Using prior data to improve models for reintroduced populations: A case study with North Island Saddlebacks

The expansion process of the Iberian ibex in the Sierra de Guadarrama National Park, Madrid (Spain)

In this paper we explore the usefulness of MaxEnt to predict the most suitable areas for a wildlife species, the Iberian ibex (Capra pyrenaica). For two decades (1990–2010), the species was established in a small part of the National Park Sierra de Guadarrama (Spain) and there has been a process of expansion to other areas of this protected area since 2010. However, almost two decades have elapsed since the modeling methods (MaxEnt) were proposed and no studies have tested their effectiveness using real distribution data, i.e. data from past predictions, to see if they fit the current distribution. We generated a model with presence– only data from 2007 and verified accuracy from 2017 data concerning real presence. Our results show a relationship between models and the species' current presence. The generated model can be useful to define the preferred locations of the species. We detected several differences between males and females of the species. This work not only shows the importance of selecting climatic and ecological variables for the construction of models but also indicates that they must be adjusted, at least for some species, to each sex and period of the year.

Nesting, brood rearing, and summer habitat selection by translocated greater sage-grouse in North Dakota, USA

Human enterprise has led to large-scale changes in landscapes and altered wildlife population distribution and abundance, necessitating efficient and effective conservation strategies for impacted species. Greater sage-grouse (Centrocercus urophasianus; hereafter sage-grouse) are a widespread sagebrush (Artemisia spp.) obligate species that has experienced population declines since the mid-1900s resulting from habitat loss and expansion of anthropogenic features into sagebrush ecosystems. Habitat loss is especially evident in North Dakota, USA, on the northeastern fringe of sage-grouse' distribution, where a remnant population remains despite recent development of energy-related infrastructure. Resource managers in this region have determined a need to augment sage-grouse populations using translocation techniques that can be important management tools for countering species decline from range contraction. Although translocations are a common tool for wildlife management, very little research has evaluated habitat following translocation, to track individual behaviors such as habitat selection and fidelity to the release site, which can help inform habitat requirements to guide selection of future release sites. We provide an example where locations from previously released radio-marked sage-grouse are used in a resource selection function framework to evaluate habitat selection following translocation and identify areas of seasonal habitat to inform habitat management and potential restoration needs. We also evaluated possible changes in seasonal habitat since the late 1980s using spatial data provided by the Rangeland Analysis Platform coupled with resource selection modeling results. Our results serve as critical baseline information for habitat used by translocated individuals across life stages in this study area, and will inform future evaluations of population performance and potential for long-term recovery.

Predicting reintroduction outcomes for highly vulnerable species that do not currently coexist with their key threats

Predicting reintroduction outcomes before populations are released is inherently challenging. It becomes even more difficult when the species being considered for reintroduction no longer coexists with the key threats limiting its distribution. However, data from other species facing the same threats can be used to make predictions under these circumstances. We used an integrated Bayesian modeling approach to predict growth of a reintroduced population at a range of predator densities when no data are available for the species in the presence of that predator. North Island Saddlebacks (Philesturnus rufusater) were extirpated from mainland New Zealand by exotic mammalian predators, particularly ship rats (black rats [Rattus rattus]) but are now being considered for reintroduction to sites with intensive predator control. We initially modeled data from previous saddleback reintroductions to predator-free sites to predict population growth at a new predator-free site while accounting for random variation in vital rates among sites. We then predicted population growth at different rat-tracking rates (an index of rat density) by incorporating a previously modeled relationship between rat-tracking and vital rates of another predator-sensitive species, the North Island Robin (Petroica longipes), and accounted for greater vulnerability of saddlebacks to rat predation based on information on historical declines of both species. The results allowed population growth to be predicted as a function of management effort while accounting for uncertainty, which means formal decision analysis could be used to decide whether to proceed with a reintroduction. Similar approaches could be applied to other situations where data on the species of interest are limited and provide an alternative to decision making based solely on expert judgment.

Combining data-derived priors with postrelease monitoring data to predict persistence of reintroduced populations

Monitoring is an essential part of reintroduction programs, but many years of data may be needed to obtain reliable population projections. This duration can potentially be reduced by incorporating prior information on expected vital rates (survival and fecundity) when making inferences from monitoring data. The prior distributions for these parameters can be derived from data for previous reintroductions, but it is important to account for site-to-site variation. We evaluated whether such informative priors improved our ability to estimate the finite rate of increase (λ) of the North Island robin (Petroica longipes) population reintroduced to Tawharanui Regional Park, New Zealand. We assessed how precision improved with each year of postrelease data added, comparing models that used informative or uninformative priors. The population grew from about 22 to 80 individuals from 2007 to 2016, with λ estimated to be 1.23 if density dependence was included in the model and 1.13 otherwise. Under either model, 7 years of data were required before the lower 95% credible limit for λ was > 1, giving confidence that the population would persist. The informative priors did not reduce this requirement. Data-derived priors are useful before reintroduction because they allow λ to be estimated in advance. However, in the case examined here, the value of the priors was overwhelmed once site-specific monitoring data became available. The Bayesian method presented is logical for reintroduced populations. It allows prior information (used to inform prerelease decisions) to be integrated with postrelease monitoring. This makes full use of the data for ongoing management decisions. However, if the priors properly account for site-to-site variation, they may have little predictive value compared with the site-specific data. This value will depend on the degree of site-to-site variation as well as the quality of the data.

Effects of age and sex ratios on offspring recruitment rates in translocated black rhinoceros

Success of animal translocations depends on improving postrelease demographic rates toward establishment and subsequent growth of released populations. Short-term metrics for evaluating translocation success and its drivers, like postrelease survival and fecundity, are unlikely to represent longer-term outcomes. We used information theory to investigate 25 years of data on black rhinoceros (Diceros bicornis) translocations. We used the offspring recruitment rate (ORR) of translocated females-a metric integrating survival, fecundity, and offspring recruitment at sexual maturity-to detect determinants of success. Our unambiguously best model (AICω = 0.986) predicted that ORR increases with female age at release as a function of lower postrelease adult rhinoceros sex ratio (males:females). Delay of first postrelease reproduction and failure of some females to recruit any calves to sexual maturity most influenced the pattern of ORRs, and the leading causes of recruitment failure were postrelease female death (23% of all females) and failure to calve (24% of surviving females). We recommend translocating older females (≥6 years old) because they do not exhibit the reproductive delay and low ORRs of juveniles (<4 years old) or the higher rates of recruitment failure of juveniles and young adults (4-5.9 years old). Where translocation of juveniles is necessary, they should be released into female-biased populations, where they have higher ORRs. Our study offers the unique advantage of a long-term analysis across a large number of replicate populations-a science-by-management experiment as a proxy for a manipulative experiment, and a rare opportunity, particularly for a large, critically endangered taxon such as the black rhinoceros. Our findings differ from previous recommendations, reinforce the importance of long-term data sets and comprehensive metrics of translocation success, and suggest attention be shifted from ecological to social constraints on population growth and species recovery, particularly when translocating species with polygynous breeding systems.

A new parameterization for integrated population models to document amphibian reintroductions

Managers are increasingly implementing reintroduction programs as part of a global effort to alleviate amphibian declines. Given uncertainty in factors affecting populations and a need to make recurring decisions to achieve objectives, adaptive management is a useful component of these efforts. A major impediment to the estimation of demographic rates often used to parameterize and refine decision-support models is that life-stage-specific monitoring data are frequently sparse for amphibians. We developed a new parameterization for integrated population models to match the ecology of amphibians and capitalize on relatively inexpensive monitoring data to document amphibian reintroductions. We evaluate the capability of this model by fitting it to Oregon spotted frog (Rana pretiosa) monitoring data collected from 2007 to 2014 following their reintroduction within the Klamath Basin, Oregon, USA. The number of egg masses encountered and the estimated adult and metamorph abundances generally increased following reintroduction. We found that survival probability from egg to metamorph ranged from 0.01 in 2008 to 0.09 in 2009 and was not related to minimum spring temperatures, metamorph survival probability ranged from 0.13 in 2010-2011 to 0.86 in 2012-2013 and was positively related to mean monthly temperatures (logit-scale slope = 2.37), adult survival probability was lower for founders (0.40) than individuals recruited after reintroduction (0.56), and the mean number of egg masses per adult female was 0.74. Our study is the first to test hypotheses concerning Oregon spotted frog egg-to-metamorph and metamorph-to-adult transition probabilities in the wild and document their response at multiple life stages following reintroduction. Furthermore, we provide an example to illustrate how the structure of our integrated population model serves as a useful foundation for amphibian decision-support models within adaptive management programs. The integration of multiple, but related, data sets has an advantage of being able to estimate complex ecological relationships across multiple life stages, offering a modeling framework that accommodates uncertainty, enforces parsimony, and ensures all model parameters can be confronted with monitoring data.

Use of Simulation Modeling to Evaluate Management Strategies for Reintroduced Riparian Brush Rabbits in California

The riparian brush rabbit Sylvilagus bachmani riparius is restricted to areas of dense cover along rivers and tributaries in the Central Valley of California, USA, and is considered endangered under the U.S. Endangered Species Act. An approved recovery plan for this subspecies recommended establishment of three additional self-sustaining populations within its historical range. Concurrent with habitat restoration efforts that included revegetation of levees and provision of flood refugia, we reintroduced 325 captive-bred individuals to the San Joaquin River National Wildlife Refuge between July 2002 and July 2005, and monitored their survival with radiotelemetry. Using available survival estimates and estimated reproductive parameters, we developed a population viability analysis model to determine the risk of extinction of the reintroduced population under a series of alternate scenarios including different release strategies. All model scenarios resulted in high probabilities of extinction over 20 y in the absence of either ongoing supplementations or significant improvements to vital rates. Extinction risks over 20 y appeared independent of initial release strategies. The risk of extinction remained high (&gt;99%) even when the initial founder population was supplemented with captive-bred brush rabbits for up to 10 y. Supplementing the population annually for the entire 20-y period would be required for the population to persist given current estimates of vital rates. These results suggest that the reintroduced population is not self-sustaining and continued releases will not provide the anticipated long-term benefits. Additionally, our understanding of the integral components of habitat and potential limiting factors should be refined to address their influence on demographics and the cause of brush rabbit declines at the release site in a comprehensive way. These results underscore the importance of viability analyses and developing testable hypotheses about potential limiting factors early in reintroduction efforts to more efficiently guide data-gathering and monitoring criteria, identify data deficiencies, and refine reintroduction techniques in the early stages of management.