Generation length for mammals

Abstract

Generation length (GL) is defined as the average age of parents of the current cohort, reflecting the turnover rate of breeding individuals in a population. GL is a fundamental piece of information for population ecology as well as for measuring species threat status (e.g. in the IUCN Red List). Here we present a dataset including GL records for all extant mammal species (n=5427). We first reviewed all data on GL published in the IUCN Red List database. We then calculated a value for species with available reproductive parameters (reproductive life span and age at first reproduction). We assigned to missing-data species a mean GL value from congeneric or confamilial species (depending on data availability). Finally, for a few remaining species, we assigned mean GL values from species with similar body mass and belonging to the same order. Our work provides the first attempt to complete a database of GL for mammals; it will be an essential reference point for all conservation-related studies that need pragmatic information on species GL, such as population dynamics and applications of the IUCN Red List assessment.

Full text

Generation length for mammals 87
Generation length for mammals
Michela Pacici1, Luca Santini1, Moreno Di Marco1, Daniele Baisero1,
LucillaFrancucci1, Gabriele Grottolo Marasini1, Piero Visconti1, Carlo Rondinini1
1Global Mammal Assessment program, Department of Biology and Biotechnologies, Sapienza Università di
Roma, Viale dell’Università 32, I-00185 Rome, Italy
Corresponding author: Moreno Di Marco (moreno.dimarco@uniroma1.it)
Academic editor: Lyubomir Penev|Received3 July 2013|Accepted 28 August 2013|Published 13 November 2013
Citation: Pacici M, Santini L, Di Marco M, Baisero D, Francucci L, Grottolo Marasini G, Visconti P, Rondinini
C (2013) Generation length for mammals. Nature Conservation 5: 87–94. doi: 10.3897/natureconservation.5.5734
Resource ID: Dryad key: 10.5061/dryad.2jd88
Resource citation: Pacici M, Santini L, Di Marco M, Baisero D, Francucci L, Grottolo Marasini G, Visconti P,
Rondinini C (2013) Database on generation length of mammals. 5427 data records. Online at http://doi.org/10.5061/
dryad.gd0m3, version 1.0 (last updated on 2013-08-27, Resource ID: 10.5061/dryad.2jd88, Data Paper ID: doi:
10.3897/natureconservation.5.5734
Abstract
Generation length (GL) is dened as the average age of parents of the current cohort, reecting the turno-
ver rate of breeding individuals in a population. GL is a fundamental piece of information for population
ecology as well as for measuring species threat status (e.g. in the IUCN Red List). Here we present a
dataset including GL records for all extant mammal species (n=5427). We rst reviewed all data on GL
published in the IUCN Red List database. We then calculated a value for species with available reproduc-
tive parameters (reproductive life span and age at rst reproduction). We assigned to missing-data species
a mean GL value from congeneric or confamilial species (depending on data availability). Finally, for a
few remaining species, we assigned mean GL values from species with similar body mass and belonging to
the same order. Our work provides the rst attempt to complete a database of GL for mammals; it will be
an essential reference point for all conservation-related studies that need pragmatic information on species
GL, such as population dynamics and applications of the IUCN Red List assessment.
Keywords
Age at rst reproduction, conservation assessment, IUCN Red List, longevity, reproductive life span
Nature Conservation 5: 87–94 (2013)
doi: 10.3897/natureconservation.5.5734
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Introduction
Generation length (GL) has been dened in a number of ways and has been approxi-
mated with a number of dierent formulas (IUCN 2013). e two most common
denitions of GL are: 1) “the average age of parents of the current cohort” (IUCN
2001, 2012b), 2) “the age at which half of total reproductive output is achieved by an
individual” (IUCN 2004). GL is a key vital statistic of animal populations and is used
in a multitude of ecological analyses (Gaillard et al. 2005, Perry et al. 2005, Jiguet et al.
2007). In IUCN Red List assessments, GL is used as a reference time-frame to assess a
species extinction risk due to population reduction (criterion A), continuing decline of
small populations over a denite time period (criterion C1; IUCN 2012b), calculated
extinction probability (criterion E; Mace et al. 2008). Nonetheless, such an important
variable is often hard to calculate due to the paucity of detailed reproductive data.
erefore it is missing for most species, even among relatively well-studied groups such
as mammals. Methods to ll missing-data gaps in biological datasets, such as multiple
imputation, have been applied in mammals (e.g. Di Marco et al. 2012). However, such
methods depend largely on data availability and assume that missing data are distrib-
uted randomly (e.g. among orders). We address this gap and provide the rst attempt
to complete a database of GL for mammals based on recently published datasets, using
published metrics as well as taxonomic and allometric species relationships.
Taxonomic coverage
is database covers all 5427 extant species in the class Mammalia. e taxonomy fol-
lows the IUCN Red List of reatened Species version 2012.2.
Methods
For 439 species, we used stated GL in years available from published IUCN Red List as-
sessments (IUCN 2012a); for 822 additional species we derived GLs from data on spe-
cies’ reproductive life span and age at rst reproduction (see Generation Length model,
below). We obtained life-history traits from PanTHERIA (Jones et al. 2009) and AnAge
(Tacutu et al. 2013). Moreover, for carnivores and ungulates, we applied a multiple
imputation procedure to estimate missing values of life history variables (see below for a
detailed description). We compiled the GL values of 3722 remaining species by assign-
ing them the mean GL value of congeneric or confamilial species (when expert-based
GL values of congeneric species were not available) in the same bin of log body mass.
For the mammal body masses, we used PanTHERIA (Jones et al. 2009) as our
main reference, and complemented the missing data with numerous other sources, in-
cluding books and primary literature (see Appendix). For species that lacked body mass
data (1047), we calculated the average body mass of congeneric or confamilial species.

Generation length for mammals 89
For 315 species, lacking a congeneric or confamilial species in the same bin of log
body mass, we assigned the mean GL value of congenerics or confamilials, irrespective
of their body mass. For the remaining species (n=116, 2.1 % of the total), where no
information was available for congeneric or confamilial species, we assigned the mean
GL value of species in the same bin of log body mass, belonging to the same order, or
simply the mean GL values of the order (2 species, Ptilocercus lowii and Cyclopes didac-
tylus). We made an exception for the two species of Dermoptera and 9 species of small
mammals (body mass < 100 g); since they were the only representatives of their orders,
we estimated mean GLs from species belonging to the same bin of log body mass. In
this way, we obtained a GL value for all existing 5427 mammals.
Generation length model
We estimated GL for mammals from information on species age at rst reproduction
and reproductive life span, by applying the methodology described in the IUCN Red
List Guidelines (IUCN 2013):
(eq. 1)
where Rspan is the species reproductive life span, calculated as the dierence between
the age at last reproduction and the age at rst reproduction (AFR), and z is a con-
stant “depending on survivorship and relative fecundity of young vs. old individuals
in the population” (IUCN 2013). Generation length values in the Red List are typi-
cally provided for threatened species (Vulnerable to Critically Endangered) assessed
under criteria A and C1 (IUCN 2001). As largely discussed (e.g. Purvis et al. 2000;
Cardillo et al. 2005), threatened species are generally characterised by relatively slow
life histories respect to non-threatened species (e.g. they are generally larger, have
longer gestation times, smaller litter sizes etc.). is has a potential to bias the tting
of GL model parameter toward long-living species respect to short-living ones. None-
theless, a moderate change in the z parameter, e.g. z=0.29 in our model (calculated
as the slope of the linear regression between GL and Rspan for 221 species) vs the
theoretical threshold of 0.5 proposed in IUCN guidelines, will have little inuence
on the calculation of a GL value for short-living species (such as most of rodents), e.g.
their modelled GL will remain below 3.3 years in any case (i.e. the arbitrary threshold
adopted for short-generation species in the Red List). For those 221 species with GL
data reported in IUCN Red List assessments, we modelled the linear relationship be-
tween expert-based GL values and calculated GL values (from reproductive life span
and age at rst reproduction). We found a good t (R2=0.84) and a high correlation
(cor=0.92, p-value of the Pearson’s test < 2.2e-16), which indicate a good correspond-
ence between reported and calculated GL values, and we are condent that this is a
good validation of the overall validity of the GL data reported in the IUCN Red List
for mammals. Discrepancies between the calculated GLs and the GLs IUCN might

Michela Pacici et al. / Nature Conservation 5: 87–94 (2013)
90
be a mix of process uncertainty (errors in the model) and observation uncertainty (er-
rors in expert-based GL estimates), which are impossible to tease apart.
Since age at last reproduction is generally related to longevity in the wild (IUCN
2013), we assumed it to be equal to the maximum known longevity of the species.
Even if published data on maximum longevity often refer to captive individuals, which
might cause biases in Rspan estimates, we believe that these biases will probably inu-
ence only a limited number of large-bodied species. Moreover, since data on GL stated
from experts were available for the majority of large-body species, we reduced the risk
of using inaccurate data. We assumed AFR to be equal to age at rst birth following
IUCN guidelines (IUCN 2013). When information on age at rst reproduction for
a species was not available, we estimated it by summing gestation length and age at
female sexual maturity. For species without empirical data on age at rst reproduction
for females, we used age at sexual maturity for males.
For carnivore and ungulate species, we completed missing data on maximum lon-
gevity and age at sexual maturity through a multiple imputation procedure (Rubin
1987). Carnivores and ungulates are generally characterized by lower levels of missing
life-history data respect to other mammal groups (e.g. see Jones et al. 2009). Repro-
ductive parameters used in our analyses were available for over 50% of species among
Carnivora, Cetartiodactyla and Perissodactyla. Missing life-history traits were imput-
ed, separately for carnivores and ungulates, following the procedure described in Di
Marco et al. (2012). In both datasets, all missing data were imputed 10 times in order
to obtain 10 complete datasets for each group. Finally, a median value was calculated
for all imputed data for maximum longevity and sexual maturity for each species. Mul-
tiple imputation analyses were conducted in R using the package MICE (van Buuren
and Groothuis-Oudshoorn 2010).
Dataset description
e dataset includes generation lengths for 5427 mammal species. Fields given are:
1. TaxID: identication number of species;
2. Order;
3. Family;
4. Genus;
5. ScienticName;
6. AdultBodyMass_g: body mass of species in grams;
7. Sources_AdultBodyMass: AnAge, Animal Diversity, Encyclopedia of Life (eol.
org/), Nowak and Paradiso 1999, PanTHERIA, Smith et al. 2003, Verde Arregoi-
tia et al. 2013, Mean congenerics, Mean_confamilials;
8. Max_longevity_d: maximum longevity (days) mediated from PanTHERIA, An-
Age and Carn_Ung (multiple imputation for carnivores and ungulates);

Generation length for mammals 91
9. Sources_Max_longevity: AnAge, Carn_ung (multiple imputation for ungulates
and carnivores) and PanTHERIA;
10. CalculatedRspan_d: reproductive life span (days) calculated from maximum lon-
gevity and age at rst reproduction;
11. AFR_d; age at rst reproduction (days);
12. Data_AFR: calculated or published data;
13. CalculatedGL_d: GL (days) calculated from reproductive life span and age at rst
reproduction;
14. GenerationLength_d: best known estimate of GL (days), including information
taken from IUCN database, calculated data and mean estimates;
15. Sources_GL:
 GMA (IUCN Red List data);
 Rspan-AFB (GL calculated as the dierence between reproductive life span
and age at rst birth);
 Rspan-AFR(SM+Gest) (when data on age at rst reproduction were not avail-
able, we calculated this parameter as the sum between age at female sexual maturity
and gestation length);
 Rspan-ASMmales (GL calculated with age at sexual maturity for males, when
data on age at rst reproduction for females were not available);
 Mean_congenerics_same_body_mass (mean GL calculated from congeneric
species in the same bin of log body mass);
 Mean_congenerics (mean GL calculated from congeneric species, irrespective
of body mass);
 Mean_family_same_body_mass (mean GL calculated from confamilial spe-
cies in the same bin of log body mass);
 Mean_family (mean GL calculated from confamilial species, irrespective of
body mass);
 Mean_order_same_mass (for species with unknown parameter estimates, we
assigned the mean GL value of species in the same bin of log body mass and belonging
to the same order);
 Mean_order (mean GL calculated from species belonging to the same order,
irrespective of body mass);
 Mean_all_orders_same_body_mass (species for which we estimated mean GL
from species belonging to the same bin of log body mass).
Data sources
e data underpinning the analysis reported in this paper are deposited in the Dryad
Data Repository at http://doi.org/10.5061/dryad.gd0m3

Michela Pacici et al. / Nature Conservation 5: 87–94 (2013)
92
Original source
Pacici M, Santini L, Di Marco M, Baisero D, Francucci L, Grottolo Marasini G,
Visconti P, Rondinini C (2013) Generation length for mammals. Nature Conser-
vation 5: 87–94. doi: 10.3897/natureconservation.5.5734
References
Boyles JG, Cryan PM, McCracken GF, Kunz TH (2011) Economic importance of bats in
agriculture. Science 332(6025): 41–42. doi: 10.1126/science.1201366
Cardillo M, Mace GM, Jones KE, Bielby J, Bininda-Emonds ORP, Sechrest W, Purvis A
(2005) Multiple causes of high extinction risk in large mammal species. Science 309(5738):
1239–1241. doi: 10.1126/science.1116030
Di Marco M, Possingham HP, Wilson KA, Blomberg SP, Boitani L, Rondinini C (2012) ANovel
Approach for Global Mammal Extinction Risk Reduction. Conservation Letters 28–66.
Fa J, Currie D, Meeuwig J (2003) Bushmeat and food security in the Congo Basin: link-
ages between wild- life and people’s future. Environ. Conserv. 30: 71–78. doi: 10.1017/
S0376892903000067
Gaillard JM,Yoccoz NG,Lebreton J-D,Bonenfant C,Devillard S, Loison A, Pontier D, and
Allaine D (2005) Generation Time: A Reliable Metric to Measure Life‐History Variation
among Mammalian Populations. e American Naturalist, Vol. 166, No. 1, 119–123.
doi: 10.1086/430330
Hoyt E (2000) Whale watching 2000: worldwide tourism numbers, expenditures, and expand-
ing socioeconomic benets. International Fund for Animal Welfare, Crowborough, UK.
IUCN (2001) IUCNRed List Categories and Criteria: Version 3.1. IUCNSpecies Survival
Commission. IUCN, Gland, Switzerland and Cambridge, U.K.
IUCN (2004) Guidelines for Using the IUCNRed List Categories and Criteria. Standards
and Petitions Subcommittee. http://www.globaltrees.org/downloads/RedListGuidelines.
pdf [accessed 2013-3-10]
IUCN (2012a) eIUCNRed List of reatened Species. Version 2012.2. http://www.iucn-
redlist.org [accessed 2013-3-18]
IUCN (2012b) IUCNRed List Categories and Criteria: Version 3.1. Second edition. IUCN,
Gland, Switzerland and Cambridge, UK. http://www.iucnredlist.org/technical-docu-
ments/categories-and-criteria [accessed 2013-3-18]
IUCN (2013) Guidelines for Using the IUCNRed List Categories and Criteria. Version 10.
Standards and Petitions Subcommittee. http://www.iucnredlist.org/documents/RedList-
Guidelines.pdf [accessed 2013-3-10]
Jiguet F, Gadot A-S, Julliard R, Newson SE, Couvet D (2007) Climate envelope, life history
traits and the resilience of birds facing global change. Global Change Biology 13: 1672–
1684. doi: 10.1111/j.1365-2486.2007.01386.x
Jones K, Bielby J, Cardillo M, Fritz S, O’Dell J, Orme CDL, Sa K, Sechrest W, Boakes EH,
Carbone C, Connolly C, Cutts MJ, Foster JK, Grenyer R, Habib M, Plaster CA, Price SA,

Generation length for mammals 93
Rigby EA, Rist J, Teacher A, Bininda-Emonds ORP, Gittleman JL, Mace GM, Purvis A,
Michener WK (2009) PanTHERIA: a species-level database of life history, ecology, and
geography of extant and recently extinct mammals. Ecology 90(9): 2648. doi: 10.1890/08-
1494.1
Kunz TH, Braun de Torrez E, Bauer D, Lobova T, Fleming TH (2011) Ecosystem ser-
vices provided by bats. Annals of the New York Academy of Sciences 1223:1–38. doi:
10.1111/j.1749-6632.2011.06004.x
Mace GM, Collar NJ, Gaston KJ, Hilton-Taylor C, Akçakaya HR, Leader-Williams N, Mill-
ner-Gulland AJ, Stuart SN (2008) Quantication of extinction risk: IUCN’s system for
classifying threatened species. Conservation Biology 22: 1424–1442. doi: 10.1111/j.1523-
1739.2008.01044.x
Nowak RM, Paradiso JL (1999) Walker’s mammals of the world. Vol. 1. Baltimore and Lon-
don, UK.
Perry AL, Low PJ, Ellis JR, Reynolds JD (2005) Climate change and distribution shifts in ma-
rine shes. Science 308: 1912–1915. doi: 10.1126/science.1111322
Purvis A, Gittleman JL, Cowlishaw G, Mace GM (2000) Predicting extinction risk in declin-
ing species. Proceedings of the Royal Society B 267(1456): 1947–1952. doi: 10.1098/
rspb.2000.1234
Rubin DB (1987) Multiple imputation for nonresponse in surveys. Wiley Online Library.
Smith FA, Lyons SK, Ernest SKM, Jones KE, Kaufman DM, Dayan T, Marquet PA, Brown JH,
Haskell JP (2003) Body mass of late quaternary mammals. Ecology 84: 87131.
Tacutu R, Craig T, Budovsky A (2013) Human Ageing Genomic Resources: Integrated data-
bases and tools for the biology and genetics of ageing. Nucleic Acids Research 41: 1027–
1033. doi: 10.1093/nar/gks1155
van Buuren S, Groothuis-Oudshoorn K (2010) MICE: Multivariate Imputation by Chained.
JStat Softw VV: 1–68.
Verde Arregoitia LD, Blomberg SP, Fisher DO (2013) Phylogenetic correlates of extinction
risk in mammals: species in older lineages are not at greater risk. Proceedings. Biological
sciences / e Royal Society 280: 20131092. doi: 10.1098/rspb.2013.1092

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Appendix
Database on generation length of mammals. (doi: 10.3897/natureconservation.5.5734.
app). File format: Microsoft Excel le (xls).
Explanation note: Database on generation length of all extant mammals, with 5427
records.
Copyright notice: is dataset is made available under the Open Database License
(http://opendatacommons.org/licenses/odbl/1.0/). e Open Database License
(ODbL) is a license agreement intended to allow users to freely share, modify, and use
this Dataset while maintaining this same freedom for others, provided that the original
source and author(s) are credited.
Citation: Pacici M, Santini L, Di Marco M, Baisero D, Francucci L, Grottolo Marasini G, Visconti P, Rondinini
C (2013) Generation length for mammals. Nature Conservation 5: 87–94. doi: 10.3897/natureconservation.5.5734
Database on generation length of mammals. doi: 10.3897/zookeys.5.5734.app