Generation length for mammals

Article (PDF Available)inNature Conservation 5(6025):87-94 · November 2013with 812 Reads
DOI: 10.3897/natureconservation.5.5734
Cite this publication
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.
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 (
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
dryad.gd0m3, version 1.0 (last updated on 2013-08-27, Resource ID: 10.5061/dryad.2jd88, Data Paper ID: doi:
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.
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
Copyright Michela Pacifici et al. This is an open access article distributed under the terms of the Creative Commons Attribution License 3.0
(CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Launched to accelerate biodiversity conservation
A peer-reviewed open-access journal
Michela Pacici et al. / Nature Conservation 5: 87–94 (2013)
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.
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)
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
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

Supplementary resources

  • Article
    Full-text available
    Species, and their ecological strategies, are disappearing. Here we use species traits to quantify the current and projected future ecological strategy diversity for 15,484 land mammals and birds. We reveal an ecological strategy surface, structured by life-history (fast-slow) and body mass (small-large) as one major axis, and diet (invertivore-herbivore) and habitat breadth (generalist-specialist) as the other. We also find that of all possible trait combinations, only 9% are currently realized. Based on species’ extinction probabilities we predict this limited set of viable strategies will shrink further over the next 100 years, shifting the mammal and bird species pool towards small, fast-lived, highly fecund, insect-eating, generalists. In fact, our results show that this projected decline in ecological strategy diversity is much greater than if species were simply lost at random. Thus, halting the disproportionate loss of ecological strategies associated with highly threatened animals represents a key challenge for conservation.
  • Article
    Full-text available
    This subspecies is listed as Vulnerable (VU A3bcd) due to the probability of a future population reduction of at least 30% within the next 33 years (three generations) if further severe droughts occur. While the population has increased in recent years, Hartmann's Mountain Zebra (HMZ) remain at threat from another catastrophic drought as this would probably result in mortality across their range, but particularly of a high proportion of zebras on private farms and freehold conservancies. Over 3,500 HMZ are killed annually under license (data from 2008-2012, Shapi 2014, CITES trade statistics). At the moment this appears sustainable, but changing climatic conditions combined with over-harvesting could quickly cause this species to become threatened again. We have not been able to carry out a detailed analysis of the impact of the early 1980s drought but recommend that this should be done if sources can be identified. It is important to fully understand that the current population is more vulnerable than it may appear from its numbers alone and that we should learn the lessons of past droughts to plan conservation measures for a sustainable future. The text of this reassessment of the conservation status of Hartmann's mountain zebra is available on the IUCN website at:-
  • Preprint
    Full-text available
    Aging is associated with accumulation of somatic mutations⁠. This process is especially pronounced in mitochondrial genomes of postmitotic cells, which accumulate large-scale somatic mitochondrial deletions with time⁠ , leading to neurodegeneration, muscular dystrophy and aging. Slowing down the rate of origin of these somatic deletions may benefit human lifespan and healthy aging. The main factors determining breakpoints of somatic mitochondrial deletions are direct nucleotide repeats⁠ , which might be considered as Deleterious In Late Life (DILL) alleles. Correspondingly, the decreased amount of these DILL alleles might lead to low production of somatic deletions and increased lifespan. Intriguingly, in the Japanese D4a haplogroup, which is famous for an excess of centenarians and supercentenarians, we found that the longest direct repeat ("common repeat") in the human mitochondrial genome has been disrupted by a point synonymous mutation. Thus we hypothesize that the disruption of the common repeat annuls common deletion (which is the most frequent among all somatic deletions) and at least partially may contribute to the extreme longevity of the D4a Japanese haplogroup⁠. Here, to better understand the mitochondrial components of longevity and potential causative links between repeats, deletions and longevity we discuss molecular, population and evolutionary factors affecting dynamics of mitochondrial direct repeats. 2 All rights reserved. No reuse allowed without permission. (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.
  • Article
    Full-text available
    Anthropogenic climate change has been shown to be one of the most pervasive threats to biodiversity. However, few studies have considered its effects on whole communities. Here, using ecological niche models (ENM) and projected future climate scenarios, we analyzed how these environmental changes could promote reductions in the alpha and beta taxonomic, phylogenetic, and functional diversities of mammals in the Cerrado Biodiversity Hotspot. We found that, on average, species richness tends to decrease in most Cerrado areas under future climate scenarios. However, this pattern is not uniform throughout the biome. Overall, southern Brazilian Cerrado may become biotically homogenized – through the extinction of native specialists and expansion of exotic generalists – in the near future, while the rest of biome may become very heterogeneous in taxonomic, phylogenetic and functional aspects. This scenario is very problematic considering that this region has been highly transformed and fragmented by human activities in the past. Based on our ENM approach of species inhabiting present Cerrado, we provided a more accurate analysis about the effects of anthropogenic and/or natural processes at large scales on the communities for this endangered Biodiversity Hotspot. This information could represent invaluable tool to guide future establishment of new and efficient conservation efforts. © 2019 Associação Brasileira de Ciência Ecológica e Conservação
  • Article
    Generation time is a fundamental component of extinction risk assessments for the International Union for Conservation of Nature’s Red List of Threatened Species. The calculation of generation time requires age‐specific data on survival and fecundity rates and knowledge of population growth rates. These data are generally lacking for threatened species, so approximations including only partial demographic information need to be used. This leads to potential errors in generation time estimates. To quantify the magnitude of potential errors in generation time estimates, we compared seven approximations with exact generation time measures, calculated either from complete life tables available for 58 mammalian species or from simulated data. We tested the influence of these errors on conservation assessments conducting mock assessments for ten species. We also tested the commonly used prediction of generation time based on the allometric relationship with body mass using phylogenetic generalized least squares. Root mean square errors were largest in measures assuming constant fecundity with age, some of which are currently used in Red List assessments. We found that the measure of generation time that only ignores population growth rates performed relatively well, but tended to underestimate the generation time for decreasing populations, and over‐estimate it for increasing populations. In the mock assessment, we found that we underestimated the threat level in 10% to 90% of the species depending on the generation time approximation we used. The predictive metric of generation time based on body mass is inaccurate. We propose an alternative predictive metric based on body mass, age at first reproduction, and reproductive life span. Synthesis and applications. Our results demonstrate potential errors that occur when estimating generation time in the absence of key demographic information. We offer practical recommendations for extinction risk assessments including more rigorous mathematical formulations of generation time, such as the measure of generation time that includes population growth rates and the appropriate age‐specific vital rates. Furthermore, we recommend alerting risk assessors of the uncertainties in proxy measures, such as the underestimation of generation time resulting from the assumption of constant fecundity in future Red List assessments.
  • Article
    Full-text available
  • Article
    The phylogenetic position of owl monkeys, grouped in the genus Aotus, has been a controversial issue for understanding Neotropical primate evolution. Explanations of the difficult phylogenetic assignment of owl monkeys have been elusive, frequently relying on insufficient data (stochastic error) or scenarios of rapid speciation (adaptive radiation) events. Using a coalescent‐based approach, we explored the population‐level mechanisms likely explaining these topological discrepancies. We examined the topological variance of 2,192 orthologous genes shared between representatives of the three major Cebidae lineages and the outgroup. By employing a methodological framework that allows for reticulated tree topologies, our analysis explicitly tested for non‐dichotomous evolutionary processes impacting the finding of the position of owl monkeys in the cebid phylogeny. Our findings indicated that Aotus is a sister lineage of the callitrichines. Most gene trees (>50%) failed to recover the species tree topology, although the distribution of gene trees mismatching the true species topology followed the standard expectation of the multispecies coalescent without reticulation. We showed that the large effective population size of the common ancestor of Aotus and callitrichines was the most likely factor responsible for generating phylogenetic uncertainty. On the other hand, fast speciation scenarios or introgression played minor roles. We propose that the difficult phylogenetic placement of Aotus is explained by population‐level processes associated with the large ancestral effective size. These results shed light on the biogeography of the early cebid diversification in the Miocene, highlighting the relevance of evaluating phylogenetic relationships employing population‐aware approaches.
  • Article
    Red List Category & Criteria: Least Concern ver 3.1 Year Published: 2008 Date Assessed: 2008-06-30 Assessor(s): Aplin, K., Molur, S. & Nameer, P.O. Reviewer(s): Amori, G. (Small Nonvolant Mammal Red List Authority) & Cox, N. (Global Mammal Assessment Team)
  • Article
    Full-text available
    Tropical moist forests in Africa are concentrated in the Congo Basin. A variety of animals in these forests, in particular mammals, are hunted for their meat, termed bushmeat. This paper investigates current and future trends of bushmeat protein, and non-bushmeat protein supply, for inhabitants of the main Congo Basin countries. Since most bushmeat is derived from forest mammals, published extraction (E) and production (P) estimates of mammal populations were used to calculate the per person protein supplied by these. Current bushmeat protein supply may range from 30 g person1 in the Democratic Republic of Congo, to 180 g person1 in Gabon. Future bushmeat protein supplies were predicted for the next 50 years by employing current E:P ratios, and controlling for known deforestation and population growth rates. At current exploitation rates, bushmeat protein supply would drop 81% in all countries in less than 50 years; only three countries would be able to maintain a protein supply above the recommended daily requirement of 52 g person1. However, if bushmeat harvests were reduced to a sustainable level, all countries except Gabon would be dramatically affected by the loss of wild protein supply. The dependence on bushmeat protein is emphasized by the fact that four out of the five countries studied do not produce sufficient amounts of non-bushmeat protein to feed their populations. These findings imply that a significant number of forest mammals could become extinct relatively soon, and that protein malnutrition is likely to increase dramatically if food security in the region is not promptly resolved.
  • Article
    Full-text available
    We show that the distributions of both exploited and nonexploited North Sea fishes have responded markedly to recent increases in sea temperature, with nearly two-thirds of species shifting in mean latitude or depth or both over 25 years. For species with northerly or southerly range margins in the North Sea, half have shown boundary shifts with warming, and all but one shifted northward. Species with shifting distributions have faster life cycles and smaller body sizes than nonshifting species. Further temperature rises are likely to have profound impacts on commercial fisheries through continued shifts in distribution and alterations in community interactions.
  • Article
    Full-text available
    Phylogenetic information is becoming a recognized basis for evaluating conservation priorities, but associations between extinction risk and properties of a phylogeny such as diversification rates and phylogenetic lineage ages remain unclear. Limited taxon-specific analyses suggest that species in older lineages are at greater risk. We calculate quantitative properties of the mammalian phylogeny and model extinction risk as an ordinal index based on International Union for Conservation of Nature Red List categories. We test for associations between lineage age, clade size, evolutionary distinctiveness and extinction risk for 3308 species of terrestrial mammals. We show no significant global or regional associations, and three significant relationships within taxonomic groups. Extinction risk increases for evolutionarily distinctive primates and decreases with lineage age when lemurs are excluded. Lagomorph species (rabbits, hares and pikas) that have more close relatives are less threatened. We examine the relationship between net diversification rates and extinction risk for 173 genera and find no pattern. We conclude that despite being under-represented in the frequency distribution of lineage ages, species in older, slower evolving and distinct lineages are not more threatened or extinction-prone. Their extinction, however, would represent a disproportionate loss of unique evolutionary history.
  • Article
    Full-text available
    The Human Ageing Genomic Resources (HAGR, is a freely available online collection of research databases and tools for the biology and genetics of ageing. HAGR features now several databases with high-quality manually curated data: (i) GenAge, a database of genes associated with ageing in humans and model organisms; (ii) AnAge, an extensive collection of longevity records and complementary traits for >4000 vertebrate species; and (iii) GenDR, a newly incorporated database, containing both gene mutations that interfere with dietary restriction-mediated lifespan extension and consistent gene expression changes induced by dietary restriction. Since its creation about 10 years ago, major efforts have been undertaken to maintain the quality of data in HAGR, while further continuing to develop, improve and extend it. This article briefly describes the content of HAGR and details the major updates since its previous publications, in terms of both structure and content. The completely redesigned interface, more intuitive and more integrative of HAGR resources, is also presented. Altogether, we hope that through its improvements, the current version of HAGR will continue to provide users with the most comprehensive and accessible resources available today in the field of biogerontology.
  • Article
    Few studies have examined how life history traits and the climate envelope influence the ability of species to respond to climate change and habitat degradation. In this study, we test whether 18 species-specific variables, related to the climate envelope, ecological envelope and life history, could predict recent population trends (over 17 years) of 71 common breeding bird species in France. Habitat specialists were declining at a much higher rate than generalists, a sign that habitat quality is decreasing globally. The lower the thermal maximum (temperature at the hot edge of the climate envelope), the more negative are the population trends and the less tolerant these species are climate warming, regardless of the thermal range over which these species occur. The life history trait ‘the number of broods per year’ was positively related to recent trends, suggesting that single-brooded species might be more sensitive to advances in food peak due to climate change, as it increases the risk of mistiming their single-breeding event. Annual fecundity explained long-term declines, as it is a good proxy for most other demographic rates, with shorter-lived species being more sensitive to global change: individuals of species with higher fecundity might have too short a life to learn to adapt to directional changes in their environment. Finally, there was evidence that natal dispersal was a predictor of recent trends, with species with high natal dispersal experiencing smaller population declines than species with low natal dispersal. This is expected if the higher the natal dispersal, the larger the ability to shift spatially when facing changes in local habitat or climate, in order to track optimal conditions and adapt to global change. Identifying decline-promoting factors allow us to infer mechanisms responsible for observed declines in wild bird populations facing global change, and by doing so allow for a more pre-emptive approach to conservation planning.
  • Article
    With one-fourth of the world's mammals threatened with extinction and limited budget to save them, adopting an efficient conservation strategy is crucial. Previous approaches to setting global conservation priorities have assumed all species to have equal conservation value, or have focused on species with high extinction risk, species that may be hard to save. Here, we identify priority species for optimizing the reduction in overall extinction risk of the world's threatened terrestrial mammals. We take a novel approach and focus on species having the greatest recovery opportunity using a new conservation benefit metric: the Extinction risk Reduction Opportunity (ERO). We discover that 65-87% of all threatened and potentially recoverable species are overlooked by existing prioritization approaches. We use the ERO metric to prioritize threatened species, but the potential applications are broader; ERO has the potential to integrate with every strategy that aims to maximize the likelihood of conservation success.