUCN 2012b) and in Documentation Standards and Consistency Checks for IUCN
Red List Assessments and Species Accounts, which is available for download at
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3. Data Quality
3.1 Data availability, inference, suspicion, and projection
The IUCN Red List Criteria are intended to be applied to taxa at a global scale. However, it is
very rare for detailed and relevant data to be available across the entire range of a taxon. For this
reason, the Red List Criteria are designed to incorporate the use of inference, suspicion, and
projection, to allow taxa to be assessed in the absence of complete data. Although the criteria are
quantitative in nature, the absence of high-quality data should not deter attempts at applying the
criteria. In addition to the quality and completeness of the data (or lack of), there may be
uncertainty in the dataset itself, which needs to be considered in a Red List assessment. Data
uncertainty is discussed separately in section 3.2.
The IUCN criteria use the terms Observed, Estimated, Projected, Inferred, and Suspected to refer
to the nature of the evidence (including aspects of data quality) for specific criteria. The relative
order of data quality is Observed > Estimated (past) = Projected (future) > Inferred > Suspected.
Some criteria have specific minimum data quality requirements (Table 3.1). For example, criterion
A allows inferred or suspected reduction, whereas criterion C1 allows only estimated declines and
criterion C2 specifies observed, projected, or inferred declines.
Table 3.1. Minimum data quality requirements for criteria A-E. If the data qualifier for the listed parameter
is of lower quality than that specified ("Min. Quality") then the specified criterion is considered not to have
been met, even if the numerical value meets the threshold for that criterion.
Criterion Parameter
Min. Quality
A
Population reduction
suspected
B
Area of occupancy (AOO)
estimated
B
Extent of occurrence (EOO)
estimated
B1b, B2b Continuing decline in EOO; AOO; area, extent and/or quality of
inferred
habitat; number of locations or subpopulations; number of mature
individuals
C, D
Number of mature individuals
estimated
C1
Estimated continuing decline
estimated
C2
Continuing decline in number of mature individuals
inferred
C2a(i)
Size of largest subpopulation
estimated
E
Extinction probability
estimated
Observed, Estimated, and Projected are similar in terms of their use in the criteria, and therefore
in terms of their effects on a taxon's Red List category; the differences among them are important
for documentation purposes only. The consequential differences are between this group
(Observed/Estimated/Projected) and Inferred, and between Inferred and Suspected because these
latter categories of evidence are not permissible for assessing some criteria (Table 3.1).
These terms are defined as follows:
Observed: information that is directly based on well-documented observations. Examples of
observed information:
Population size based on a census of all known mature individuals of the taxon.
Population reduction derived from a census of all known mature individuals that took place
three generations ago, and a current census of all known mature individuals.
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Continuing decline in the area, extent or quality of habitat derived from a survey of all
known habitat, or from aerial photography of all known habitat.
Continuing decline in the number of mature individuals derived from multiple censuses of
all known mature individuals.
Estimated: information that is based on calculations that may include statistical assumptions about
sampling, or biological assumptions about the relationship between an observed variable
(e.g., an index of abundance) and the variable of interest (e.g., number of mature individuals).
For example, transect counts of singing males of a bird species may be used with assumptions
about the overall proportions of mature males these represent and about sex ratios to estimate
the number of mature individuals. The assumptions used should be stated and justified in the
documentation. Estimation may also involve interpolation in time to calculate the variable of
interest for a particular time step
(e.g., a
10-year reduction based on observations or
estimations of population size 5 and 15 years ago). For examples, see discussion under
criterion A.
Additional examples of estimated information:
Number of mature individuals calculated from a sample (cf. complete census) of (i) counts
or density estimates carried out at sample areas across the taxon's range; (ii) an estimate
of the proportion of mature individuals in the population derived from demographic
information for the taxon; and (iii) the total area occupied by the taxon, derived from
surveys sampling across its range.
Population reduction or a continuing decline in the number of mature individuals derived
from the estimated numbers of mature individuals at two or more time points, with or
without extrapolation (see section 4.5.1).
Population reduction or a continuing decline in the number of mature individuals derived
from Catch Per Unit Effort data or trade estimates, with a known relationship to the
species’ population size (e.g., that CPUE and population size are linearly related).
Continuing decline in the area or extent of habitat derived from remote-sensed land cover
data or field surveys.
EOO or AOO calculations that include 'inferred sites of occurrence', i.e., sites that are
inferred from presence of known appropriate habitat, information about habitat
requirements and dispersal capability of the taxon, rates and the effects of habitat
destruction and other relevant factors (see section 4.10.7). Because the definition of EOO
and AOO allow for 'inferred sites of occurrence', EOO and AOO based on such sites are
considered to meet the criterion B data quality requirement for Estimated. However,
inferred sites of occurrence should only be used to calculate the upper bound of the size of
area, such that incorporating inferred sites results in a range of plausible values of EOO
and AOO, which may lead to a range of plausible Red List Categories (see section 4.9).
Projected: same as “estimated”, but the variable of interest is extrapolated in time towards the
future, or in space. Projected variables require a discussion of the method of extrapolation
(e.g., justification of the statistical assumptions or the population model used) as well as the
extrapolation of current or potential threats into the future, including their rates of change.
Examples of projected information:
Population reduction derived from census data extrapolated into the future, either from the
present (criterion A3), or from past and present (criterion A4), using statistical methods or
population models (see sections 4.5.1 and 4.5.2).
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EOO or AOO calculations that are based on occurrences that include spatially projected
sites of occurrence, i.e., sites that are based on a habitat model (see section 4.10.7).
Continuing decline in the area or extent of habitat predicted by a statistical model of land-
cover change that is based on an analysis of past land-cover changes derived from remote-
sensed land cover data.
Inferred: information that is in the same general type of units but not a direct measure of the
variable of interest (refer to definition of ‘Suspected’ below for examples that are not
measured in the same general type of units). Examples include population reduction (A2d)
inferred from a change in catch statistics, continuing decline in number of mature individuals
(C2) inferred from trade estimates, or continuing decline in area of occupancy (B1b(ii,iii),
B2b(ii,iii)) inferred from rate of habitat loss. The main difference between Estimated (or
Projected) and Inferred is that Inferred values rely on more assumptions than estimated
values. For example, inferring reduction from catch statistics not only requires statistical
assumptions (e.g., random sampling) and biological assumptions (about the relationship of
the harvested section of the population to the total population), but also assumptions about
trends in effort, efficiency, and spatial and temporal distribution of the harvest in relation to
the population. When information replaces these additional assumptions, allowing calculation
of the reduction based on data on trends in effort, efficiency, and distributions, the reduction
can be considered Estimated. Inference may also involve extrapolating an observed or
estimated quantity from known subpopulations to calculate the same quantity for other
subpopulations. Whether there are enough data to make such an inference will depend on
how large the known subpopulations are as a proportion of the whole population, and the
applicability of the threats and trends observed in the known subpopulations to the rest of the
taxon. The method of extrapolating to unknown subpopulations depends on the criteria and
on the type of data available for the known subpopulations. Further guidelines are given
under specific criteria (e.g., see section 4.5 for extrapolating population reduction for criterion
A assessments).
Additional examples of inferred information:
Number of mature individuals calculated by combining all of the following information:
(i) density estimates based on counts of individuals carried out at sample areas (not in all
subpopulations), or from a closely-related species with similar ecology and under similar
threats, where they can be plausibly assumed to have similar densities; (ii) an estimate of
the proportion of mature individuals in the population derived from demographic
information for a closely-related taxon, which can be plausibly assumed to have similar
population structure; and (iii) the total area occupied by the taxon, derived from remote-
sensed data.
Population reduction or a continuing decline in the number of mature individuals derived
from numbers of mature individuals at multiple time points inferred from the types of
information listed in the above point, with or without extrapolation (see section 4.5.1).
Population reduction or a continuing decline in the number of mature individuals derived
from trends in catch or trade statistics, with plausible assumptions about change (or lack
of change) in effort and efficiency.
Continuing decline in AOO or EOO based on land-cover changes derived from remote-
sensed data, or based on evidence of decline in habitat quality.
Continuing decline in area, extent and/or quality of habitat based on land-cover changes
derived from remote-sensed data, or qualitative accounts of habitat loss or degradation.
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Continuing decline in the number of mature individuals (for criteria B and C2, but not C1)
based on continuing decline in habitat of a species that is known to be a habitat specialist.
Suspected: information that is based on variables in different types of units, for example, %
population reduction based on decline in habitat quality (A2c) or on incidence of a disease
(A2e), or on circumstantial evidence. For example, qualitative information on habitat loss
can be used to infer that there is a qualitative (continuing) decline in area of occupancy,
whereas evidence of the amount of habitat loss can be used to suspect a population reduction
at a particular rate. In general, a suspected population reduction can be based on any factor
related to population abundance or distribution, including the effects of (or dependence on)
other taxa, so long as the relevance of these factors can be reasonably supported.
Additional examples of information that could be used to suspect a reduction:
Population reduction in the number of mature individuals based on information on trends
in harvest, habitat quality, and sightings (e.g., from a structured elicitation of information
from multiple experts familiar with the taxon).
Population reduction in the number of mature individuals based on land-cover changes
derived from remote-sensed data.
Population reduction in the number of mature individuals based on a report of large
numbers of individuals being hunted, poached or traded, where it is suspected that the level
of exploitation will impact the population size, but there is no quantitative evidence to
support this.
3.2 Uncertainty
The data used to evaluate taxa against the criteria are often obtained with considerable uncertainty.
Uncertainty in the data should not be confused with a lack of data for certain parts of a species’
range or a lack of data for certain parameters. This problem is dealt with in section 3.1 (Data
availability, inference, suspicion and projection). Data uncertainty can arise from any one or all
of the following three factors: natural variability, vagueness in the terms and definitions used in
the criteria (semantic uncertainty), and measurement error (Akçakaya et al. 2000). The way in
which uncertainty is handled can have a major influence on the results of an evaluation. Details
of methods recommended for handling uncertainty are given below.
3.2.1 Types of uncertainty
Natural variability results from the fact that species’ life histories and the environments in which
they live change over time and space. The effect of this variation on the criteria is limited, because
each parameter refers to a specific time or spatial scale. However, natural variability can be
problematic, e.g. there is spatial variation in age-at-maturity for marine turtles, and a single
estimate for these taxa needs to be calculated to best represent the naturally occurring range of
values. Semantic uncertainty arises from vagueness in the definition of terms in the criteria or
lack of consistency in different assessors’ usage of them. Despite attempts to make the definitions
of the terms used in the criteria exact, in some cases this is not possible without the loss of
generality. These guidelines aim to reduce semantic uncertainty by explaining the terms in detail
and for different contexts; and we encourage assessors to highlight remaining areas of semantic
uncertainty. Measurement error is often the largest source of uncertainty; it arises from the lack
of precise information about the quantities used in the criteria. This may be due to inaccuracies
in estimating values or a lack of knowledge. Measurement error may be reduced or eliminated by
acquiring additional data (Burgman et al. 1999, Akçakaya et al. 2000). Another source of
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measurement error is ‘estimation error’, i.e. sampling the wrong data or the consequences of
estimating a quantity (e.g., natural mortality) based on a weak estimation method. This source of
measurement error is not necessarily reduced by acquiring additional data.
3.2.2 Representing uncertainty
Uncertainty may be represented by specifying a best estimate and a range of plausible values for
a particular quantity. The best estimate can itself be a range, but in any case the best estimate
should always be included in the range of plausible values. The plausible range may be established
using various methods, for example based on confidence or probability intervals, the opinion of a
single expert, or the consensus view of a group of experts. The method used should be stated and
justified in the assessment documentation.
3.2.3 Dispute tolerance and risk tolerance
When interpreting and using uncertain data, attitudes toward risk and uncertainty are important.
First, assessors need to consider whether they will include the full range of plausible values in
assessments, or whether they will exclude extreme values from consideration (known as dispute
tolerance). Perceived uncertainty in the data is reduced when an assessor has a high dispute
tolerance, and thus excludes extreme values from the assessment. On the one hand, it may
sometimes be desirable to exclude the extreme values if these are unrealistic (e.g., the result of
opinions that reflect biases rather than underlying data uncertainty). On the other hand, it is
important that assessments accurately represent the range of uncertainty. We recommend that
dispute tolerance (representing attitude towards uncertainty) is set to a low value, in most cases as
low as 0.0 (including the whole range of possible outcomes).
Second, assessors need to consider whether they have a precautionary or evidentiary attitude to
risk (known as risk tolerance). A precautionary attitude (i.e., low risk tolerance) will classify a
taxon as threatened unless it is highly likely that it is not threatened, whereas an evidentiary
attitude will classify a taxon as threatened only when there is strong evidence to support a
threatened classification. A method developed for incorporating attitudes towards risk and
uncertainty (Akçakaya et al. 2000) has been implemented in SIS as well as in RAMAS Red List
(Akçakaya and Root 2007). Because these systems are used by a variety of institutions (e.g., for
national assessments), it is not appropriate to set the values for attitude settings to specific
constants. This is because the attitude settings are subjective, and reflect the assessors' values.
However, for global listings in the IUCN Red List, it is appropriate to use a single risk tolerance
value for all assessments, so that assessments are consistent across taxa. In particular, for the
IUCN Red List, the risk tolerance value should not depend on factors such as ecological,
evolutionary, economic, societal importance of the species; its chances of recovery; cost of
measures to save it, etc. (such factors can be used in prioritization of conservation actions, but not
for red-listing). This institutional setting for the IUCN Red List should reflect the reasons for this
use (determination of global threat status), the overall objective of maintaining consistency of the
IUCN Red List, and IUCN's values. IUCN (2001) specifies that "… when uncertainty leads to
wide variation in the results of assessments, the range of possible outcomes should be specified.
A single category must be chosen and the basis for the decision should be documented; it should
be both precautionary and credible" and assessors "should resist an evidentiary attitude and adopt
a precautionary but realistic attitude to uncertainty when applying the criteria". A precautionary
but realistic attitude would require a slightly lower than mid-value for the risk tolerance parameter,
perhaps a value in the range from 0.40 to 0.49.
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3.2.4 Dealing with uncertainty
It is recommended that assessors should adopt a precautionary but realistic attitude, and to resist
an evidentiary attitude to uncertainty when applying the criteria (i.e., have low risk tolerance).
This may be achieved by using plausible lower and upper bounds, rather than only the best
estimates, in determining the quantities used in the criteria. In cases where a statistical method is
used to estimate a quantity, a 90% confidence interval or 90% credible interval may be used to set
the plausible range of values. It is recommended that ‘worst case scenario’ reasoning be avoided
because this may lead to unrealistically precautionary listings. All attitudes should be explicitly
documented. In situations where the spread of plausible values (after excluding extreme or
unlikely values) qualifies a taxon for two or more categories of threat, the precautionary approach
would recommend that the taxon be listed under the higher (more threatened) category.
In some rare cases, uncertainties may result in two non-consecutive plausible threat categories.
This may happen, for example, when extent of occurrence (EOO) or area of occupancy (AOO) is
smaller than the EN threshold and one subcriterion is definitively met, but it is uncertain whether
a second subcriterion is also met. Depending on this, the category can be either EN or NT. In
such cases, the category could be specified as the range EN-NT in the documentation (giving the
reasons why), and the assessors must choose the most plausible of the categories, of which VU
could be one. This choice depends on the level of precaution (see section 3.2.3) and should be
justified.
Specific guidelines for dealing with uncertainty in assessing taxa with widely distributed or
multiple subpopulations against criterion A are given in section 4.5. This section offers clear
guidance on using uncertain estimates, accounting for uncertainty about the pattern of population
decline and using data with different abundance units.
3.2.5 Documenting uncertainty and interpreting listings
The level of uncertainty associated with a particular taxon’s assessment is not apparent from the
listing itself, potentially complicating and de-valuing interpretation of listings. When a plausible
range for each quantity is used to evaluate the criteria, a range of categories may be obtained,
reflecting the uncertainties in the data. However, only a single category, based on a specific
attitude to uncertainty, will be listed along with the relevant criteria on the IUCN Red List. It is
important to note that the range of possible categories should also be indicated, along with the
assessors’ attitudes to uncertainty, in the documentation accompanying the assessment. The
inclusion of information on uncertainty in the documentation, allows users of the Red List access
to important information that will assist in the interpretation of listings, and inform debates over
particular issues or listings.
3.2.6 Uncertainty and the application of the categories Data Deficient and Near Threatened
The level of uncertainty in the data used for assessments may or may not affect the application of
the categories Data Deficient and Near Threatened. Guidance on the application of these
categories is given in section 10.
4. Definitions of Terms Used in the Criteria and their Calculation
The terms used in the IUCN Red List Categories and Criteria must be clearly understood to ensure
that taxa are correctly assessed. The following terms are defined in the IUCN Red List Categories
Red List Guidelines
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and Criteria (version 3.1) on pages 10-13 (IUCN 2001, 2012b). These definitions are reproduced
here, with additional guidelines to assist in their interpretation and calculation.
4.1 Population and population size (criteria A, C and D)
“The term ‘population’ is used in a specific sense in the Red List Criteria that is different to its
common biological usage. Population is here defined as the total number of individuals of the
taxon. For functional reasons, primarily owing to differences between life forms, population size
is measured as numbers of mature individuals only. In the case of taxa obligately dependent on
other taxa for all or part of their life cycles, biologically appropriate values for the host taxon
should be used.” (IUCN 2001, 2012b)
The definition above means that a "population" (sensu IUCN 2001, 2012b) includes all individuals
(mature and other life stages) that are assigned to the taxon throughout its distribution.
“Population” and “Population size” are, however, not synonymous. There are two important
aspects of the definition of population size. First, population size is measured only in terms of
mature individuals. Thus, the interpretation of this definition depends critically on an
understanding of the definition of ‘mature individuals’, which is given and discussed below in
section 4.3. Second, population size is defined as the total number of mature individuals in all
areas. Even if some of the taxon exists in subpopulations that might be seen as distinct populations
in a general biological sense, for the purposes of the criteria, the total number of mature individuals
in all areas (or all subpopulations) is used to measure the "population size" of the taxon.
4.2 Subpopulations (criteria B and C)
“Subpopulations are defined as geographically or otherwise distinct groups in the population
between which there is little demographic or genetic exchange (typically one successful migrant
individual or gamete per year or less).” (IUCN 2001, 2012b)
The significance of subpopulations in the criteria relates to the additional risks faced by taxa where
the population is either subdivided into many small spatial units or where most individuals are
concentrated into one such unit. Operational methods for determining the number of
subpopulations may vary according to the taxon; in the case of tree species, for example, a
subpopulation can be defined as a spatially distinct segment of the population that experiences
insignificant or reproductively unsuccessful migration
(of seed or pollen) from other
subpopulations.
Although subpopulations typically have little demographic or genetic exchange, this may or may
not amount to their complete isolation in this regard. In other words, subpopulations need not be
completely isolated. Even highly mobile species may have multiple subpopulations, as high
mobility is not always a guarantee of genetic or demographic connectivity. For example, even if
a species migrates thousands of kilometres annually, if it has very high fidelity to both natal and
breeding sites, there could be few dispersers among subpopulations within the breeding range,
making it necessary to recognize multiple subpopulations.
4.3 Mature individuals (criteria A, B, C and D)
“The number of mature individuals is the number of individuals known, estimated or inferred to
be capable of reproduction. When estimating this quantity the following points should be borne
in mind:
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Mature individuals that will never produce new recruits should not be counted (e.g., densities
are too low for fertilization).
In the case of populations with biased adult or breeding sex ratios, it is appropriate to use lower
estimates for the number of mature individuals, which take this into account.
Where the population size fluctuates, use a lower estimate. In most cases this will be much
less than the mean.
Reproducing units within a clone should be counted as individuals, except where such units are
unable to survive alone (e.g., corals).
In the case of taxa that naturally lose all or a subset of mature breeding individuals at some
point in their life cycle, the estimate should be made at the appropriate time, when mature
individuals are available for breeding.
Re-introduced individuals must have produced viable offspring before they are counted as
mature individuals.” (IUCN 2001, 2012b)
4.3.1 Notes on defining mature individuals
This definition of mature individuals differs slightly from that given in version 2.3 of the Red List
Categories and Criteria (IUCN 1994). Some groups have found the more recent definition of
mature individuals to be less conservative and less precise, leading to a potential down-listing of
some taxa (e.g., obligate co-operative breeders), even though their extinction risk has not changed.
It must be stressed that the intention of the definition of mature individuals is to allow the estimate
of the number of mature individuals to take account of all the factors that may make a taxon more
vulnerable than might otherwise be expected. The list of points given with the definition is not
exhaustive and should not restrict an assessor’s interpretation of mature individuals, provided they
are estimating the number of individuals known, estimated or inferred to be capable of
reproduction. "Reproduction" means production of offspring (not just mating or displaying other
reproductive behaviour). The ability of an assessor to estimate or infer which individuals are
capable of reproduction is paramount and highly contingent on the particular features of the taxon
or group. Juveniles, senescent individuals, suppressed individuals and individuals in
subpopulations whose densities are too low for fertilization to occur will never produce new
recruits, and therefore should not be counted as mature individuals. On the other hand, in many
taxa there is a pool of non-reproductive (e.g., suppressed) individuals that will quickly become
reproductive if a mature individual dies. These individuals can be considered to be capable of
reproduction. For example, in social bees and ants there is often just one or a few actually
reproducing females ("queens") at a time, but new such queens can be promoted from larvae under
development or from reproductively suppressed workers, if a functional queen were to die. A
possible template for the number of ‘mature individuals’ in such societies could be the number of
queens * 10 (an expression for the number of potential queens that could realistically be produced)
* 2 (the male counterpart). In general, the judgement will be best made by assessors with insight
into the species’ biology.
These considerations also apply to cases of populations with biased adult or breeding sex ratios.
In such cases, it is appropriate to use lower estimates for the number of mature individuals, which
take this into account. An appropriate lower estimate will depend on whether individuals of the
limiting sex are biologically capable of reproduction. For example, if there are 100 males and 500
females capable of reproduction, then the number of mature individuals would be < 600, perhaps
as small as 200 (=100*2, if mating is strictly monogamous). However, if these are the number of
actual breeders in some years and there are 400 other males capable of reproduction (but that did
not breed in the year the data were collected), then there would be 1,000 mature individuals.
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Note that effective population size (Ne) cannot be used as an estimate of the number of mature
individuals. One reason is that reproductively suppressed individuals do not contribute to the
calculation of Ne, but, as explained above, they may be counted as mature individuals.
In the case of taxa obligately dependent on other taxa for all or part of their life cycles, biologically
appropriate values of mature individuals for the host taxon might be used. This number may be
much less than the total number of mature individuals of the host taxon, because generally other
factors restrict the dependant taxon from utilizing all host individuals.
The number of mature individuals can be estimated using the equation d * A * p, where d is an
estimate of population density, A is an estimate of area, and p is an estimate of the proportion of
individuals that are mature. However, this approach often leads to gross overestimates of number
of mature individuals if the parameters are not set appropriately. Therefore, great care should be
taken when using this formula to ensure that: (a) the area is appropriately selected and d is an
estimate of the average over the entire A (for example, the estimate will be positively biased if A
is set to EOO and d is based on samples from areas of highest density), and (b) p should be selected
based on knowledge of the taxon (or related taxa) rather than being set to a default value (such as
0.5) because the proportion of mature individuals in a population differs markedly among taxa.
Bounds on the estimate of number of mature individuals can be obtained by placing bounds on
each of d, A, and p. The value from this approach will be an estimate if the values for d, A and p
are all estimates, but should be considered to be an inference if one or more of these values are
based on inference (e.g., if the value for p is based on data for individuals from a subset of the
area the taxon is found in rather than a random set of individuals across the area). Estimates of d
(population density) should incorporate the imperfect detection of individuals, ideally using an
estimate of the probability of detection.
4.3.2 Clonal colonial organisms
Clonal colonial organisms include most corals, algae, bryophytes, fungi and some vascular plants.
As opposed to a unitary organism, such as a vertebrate, an insect and many vascular plants, the
growth and development of a clonal (modular) colonial organism is an iterative process in which
“modules” are added step by step to the existing structure. In principle, the growth of a modular
organism never ends and it has no final shape, size or age. A modular organism (the genet) can
sometimes exist in a form of many parts (ramets), which can become more or less isolated from
each other. Consequently, what constitutes a ‘mature individual’ in a colonial or modular
organism is not always clear. Still, it is important to define ‘mature individual’ for such organisms,
since ‘mature individual’ is used under criteria C and D to capture the effects of threats and
demographic stochasticity to a small population. In defining ‘mature individual’ for colonial
organisms, it is important to identify entities that are comparable in demographic stochasticity and
extinction proneness to a population of discrete individuals of animals. For some taxa (e.g., reef-
forming corals), it may also help to consider what entity typically lives, is injured, and dies as a
unit.
As a general rule, the ramet, i.e., the smallest entity capable of both independent survival and
(sexual or asexual) reproduction should be considered a ‘mature individual’. Reproducing units
within a clone should be counted as individuals, except where such units are unable to survive
alone
(IUCN 2012b). For instance, in those cases where the organism appears in well-
distinguishable units, each such unit would be counted as one mature individual. Examples may
be a bryophyte tuft (e.g., of Ulota) or a discrete cushion (e.g., Brachythecium), a lichen thallus
(e.g., Pseudocyphellaria) or foliose patch (e.g., Parmelia), or a coral discrete entity (e.g., a brain
coral Diploria or sun coral Tubastrea).
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If the delimitation of ramets is not obvious, but the species lives in or on a discrete and relatively
small substrate unit limited by a certain resource, e.g. a piece of cow dung, a leaf or a dead tree
branch, each unit colonized by the species should be counted as a single mature individual. In
many other cases, like reef-forming corals, cliff-growing lichens and ground-growing fungi, the
organism grows in large, more or less continuous entities that could be divided into smaller pieces
without obviously harming the organism. In principle, the smallest such entity (ramet) that an
organism could be divided into without causing its death or preventing reproduction, should be
counted as one mature individual. Obviously, what such an entity would be is often not known.
Therefore, in such cases, it may be necessary to adopt a pragmatic approach to defining ‘mature
individuals’. Examples of possible interpretations of the definition of a mature individual are:
For diffuse, wholly visible organisms in continuous habitats (e.g., reef-forming corals, algal
mats) assessors may assume an average area occupied by a mature individual and estimate
the number of mature individuals from the area covered by the taxon. The area covered by
the taxon should be estimated at a scale (grid size; e.g. 1 m2) that is as close as practicable to
the area assumed to be occupied by a single mature individual. (However, note that AOO
must still be estimated using the 22 km grids.)
For diffuse organisms, not wholly visible, in continuous habitats (e.g., subterranean mycelial
fungi) assessors may assume that each recorded presence separated by a minimum distance
represents an assumed number of individuals. For example, each visible fungal fruiting body
may be assumed to represent ten mature individuals, so long as they are separated by at least
10 metres. This kind of assumption is necessary because the size or area of a fungal mycelium
is rarely known.
For diffuse organisms that occur in discrete habitat patches (e.g., fungi living more or less
concealed in dead wood), each patch (trunk or log colonized by the species) could - if no
better information exists - be counted as 1-10 mature individuals, depending on the size of
the tree.
In any case, it is recommended that authors of Red List assessments specify the way they have
used ‘mature individual’.
4.3.3 Fishes
In many taxa of marine fish, reproductive potential is commonly closely related to body size.
Since exploitation usually reduces the mean age and size of individuals, assessing declines in
numbers of mature individuals may under-estimate the severity of the decline. When evaluating
population decline, this factor should be kept in mind. One possible method is to estimate decline
in the biomass of mature individuals rather than the number of such individuals when applying
criterion A, where biomass is ‘an index of abundance appropriate to the taxon’.
4.3.4 Sex-changing organisms
Many marine taxa have the capacity to change sex as they grow. In such taxa, the sex ratio may
be highly biased towards the smaller sex. The criteria acknowledge that the number of mature
individuals can take biased sex ratios into account, by using a lower estimate for the number of
mature individuals. For sex-changing organisms it is also appropriate to consider changes in sex
ratio as an indicator of population perturbation, which may be of additional conservation concern
because the larger sex (already less numerous) is often subject to higher harvest mortality. In
these cases, the number of mature individuals may be estimated by doubling the average number
of individuals of the larger (or less numerous) sex.
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4.3.5 Trees
Individual trees that flower without producing viable seeds do not qualify as mature individuals.
For example, Baillonella toxisperma first flowers at 50-70 years and does not fruit until roughly
20 years later. Conversely, Sequoiadendron giganteum may produce seed at less than 20 years of
age and continue to do so for 3,000 years. However, not all trees between these ages may be
mature individuals if the population includes some reproductively suppressed individuals. If little
is known about age at fruiting, mature individuals should be counted as those of a typical
reproductive size; e.g. estimates for canopy taxa should exclude sub-canopy individuals.
Vegetative clones, apomictic taxa and self-fertilizing taxa may qualify as mature individuals, so
long as they produce viable offspring and their survival is independent of other clones.
Where it is impossible to calculate the number of mature individuals, but information is available
on the total population size, it may be possible to infer the number of mature individuals from the
total population size.
4.4 Generation (criteria A, C1 and E)
“Generation length is the average age of parents of the current cohort (i.e., newborn individuals
in the population). Generation length therefore reflects the turnover rate of breeding individuals
in a population. Generation length is greater than the age at first breeding and less than the age of
the oldest breeding individual, except in taxa that breed only once. Where generation length varies
under threat, such as the exploitation of fishes, the more natural, i.e. pre-disturbance, generation
length should be used.” (IUCN 2001, 2012b)
In general, time-based measures in the criteria are scaled for the different rates at which taxa
survive and reproduce, and generation length is used to provide this scaling. The current definition
of generation length has been widely misunderstood, and there are difficulties when dealing with
very long-lived taxa, with taxa having age-related variation in fecundity and mortality, with
variation in generation length under harvesting, with environmental changes and variation
between the sexes. Some of the different acceptable methods for estimating generation length are
included here.
It is also appropriate to extrapolate information such as a generation length from closely related
well-known taxa and to apply it to lesser-known and potentially threatened taxa (e.g., Bird et al.
2020).
Formally, there are several definitions of generation length, including the one given above; 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; and time required
for the population to increase by the replacement rate. All of these definitions of generation length
require age- and sex-specific information on survival and fecundity, and are best calculated from
a life table (e.g., option 1 below). Depending on the taxon concerned, other methods may provide
a good approximation (e.g., options 2 and 3). Care should be taken to avoid estimates that may
bias the generation length estimate in a non-precautionary way, usually by under-estimating it.
Generation length may be estimated in a number of ways:
1. The average age of parents in the population, based on the equation
G
xl
m
l
m
x x
x
x
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