Reproductive Viability Analysis (RVA) as a new tool for ex situ population management - Squarespace

 
Received: 4 July 2018      |   Revised: 14 December 2018   |   Accepted: 21 December 2018
DOI: 10.1002/zoo.21477

RESEARCH ARTICLE

Reproductive Viability Analysis (RVA) as a new tool for ex
situ population management

Karen Bauman1                         |      John Sahrmann2 | Ashley Franklin2                                    |   Cheryl Asa2 |
Mary Agnew2 | Kathy Traylor-Holzer3                                               |   David Powell1

1 Saint   Louis Zoo, Saint Louis, Missouri
2 AZA  Reproductive Management Center,
                                                     Many animal populations managed by the Association of Zoos and Aquariums’ (AZA)
Saint Louis Zoo, Saint Louis, Missouri               Species Survival Plans® (SSPs) have low rates of reproductive success. It is critical that
3 IUCN SSC Conservation Planning Specialist          individuals recommended to breed are successful to achieve genetic and demographic
Group, Apple Valley, Minnesota
                                                     goals set by the SSP. Identifying factors that impact reproductive success can inform
Correspondence
                                                     managers on best practices and improve demographic predictions. A Reproductive
Karen Bauman, Saint Louis Zoo, 1
Government Drive, Saint Louis, MO 63110.             Viability Analysis (RVA) utilizes data gathered from Breeding and Transfer Plans,
Email: kbauman@stlzoo.org
                                                     studbooks, and SSP documents, and through modeling identifies factors associated
                                                     with reproductive success in a given species. Here, we describe the RVA process,
                                                     including different statistical models with the highest accuracy for predicting
                                                     reproductive success in fennec foxes (Vulpes zerda) and Mexican wolves (Canis lupus
                                                     baileyi). Results from the RVA provide knowledge that can be used to make evidence-
                                                     based decisions about pairing and breeding strategies as well as improving
                                                     reproductive success and population sustainability.

                                                     KEYWORDS
                                                     ex situ, reproductive success, sustainability

1 | INTRODUCTION                                                                       Mexican grey wolves Canis lupus baileyi, a species extinct in the wild,
                                                                                       into Arizona and New Mexico in 1998 (USFWS, 2017). There are now
Cooperative breeding and management programs in professionally                         more than 500 SSPs and similar programs in other regional zoo and
managed zoos and aquariums in the United States, administered by the                   aquarium associations.
Association of Zoos and Aquariums (AZA), have been organized since                          However, studies by several authors have demonstrated that not
the 1980's (Ballou et al., 2010, and see Powell, Dorsey, & Faust, this                 all managed programs are meeting their target genetic and demo-
issue). Each of these programs, called Species Survival Plans® [SSP],                  graphic goals and are not sustainable (Lees & Wilcken, 2009; Leus et al.,
focuses on a single species, with a studbook as its foundation; the                    2011; Long, Dorsey, & Boyle, 2011; and see Che-Castro et al., this
studbook is a computerized genealogy for every individual in the SSP                   issue). The historic separation between the ex situ and in situ
population. All SSPs were originally designed to be insurance or ‘ark’                 communities is now gradually being replaced by a mutual respect for
populations, which were demographically and genetically sustainable                    the roles each plays in species recovery and conservation, allowing
to maintain 90% of the gene diversity from the founding population for                 efforts in both realms to be integrated (Conde, Flesness, Colchero,
200 years [later revised to 100 years] (Ballou et al., 2010; Soule, Gilpin,            Jones, & Scheuerlein, 2011; Conde et al., 2015; Maunder & Byers,
Conway, & Foose, 1986; and references therein). Cooperative                            2005; McGowan, Traylor-Holzer, & Leus, 2016; Pritchard, Fa, Oldfield,
breeding programs have directly aided in the recovery of some                          & Harrop, 2011). The “One Plan Approach” promotes this collaborative
species (Conde et al., 2013; Hoffmann et al., 2010), and have served as                process to develop a single integrated species conservation plan
a source of animals for release, for example, the reintroduction of                    (Byers, Lees, Wilcken, & Schwitzer, 2013; Traylor-Holzer, Leus, &

Zoo Biology. 2019;38:55–66.                                    wileyonlinelibrary.com/journal/zoo                           © 2019 Wiley Periodicals, Inc.   |   55
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Byers, 2018). Moreover, intensive species prioritization tools have            tool that analyzes the inherent biological and reproductive character-
been created, for example, the IUCN SSC Conservation Planning                  istics of individual animals (e.g., age, parity, rearing type) and of
Specialist Group's new Integrated Collection Assessment and Planning           breeding pairs (e.g., experience as a pair, age difference) that correlate
(CPSG ICAP) process that can be used to guide ex situ global or regional       with successful reproduction, that is, the “reproductive viability” of a
collection planning (Traylor-Holzer et al., this issue). Yet, if the ex situ   given species. The RVA is similar to a PVA in that it utilizes a variety of
community is to be increasingly relied upon for conservation roles, we         data inputs, is data intensive, and through modeling determines what
must assure that cooperative breeding programs are efficient and we            factors impact outcomes (in this case reproductive success), and thus
are managing robust, viable populations.                                       are key to population persistence. Unlike a PVA, though, the RVA
         SSP sustainability has been addressed in several ways. AZA has        process generally ignores environmental and management factors and
partnered with the Lincoln Park Zoo and the AZA Population                     does not make projections about the future status of populations.
Management Center (PMC) to conduct population viability analyses                   Here we describe the RVA process and present results from the
(PVAs) on many SSPs (Che-Castaldo et al., this issue). A web-based             first two RVAs, conducted for Mexican wolves (Canis lupus baileyi) and
program called PMCTrack, was developed as a tool to improve                    fennec foxes (Vulpes zerda). These species were selected because they
population sustainability (Faust et al., 2011). PMCTrack maintains             had good quality source data readily available, the reproductive
studbook data, as well as the SSP Breeding and Transfer Plans (BTP)            physiology of both species has been well studied (Asa & Valdespino,
recommendations, and through a user interface tracks breeding and              1998; Valdespino, Asa, & Bauman, 2002), and canids were identified as
transfer recommendation fulfillment (or lack thereof) to identify              a taxon of concern (Agnew & Asa, 2014; Asa et al., 2014). The AZA
obstacles so they can be addressed. A recent analysis of SSP breeding          Fennec Fox SSP program, like many small canid programs, has
recommendations found that on average only 20% of breeding                     struggled to maintain a sustainable population due to inconsistent
recommendations were being fulfilled (Faust et al., this issue).               reproductive success (Bauman, Mekarska, Grisham, & Lynch, 2010). In
Unfulfilled recommendations were the result of many factors, some              contrast, the AZA Mexican Wolf SSP has had relatively reliable
being logistical or related to institutional compliance (e.g., institutional   reproduction in general but higher inbreeding than most populations
failure to transfer, weather preventing transfer, failure to put animals       since there were only seven founders.
together), while others were likely due to biological factors such as              Several different modeling approaches are used in the RVA
incompatibility (see Martin-Wintle et al., this issue) or fertility (animals   process (see section 2) to determine which has the best power at
were put together, but did not produce offspring). AZA addressed the           predicting reproductive success. For these species, we predicted that
issues relating to logistics by re-structuring programs, providing             an experience-based model, where the variables to be tested against
participation incentives, and changing management practices. How-              reproductive success are identified in advance by species coordinators
ever, poor or inconsistent reproduction was not being systematically           with extensive knowledge of the species and for which there is a robust
addressed across SSP programs. Therefore, the AZA expanded the                 scientific literature, would perform best.
purview of the AZA Wildlife Contraception Center (WCC, now called
the AZA Reproductive Management Center or RMC) to identify taxa
                                                                               2 | METHO DS
with high rates of reproductive failure, and suggest approaches to
mitigate problems. The initial focus was largely on carnivores and
                                                                               2.1 | Data sources
ungulates, as studies with elephants, rhinos, wildebeest, felids, and
canids had shown that a common cause of reproductive failure was               Consideration of all pairs, successful or not, is vital to the RVA process for
uterine pathology associated with delayed first reproduction or                proper analysis of factors that promote or hamper reproductive
prolonged periods without production of young, which are manage-               success of a species. We used two primary data sources: the BTPs,
ment strategies often used when SSPs are at capacity—a phenomenon              and the studbooks with the histories of each individual, as well as
characterized as “use it or lose it” (Asa et al., 2014; Penfold, Powell,       supplementary information from the documents maintained by the SSP
Traylor-Holzer, & Asa, 2014; and references therein). However,                 Coordinators and in other AZA databases. BTPs are individual-based
uterine pathology does not explain reproductive failure in all species.        recommendations (breeding/non-breeding, transfer/do not transfer)
Many SSPs have low reproductive efficiency—the number of                       generated each time (every 1–3 years) a SSP meets with the PMC (or
recommended breeding pairs far exceeds the number of offspring                 other population advisor) to review the demographic and genetic status
born. Analyses conducted of the lion [Panthera leo] (Daigle et al., 2015)      of the population as it relates to the long-term goals for the SSP. These
and tiger (Panthera tigris) (Saunders, Harris, Traylor-Holzer, & Good-         recommendations are based upon an analysis of studbook data, along
rowe-Beck, 2014) SSPs provided a valuable starting point for our goal          with animal (e.g., health, behavior, history, and age) and institutional
to establish a method that could be used efficiently in a wide diversity       information are then considered for all animals in the population.
of species to identify the factors that drive reproductive success                 All of the source data were directly entered by hand into Excel,
(Agnew & Asa, 2014). We developed the Reproductive Viability                   however, subsequent to the completion of these initial two RVAs, a
Analysis (RVA) process to analyze past breeding recommendations and            method for populating the RVA data fields directly from PMCTrack
produce timely results from which evidenced-based management                   into an Access database was developed by the RMC which should
decisions could be made to improve SSP sustainability. The RVA is a            make future RVAs more efficient.
BAUMAN    ET AL.
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    A list of the RVA variables with a description along with their              had ever served or were currently serving as an animal ambassador.
source(s) is provided in Table 1. The RVA process relies on a core set of        This is important for this RVA, as approximately one third of the
variables, but is designed to be flexible, so variables may be added             animals in this SSP are used for education programs.
depending on the species and its biology. For example, fennec foxes can
have multiple litters per year so fields were added to include data relating
                                                                                 2.3 | Definition of reproductive success
to any second or third litters. Additionally, species-specific data fields can
also be included to address variables that might be important for breeding       For the RVA, we assigned success (or failure) for each pair based on
success in a given species as suggested by the scientific literature (e.g.,      whether offspring were born (including stillborn offspring) within the
lineage effects in Mexican wolves, see Asa et al., 2007) or management           active period of the BTP. We defined this active period as starting on
experience (e.g., ambassador animal history in fennec foxes). For some           the date the BTP was finalized until the date the next Plan was
species, parameters such as social groupings might be relevant.                  finalized, for example, if a BTP was finalized in July of 2001 with next
                                                                                 plan in 2002, the active period would be July 2001 until July 2002. We
                                                                                 focused on the production of, rather than survival of, offspring because
2.2 | Data collection
                                                                                 birth is the primary indicator that reproduction has been successful.
Data from all available BTPs for each species were used to identify all
recommended breeding pairs. Each pair was assigned a pair type: a
                                                                                 2.4 | Statistical analyses
“new” pair was two individuals recommended to breed together for the
first time; a “carryover” was a pair that had been previously together           Data for any pair that was not given the opportunity to breed were
but had never had offspring together; or an “experienced” pair was one           removed from the primary dataset and analyzed separately using
that had offspring together previously. When one individual had a                descriptive statistics as these data provide important information on
recommendation to breed with more than one partner, each possible                causes of logistical failures. They also can be informative in predicting
pairing was entered as a separate recommendation.                                overall likelihood of breeding recommendation success (e.g., probabil-
    Studbook data were used to provide individual-specific data for              ity of success if transfer is required, see Faust, this issue) and are
each animal in the pair at the time of the breeding recommendation, as           valuable for calculating the number of pairs needed to meet population
well as providing information on any offspring the recommended pair              demographic goals.
produced. Both studbook software programs (PopLink (Faust,                           Descriptive statistics were run on all variables in Table 1 for all
Bergstrom,     Thompson,      &   Bier,   2012)    and    SPARKS      [www.      pairs given the opportunity to breed (primary dataset). Variables that
Species360.org]) have reproductive reports that provide information              had insufficient sample sizes (e.g., prior use of contraception) or had
on parity, details on offspring (birth date, number of offspring born,           low variability (e.g., only one Mexican wolf was hand-reared) were not
other parent of offspring, etc.) and number of years since the last litter.      included in additional analyses. All additional analyses were conducted
Studbook data were also used to identify any offspring produced by               within R version 3.2.1 (R Core Team, 2015) on the subset of variables.
any pairs who had not been recommended to breed. Because staff                   For fennec foxes these included female age, male age, age difference,
experience and management protocols have been associated with                    rearing type, pair parity, pair type, litter last 5 years, litter last 10 years,
reproductive success in some species (Saunders et al., 2014), for each           both at breeding location, and year; whereas for Mexican wolves these
pair we recorded whether the institution receiving the breeding                  were female age, male age, age difference, female inbreeding, male
recommendation had successful reproduction in the previous 5-year                inbreeding, pair parity, pair type, litter last 5 years, litter last 10 years,
period and 10-year period for that species. The studbook was also used           both at breeding location, and year. Success of a pair was treated as a
to provide information on “specialty” fields such as rearing type for            binary response variable. A unique identifier was assigned to each pair
fennec foxes, and lineage for Mexican wolves.                                    that served as a random effect in each model to account for
    Although not available for every SSP, whenever possible,                     dependencies in the data resulting from some pairs receiving more
information provided by the SSP Coordinator on any additional pairs              than one recommendation. The year in which the recommendation
that might have been recommended to breed between published plans                was made was included to test for any change in the rate of success
(interim recommendations) as well as relevant notes including whether            over time independent of the other variables under consideration, for
attempts were made to fulfill recommendations (or not), whether the              example, if husbandry improved.
recommended pair had an opportunity to breed (i.e., were housed                      Four different modeling approaches were utilized in the analysis.
together for a sufficient period of time), and mating behaviors or               The first approach, hereafter referred to as the experience-based
copulation observed are included in the RVA dataset. The majority of             approach, began with the design of eight models consisting of different
these data existed for Mexican wolves, including mate access date                numbers and combinations of the explanatory variables. Variables
information gathered as part of an annual SSP report for US Fish and             were chosen based on results from descriptive statistics of the RVA
Wildlife Service. For fennec foxes, interim recommendations and notes            dataset, consensus from SSP Coordinators regarding what variables
about attempts to fulfill recommendations were available, and the                they believed were relevant to success in the species, and a review of
Coordinator gathered data on opportunity to breed and used                       the literature (Burnham, Anderson, & Huyvaert, 2011; Dochtermann &
institutional records to determine whether the individuals in the pair           Jenkins, 2011; Saunders et al., 2014). Individual models were
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TABLE 1           Description of variables used in the RVA with definition and data source information
    Variable name           Definition                                                                     Data source
    Attributes of pairs
      RecAttempta           “Yes” or “No” depending on if there was an attempt to follow the               SSP coordinator and/or Institutional
                              breeding recommendation (animals transferred/animals put together/             Representative
                              etc.).
      Successa              “Yes” if the pair successfully produced offspring (live or stillborn) during   Studbook
                              the B&T Plan period. “No” if the pair was unsuccessful.
      BTYeara               Master Plan/Breeding & Transfer Plan the pair is listed in (year only); or     Breeding & Transfer Plan; SSP coordinator for
                             year of interim recommendation                                                  Interim Recommendations
      Locationa             Institution where the pair was recommended to breed in Master Plan/            Breeding & Transfer Plan; SSP coordinator for
                              Breeding & Transfer Plan                                                       Interim Recommendations
      AtLocationa           “Yes” if both the male and female in the pair are at the same institution      Breeding & Transfer Plan; Studbook
                              already prior to the date the B&T plan was published. “No” if one or
                              both individuals has to be transferred to a new institution to fulfill the
                              breeding recommendation
      IntSuccess5           Has the institution successfully bred this species in the five years prior     Studbook
                             to the published date of the B&T plan? “Yes” or “No”
      IntSuccess10          Has the institution successfully bred this species in the ten years prior to   Studbook
                             the published date of the B&T plan? “Yes” or “No”
      PairType              “New” if pair has the opportunity to breed together for the first time;        Breeding & Transfer Plans; Studbook (for non-
                              “experienced” if the pair had a previous opportunity together and              recommended breeding); SSP coordinator for
                              they successfully produced offspring; or “carryover” if the pair had a         interim pairs
                              previous opportunity together but has never produced offspring.
      PairParity            “Parous” if both individuals are parous; “Nulliparous” if both individuals     Calculated field; requires male and female parity
                              are nulliparous; “Mixed” if parous individual paired with nulliparous          variables
                              individual
      PairRearing           “Parent” if both individuals were parent reared; “Hand” if both                Calculated field; requires male and female rearing
                              individuals were hand reared; “Mixed” if a parent reared individual is         type variables
                              paired with a hand reared individual
      AgeDiff               Difference in age (in years) between the male and female.                      Calculated field; requires male and female age
                                                                                                             variables
    Attributes of individuals
      MSBa                  Male's Studbook Number                                                         Breeding & Transfer Plans; Studbook (for non-
                                                                                                             recommended breeding); SSP coordinator for
                                                                                                             interim pairs
      FSBa                  Female's Studbook Number                                                       Breeding & Transfer Plans; Studbook (for non-
                                                                                                             recommended breeding); SSP coordinator for
                                                                                                             interim pairs
      Agea                  Individual's age at the time the breeding recommendation was made              Breeding & Transfer Plan
      Parity                Individual's parity at the time the breeding recommendation was made           Studbook
      RearingType           “Parent” if individual was parent reared; “Hand” if individual was hand        Studbook
                              reared
      Inbreeding            Inbreeding coefficient of the individual                                       Calculated in PMx or other software from
                                                                                                             studbook data
      Contraception         “Yes” if the individual has ever previously been contracepted; else “No”       RMC's contraception database
      Lineage               Can be used to identify genetic lineages (e.g., Mexican wolf)                  Studbook
      Role                  This variable can be used to identify animals with different roles, such as    Studbook
                              education or ambassador animals.
      Origin                “Captive” born or “Wild” born                                                  Studbook
      NumYrLastLitter       Number of years since the female last gave birth                               Calculated from studbook
a
Indicates data that in the future will be directly imported from PMCTrack for RVAs.
BAUMAN   ET AL.
                                                                                                                                                     |   59

compared using Akaike's information criterion with a correction for        BTPs representing a 10-year population management history (2004 to
small sample sizes (AICc—the best model has the smallest value), and       2014) that included 162 breeding recommendations. Nine records
model averaging was used to obtain a single, final model (Burnham          were excluded from the fennec fox dataset due to missing data and 22
et al., 2011; Symonds & Moussalli, 2011).                                  (14.2% of all recommended pairs) records were excluded because
    The second approach considered models containing all subsets of        foxes were not given the opportunity to breed. Records were excluded
the ten or eleven explanatory variables used for fennec fox and Mexican    from the Mexican wolf dataset due to missing data (N = 5) and an
wolf, respectively. Because of the limited sample size, no interaction     additional 223 records (31.7% of all recommended pairs) were
terms were included, resulting in 1,024 unique models for fennec fox       excluded because the recommended pair was not given the
and 2,048 unique models for Mexican wolves. Models were assessed           opportunity to breed due to logistical reasons. Logistical reasons
with AICc, and model averaging was used to generate a single model.        resulting in the recommendations not being attempted were similar
    The third approach made use of the least absolute shrinkage and        between the two species; these included shipment problems (import
selection operator (LASSO) regression technique to fit a single model      canceled, facility could not get animal transferred due to weather, etc.),
including all explanatory variables. LASSO regression optimizes the fit    or a facility refused to or could not comply with recommendations.
to the data while constraining its complexity; therefore the regression           Of the remaining 131 and 482 breeding recommendations for
coefficients for some of the explanatory variables are forced to           fennec fox and Mexican wolves respectively, only 24.4% (32 of 131) of
become zero, resulting in simpler models compared to traditional           the fennec fox pairs and 45.9% (221 of 482) Mexican wolf pairs
regression techniques, decreasing the likelihood of overfitting and        produced at least one litter within the active period. Descriptive
improving the accuracy of predictions made on new data (James,             statistics for the pair-related variables related to reproductive success
Witten, Hastie, & Tibshirani, 2014).                                       are presented in Table 2 (fennec fox) and Table 3 (Mexican wolf),
    The fourth approach used was the creation of a conditional
random forest (CRF) model (Strobl, Boulesteix, Kneib, Augustin, &
                                                                           TABLE 2 Descriptive statistics for pair-related variables’ impact on
Zeileis, 2008; Strobl, Malley, & Tutz, 2009) to generate the predictions   reproductive success in fennec fox pairs given the opportunity to
for the probability of reproductive success. The CRF model constructs      breed
a “forest” of conditional inference trees, which are grown based on                                                     Fennec      Fennec fox %
bootstrapping samples with only a subset of variables available for            Pair condition                           fox, N      successful (N)
splitting each node. For generating predictions, weighted means of all         Pairs with opportunity to breed          131         24.4% (32)
the observed responses (or decisions) from all the inference trees             Pair type
created are used. While conditional inference trees utilize significance         Sexually experienced pairs             27          59.2% (16)
tests for determining the splitting variables and split points for the
                                                                                 Carryover pairs                        32          12.0% (4)
creation of nodes within the decision trees, there are no classical
                                                                                 New pairs                              72          16.6% (12)
significances for the explanatory variables. Rather, variable importance
                                                                               Pair previous success
measures are assigned (Strobl et al., 2008; Strobl et al., 2009).
    The four approaches were compared by using the resulting models              Both in pair were previously           31          58.0% (18)
                                                                                   successful (parous)
to predict the probability of success for selected recent BTP for each
                                                                                 Both in pair were previously           62          24.0% (12)
species with known outcomes, which had not been used to fit the
                                                                                   unsuccessful (nulliparous)
models (Fennec foxes 2014 and 2015 BTPs for 37 pairs; Mexican
                                                                                 One in pair was previously             38          7.8% (3)
wolves 2016 BTP for 26 pairs). Performance was measured using the
                                                                                  successful and other was not
area under the receiver operating characteristic (ROC) curve (AUC).
                                                                               Pair rearing type
AUC has been used in a variety of settings to assess the accuracy of
                                                                                 Both in pair were hand-reared          22          45.5% (10)
models over a range of thresholds for classifying a binary outcome
(Jiménez-Valverde, 2012). Values range from 0 to 1, with an AUC of               Both in pair were parent-reared        18          33.0% (6)

0.5 expected as being the same as random and values close to 1                   Mixed rearing type pair                91          17.6% (16)
representing high accuracy in predicting realized outcomes.                    Pairs carried over beyond the original recommendation
                                                                                 Pairs carried over for 1 year          21          19.0% (4)
                                                                                 Pairs carried over for 2 year          4           0.0% (0)
3 | RE SULTS                                                                     Pair carried over for 3 year           1           0.0% (0)
                                                                               Number of litters born within the time period for successful pairsa
The AZA Mexican Wolf SSP has created annual BTPs since 1983, with
                                                                                 Successful pairs that had only 1       32          69.0% (22)
710 breeding recommendations made between 1983 and 2015 thus
                                                                                   litter
the Mexican wolf RVA dataset represents 32 years of data. In contrast,
                                                                                 Successful pairs that had 2 litters    32          28.0% (9)
the AZA Fennec Fox SSP BTPs were issued biennially from 2004 until
                                                                                 Successful pairs that had 3 litters    32          3.0% (1)
2010 and yearly thereafter when population instability necessitated
                                                                           a
more frequent planning. Therefore, for the fennec fox, we used eight       Period of the Breeding and Transfer Plan: 1–2 years.
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TABLE 3 Descriptive statistics for pair-related variables’ impact on       TABLE 4 Descriptive statistics for individual-related variables’
reproductive success in Mexican wolf pairs given the opportunity to        impact on reproductive success in fennec fox pairs given the
breed                                                                      opportunity to breed
                                      Mexican      Mexican wolf %                                                               % successful
 Pair condition                       wolf, N      successful (N)           Individual foxes                              N     (N)
 Pairs with opportunity to breed      482          45.9% (221)              Individual previous success
 Pair type                                                                    Previously unsuccessful males (any ages)    86    16.3% (14)
     Sexually experienced pairs       140          66.4% (93)                 Previously successful males (any age)       46    39.1% (18)
     Carryover pairs                  97           27.8% (27)                 Previously unsuccessful females (any        85    15.2% (13)
                                                                                age)
     New pairs                        245          41.2% (101)
                                                                              Previously successful females (any age)     47    40.4% (19)
 Pair previous success
                                                                            Age of females given the opportunity to breed
     Both in pair were previously     158          66.5% (105)
       successful (parous)                                                    0 (less than 1 year)                        8     50.0% (4)
     Both in pair were previously     239          29.3% (70)                 1                                           13    38.4% (5)
       unsuccessful (nulliparous)
                                                                              2                                           26    26.9% (7)
     One in pair was previously       85           54.1% (46)
                                                                              3                                           15    46.6% (7)
      successful and other was not
                                                                              4                                           18    27.7% (5)
 Pairs carried over beyond the original recommendation
                                                                              5                                           14    21.4% (3)
     Pairs carried over for 1year     71           33.8% (24)
                                                                              6                                           5     20.0 % (1)
     Pairs carried over for 2 year    21           16.6% (3)
                                                                              7–14                                        32    0.0% (0)
     Pair carried over for 3 year     4            0.0% (0)

whereas individual-related variables are in Tables 4 and 5 for fennec      rearing type, and the age difference of the pair, in various
fox and Mexican wolves respectively. Briefly, results for fennec foxes     combinations. The fennec fox model developed using the LASSO
show that no female over age six has been successful despite a median      regression technique was more restrictive, and only identified pair
life expectancy for this species of 11 years (www.aza.org/species-         type, female age, and male age as being significant predictors of
survival-statistics). Pairs where an experienced (parous) individual was   reproductive success and decreases as female age and male age
paired with an inexperienced (nulliparous) individual were rarely          increase.
successful; similarly pairs with individuals of different rearing types        The logistic equation produced from the LASSO regression is
were not successful. Pairs that were carried over for 1 year did have      presented in Figure 1a. When predictions for the reproductive success
some success; however, pairs carried over for 2 or 3 years did not. For    of pairs were generated by the conditional random forest, the top five
Mexican wolves, carry over pairs were successful in the first and          most important factors for the fennec fox population were pair type,
second years, although the success rate in year 2 was much lower; like     male age, female age, parity of the pair, and the age difference between
the fennec fox, no Mexican wolf carry over pairs were successful in        the male and female (Figure 2a). Consensus among the modeling
year 3. Success decreased markedly in males with inbreeding                methods evaluated illustrates that female age and experience as a pair
coefficients greater than 0.3.                                             are the factors most significantly associated with reproductive success
                                                                           in the AZA Fennec Fox SSP population: the probability of a breeding
                                                                           pair to be successful decreases as female age increases, and increases if
3.1 | Statistical prediction models
                                                                           the pair is “experienced.” Other factors identified among multiple
                                                                           methods included pair parity, male age, and the age difference
3.1.1 | Fennec fox
                                                                           between the male and female.
The models constructed using the experience-based approach for
fennec fox in order of AICc values are presented in Table 6. The
                                                                           3.1.2 | Mexican wolf
model containing female age, parity of the pair, pair type, and the
difference between female and male ages had the lowest AICc. A             For Mexican wolves, the models constructed using the experience-
model containing those same variables, plus whether the female and         based approach in order of AICc values are presented in Table 7. The
male were at the same location at the time the breeding                    model containing female age, male age, parity of the pair, pair type,
recommendation was made, performed almost as well. The null                male inbreeding coefficient, and female inbreeding coefficient had the
model containing no explanatory variables and the full model               lowest AICc and was thus the best model. The null model containing no
containing all explanatory variables performed worst. When looking         explanatory variables performed worst in this analysis. When looking
at all-subsets of the variables, there were three top performing           at all-subsets of the variables, the top performing model included male
models which included female age, parity of the pair, pair type,           age, parity of the pair, male and female inbreeding coefficients, the age
BAUMAN    ET AL.
                                                                                                                                                         |   61

TABLE 5 Descriptive statistics for individual-related variables’                         Figure 1b contains the logistic equation produced from the LASSO
impact on reproductive success in Mexican wolf pairs given the                      regression. When predictions for the reproductive success of pairs
opportunity to breed
                                                                                    were generated by the conditional random forest for the Mexican wolf
 Individual wolves                               N        % successful (N)          population, parity of the pair, male age, male and female inbreeding
 Individual previous success                                                        coefficients, and pair type were the most important factors for
   Previously unsuccessful males (any age)       268      33.3% (89)                predicting reproductive success (Figure 2b). Consensus factors among
   Previously successful males (any age)         214      61.7% (132)               the modeling methods for the Mexican wolf population suggest that
   Previously unsuccessful females (any age)     295      32.9% (97)                male age, pair parity, and male and female inbreeding coefficients are
   Previously successful females (any age)       187      66.3% (124)               the factors most significantly associated with reproductive success:
 Age of females given the opportunity to breed                                      probability of success increases if either the male or female are parous
   0 (less than 1 year)                          2        0.0% (0)                  (but highest if both are parous), and probability of success decreases as
   1                                             37       32.4% (12)                male age increases, and as male and female inbreeding coefficients
   2                                             62       48.4% (30)                increase. Additionally, pair type and prior institutional success within
   3                                             58       48.3% (28)                10 years were identified among multiple modeling methods as
   4                                             56       53.6% (30)                influencing the probability of success for Mexican wolves.
   5                                             55       43.6% (24)
   6                                             48       54.2% (26)                3.2 | Comparison of modeling strategies
   7                                             38       55.6% (21)
                                                                                    Of the four modeling strategies, LASSO regression performed best
   8                                             37       37.8% (14)
                                                                                    according to AUC (Figure 3a) for fennec foxes, but for Mexican
   9                                             39       43.6% (17)
                                                                                    wolves the conditional random forest approach was better than all
   10                                            27       48.1% (13)
                                                                                    other models (Figure 3b). For both species, all models were superior
   11                                            19       26.3% (5)
                                                                                    to random as the AUC was above 0.5 in all cases. Figure 4 shows the
   12                                            4        25.0% (1)
                                                                                    predicted probability of success for each of the 37 and 26 test pairs,
 Male inbreeding coefficients
                                                                                    respectively, for fennec foxes and Mexican wolves generated by
   0                                             88       59.0% (52)
                                                                                    each modeling strategy, overlaid upon the actual outcomes
   0.05–0.099                                    51       49.0% (25)
                                                                                    (success = 1, failure = 0) of those pairings. Predicted probabilities
   0.1–0.124                                     22       59.0% (13)
                                                                                    from the LASSO model fell within a narrower range between 0.1 and
   0.125–0.149                                   108      47.0% (51)
                                                                                    0.5 for fennec fox and between 0.21 and 0.82 for Mexican wolf. By
   0.15–0.199                                    118      45.7% (54)
                                                                                    contrast, the experience-based, all subsets models, and the
   0.2–0.299                                     70       37.1% (26)                conditional random forest generated probabilities as low as near 0
   0.3–0.499                                     33       18.2% (6)                 and as high as 0.92 for fennec and Mexican wolf.
   0.5 and above                                 19       10.5% (2)

                                                                                    4 | DISCUSSION
difference of the pair, and prior success at the institution within the last
10 years. Significant predictors of reproductive success in the Mexican             RVA statistically identifies key pair- and individual-related factors that
wolf LASSO model were parity of the pair, male age, male and female                 have affected reproductive success in a given population. This
inbreeding coefficients, and prior success at the institution.                      information can be used as a tool by program leaders to improve

TABLE 6      Comparison of ΔAICc and weights among models tested for fennec fox as part of the experience-based approach
 Variables in model                                                                                                     ΔAICc               Model weight
 Female age, pair parity, pair type, age difference                                                                     0                   0.41
 Female age, pair parity, pair type, age difference, both at breeding location                                          0.22                0.37
 Female age, pair parity, pair type, age difference, rearing type, male age                                             3.27                0.08
 Female age, pair parity, pair type, age difference, litter last 5 years, litter last 10 years                          3.77                0.06
 Female age, pair parity, pair type, age difference, litter last 5 years, litter last 10 years, rearing type,           4.84                0.04
   both at breeding location
 Female age, pair parity, pair type, age difference, litter last 5 years, litter last 10 years, year                    6.31                0.02
 Null (no explanatory variables)                                                                                        9.78                3E-3
 Female age, pair parity, pair type, age difference, litter last 5 years, litter last 10 years, rearing                 10.20               3E-3
   type, both at breeding location, year, male age
62   |                                                                                                                              BAUMAN    ET AL.

                                (a)

                (b)

FIGURE 1 The logistic equations produced from the LASSO regression, for fennec fox (a) and Mexican wolf (b), where: p(S) is the
probability of success, E = 1 if the pair is experienced, otherwise E = 0, MA is the age of the male, FA is the age of the female, YY = 1 if both
the male and female are parous, otherwise YY = 0, M = 1 if only one individual (the male OR the female) is parous, otherwise M = 0, PS = 1 if
the pair is at an institution that has successfully bred Mexican wolves in the past 10 years, otherwise PS = 0, MF is the inbreeding coefficient
of the male and FF is the inbreeding coefficient of the female

the sustainability of their populations by making better-informed          RVA dataset in the future, more subtle factors may be identified. The
breeding recommendations.                                                  LASSO statistical model clearly performed the best for fennec foxes,
         The AZA Fennec Fox RVA process revealed that female age and       and we believe it is likely to do so for other species with limited
parity are key drivers of reproductive success in this species, with       historical data. Because it limits complexity, LASSO prevents
male age, pair experience, and age difference also being effective         overfitting the data, which is probably why its predictions were
predictors. Unfortunately, the sample size was too small to estimate       better on the new pairs, as well as more moderated (i.e., LASSO gave
all but the strongest effects (female age and parity, in this case);       most new pairs a probability of success in the range 20–50%,
however, if data from the EAZA Fennec Fox ESB were added to the            whereas the other approaches tended to be all or nothing, 0% or
                                                                           100%).
                                                                                In contrast, the data set for the AZA Mexican Wolf SSP was
                                                                           much larger, providing more statistical power to estimate smaller
                                                                           effects, as male age, pair parity, male and female inbreeding
                                                                           coefficients, and pair type were all effective predictors of
                                                                           reproductive success. Additionally, the larger sample size and
                                                                           associated increase in power provides more opportunity to
                                                                           investigate possible interactive effects between factors. The
                                                                           conditional random forest technique was the only predictive model
                                                                           used that considers possible interactions between factors, which
                                                                           may explain why this technique worked best for the Mexican wolf
                                                                           population, as it was able to better fine-tune the predictions. We
                                                                           believe this approach is likely to work well for other species with
                                                                           richer historical data sets.
                                                                                Beyond the statistical modeling in R as part of the RVA process,
                                                                           the data exploration we conducted to populate the R models also
                                                                           revealed some useful information. For example, in 2010, as part of a
                                                                           new breeding strategy, proven-breeder fennec foxes were paired with
                                                                           inexperienced individuals in the hope that the experienced individual
                                                                           would “teach” the inexperienced one. Likewise, some pairs were also
                                                                           purposely selected to be comprised of individuals with different
                                                                           rearing types (hand- and parent-reared), with the hope that the more
                                                                           relaxed hand-reared individual would provide some stability for its
                                                                           mate. However, RVA results suggest that these ideas may have been
                                                                           counter-productive, so these practices were discontinued in 2017. It is
                                                                           difficult to decide how long to leave an unsuccessful pair together, so
FIGURE 2 Variable importance scores for each factor used in the
                                                                           the information that no “carryover” pair has been successful after 2 or
creation of nodes within the conditional inference trees for the
                                                                           3 years, in fennec fox and Mexican wolves, respectively, provides
fennec fox (a) and Mexican wolf (b) random forest models. Factors
with higher importance scores are the variables that are driving the       valuable information. While the finding of female age effects in both
predictions of reproductive success (or failure)                           species was potentially predictable, given the importance of this factor
BAUMAN    ET AL.
                                                                                                                                                           |   63

TABLE 7      Comparison of ΔAICc and weights among models tested for Mexican wolf as part of the experience-based approach
 Variables in model                                                                                                          ΔAICc           Model weight
 Female age, male age, pair parity, pair type, male inbreeding, female inbreeding                                            0               0.77
 Female age, male age, pair parity, pair type, age difference, litter last 5 years, litter last 10 years,                    2.42            0.23
   both at breeding location, year, male inbreeding, female inbreeding
 Female age, male age, pair parity, pair type, litter last 5 years, litter last 10 years                                     16.22           2E-4
 Female age, male age, pair parity, pair type, age difference, litter last 5 years, litter last 10 years,                    17.4            1E-4
   both at breeding location, year
 Female age, male age, pair parity, pair type, litter last 5 years, litter last 10 years, both at breeding location          17.47           1E-4
 Female age, pair parity, pair type, both at breeding location                                                               30.8            2E-7
 Pair parity, pair type, both at breeding location                                                                           40.62           1E-9
 Null (no explanatory variables)                                                                                             65.64           4E-15

in the literature for mammals generally (Cohen, 2004; Lockyear,                     years) was a surprise. This pattern, described by Daigle et al. (2015) in
Waddell, Goodrowe, & MacDonald, 2009; Ricklefs, Scheuerlein, &                      captive lions, was speculated to be related to husbandry, since wild
Cohen, 2003) and for tigers through a similar process (Saunders et al.,             lionesses commonly reproduce until 12 or 13 years of age. Further
2014) confirmation through such a rigorous process for these two                    investigation into both husbandry correlates and possible differences
species provides support that these factors should be weighted highly               in ovulatory patterns by age for fennec foxes is merited. Another
in population planning. The finding that female fennec foxes                        surprising finding was the impact of male age in Mexican wolves, which
reproduced for less than half their lifespan (no reproduction after 6               also needs further investigation. Lastly, it is interesting that, despite
                                                                                    institutional knowledge being important for reproductive success in
                                                                                    tigers and lions (Daigle et al., 2015; Saunders et al., 2014), it was not at
                                                                                    all so for Mexican wolves. This may be because the Mexican Wolf SSP
                                                                                    has emphasized consistent husbandry practices due to the reintroduc-
                                                                                    tion potential and binational nature of that SSP, so institutional
                                                                                    knowledge has not been lost.
                                                                                           We see a role for RVA in any cooperative breeding program
                                                                                    where breeding efficiency, that is, a high proportion of breeding
                                                                                    recommendations result in births, is lacking. Turnover of SSP
                                                                                    coordinators can be high, making it difficult for many program
                                                                                    leaders to have long-term insight into reproductive performance of
                                                                                    the population. With time, program leaders accumulate more
                                                                                    experience dealing with reproductive challenges and may learn
                                                                                    from research in the population they manage. Still, it is challenging
                                                                                    for even an experienced program leader to put together all of the
                                                                                    pieces that impact reproductive success in their population. They
                                                                                    may borrow insights from other species that may apply to their own
                                                                                    program or make common-sense assumptions in the absence of data,
                                                                                    as was done previously in fennecs, about factors that should
                                                                                    promote better breeding success. However, these guesses could be
                                                                                    wrong; results from the RVA provide information for making
                                                                                    evidence-based decisions about pairing and breeding strategies.
                                                                                           Reproductive success should be monitored following changes
                                                                                    implemented after an RVA, especially since this is a new process. The
                                                                                    ability to now connect the RVA data collection process to PMCTrack,
                                                                                    means that over time, RVAs can easily be run periodically to determine
                                                                                    whether the lessons learned previously still apply. In addition,
FIGURE 3 Area under the receiver operating characteristic (ROC)
                                                                                    reproduction management strategies change as SSPs evolve from a
curve (AUC) for four modeling strategies tested on (a) 37 breeding
                                                                                    “growth phase” to a “maintenance phase” at space capacity, which can
pairs from the 2014 and 2015 Fennec Fox Breeding and Transfer
Plans and (b) 26 breeding pairs from the 2016 Mexican Wolf                          alter reproductive success and lead to the need for additional
Breeding and Transfer Plan                                                          information and management considerations.
64   |                                                                                                                               BAUMAN   ET AL.

FIGURE 4 Predicted probabilities of success for (a) 37 breeding pairs from the 2014 and 2015 Fennec Fox Breeding and Transfer Plans
and (b) 26 breeding pairs from the 2016 Mexican Wolf Breeding and Transfer Plan generated by four different modeling strategies. Filled
circles represent the actual results of the breeding recommendations (1 = success, 0 = failure)

         The RVA examines factors objectively, at least for biological and   as part of the new species recovery plan (USFWS, 2017).
pair-related variables, in a relatively straightforward and consistent       Additionally, because we know that periods of contraception and
way that may identify key variables not previously thought to be             periods of non-breeding can affect fertility and reproductive health
important. No single RVA model will perfectly predict the outcomes of        (Asa et al., 2014; Penfold et al., 2014 and references therein), the
breeding pairs, and over time, as more data are added to the dataset,        AZA RMC is developing another modeling approach called Lifetime
these models will change. The RVA is not meant to make perfect               Reproductive Planning (LRP) to model the demographic and genetic
predictions, but rather to find primary drivers of reproductive success      impacts of various reproductive management scenarios (e.g., breed
or failure to advise population management in order to meet genetic          early and often, intersperse contraception with gender separation
and demographic goals.                                                       during non-breeding cycles, or breed and cull). These stochastic LRP
         While RVA results can be used solely to improve breeding            models, like PVAs, can utilize the RVA results to parameterize the
efficiency, they also can be utilized as parameters for other analyses       models. LRP should also assist program leaders by modeling best
related to population sustainability. PVAs (see Lacy, this issue and         strategies to space pregnancies that would facilitate females being
Che-Castaldo et al., this issue) are important tools in predicting how       bred at younger ages (prime fertility) while maintaining demographic
animal populations will perform over time with regard to genetics,           and genetic goals as well as target population sizes.
demographics, and persistence. An understanding of the variables                 Effective management of zoo populations has never been more
that affect the reproductive performance of individuals and breeding         important, with increasingly human-dominated landscapes and more
pairs/groups is critical to making PVAs more reliable. For example,          species becoming “conservation reliant” (Redford, Amato, & Baillie,
RVA results were used in the recent Mexican Wolf PVA conducted               2011; Scott, Goble, Haines, Wiens, & Neel, 2010). An increasing number
BAUMAN     ET AL.
                                                                                                                                                                    |   65

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ACKNOWLEDGMENTS
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The authors acknowledge the efforts of Brenda Gonzalez, Jenny                            husbandry and environmental factors for the SSP African lion Panthera
                                                                                         leo population: Examining the effects of a breeding moratorium in relation
Jankovitz, Erin Klein, and Bruna Wilhelm who assisted in the data
                                                                                         to reproductive success. International Zoo Yearbook, 49, 198–213.
gathering for these two species, as well as Peter Siminski, the AZA                  Dochtermann, N. A., & Jenkins, S. H. (2011). Developing multiple
Mexican Wolf SSP Coordinator. We also thank the anonymous                                hypotheses in behavioral ecology. Behavioral Ecology and Sociobiology,
reviewers for comments that strengthened this paper.                                     65, 37–45.
                                                                                     Faust, L. J., Theis, M., Long, S., & Shell, S. (2011). PMCTrack: A Website for
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ORCID                                                                                    grams. Lincoln Park Zoo. https://www.pmctrack.org
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Karen Bauman          http://orcid.org/0000-0001-8964-9575                               Version 2.4. Chicago, IL: Lincoln Park Zoo.
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Ashley Franklin       http://orcid.org/0000-0002-0818-5156
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Kathy Traylor-Holzer         http://orcid.org/0000-0002-3816-6706                        recommendations with PMCTrack. Zoo Biology, 38, 24–35.
David Powell        http://orcid.org/0000-0002-1462-2826                             Hoffmann, M., Hilton-Taylor, C., Angulo, A., Böhm, M., Brooks, T. M.,
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