Using Modeling to Improve Monitoring of Structured Populations: Are We Collecting the Right Data?

Abstract:  Population monitoring is central to most demographic studies and conservation efforts, but it may not always be directed at the most appropriate life stage. We used stochastic simulation modeling to evaluate the effectiveness of a monitoring program for a well-studied population of Eastern Imperial Eagles ( Aquila heliaca ) in Kazakhstan. Specifically, we asked whether the most appropriate data were being collected to understand system state and population dynamics. Our models were parameterized with data collected over the course of 25 years of study of this population. We used the models to conduct simulation experiments to evaluate relationships between monitored or potentially monitored parameters and the demographic variables of interest—population size ( N ) and population growth (λ). Static analyses showed that traditional territory-based monitoring was a poor indicator of eagle population size and growth and that monitoring survivorship would provide more information about these parameters. Nevertheless, these same traditionally monitored territory-based parameters had greater power to detect long-term changes in population size than did survivorship or population structure. Regardless of the taxa considered, threats can have immediate impacts on population size and growth or longer-term impacts on population dynamics. Prudently designed monitoring programs for any species will detect the demographic effects of both types of threats.     

Spatially Explicit Power Analyses for Occupancy‐Based Monitoring of Wolverine in the U.S. Rocky Mountains

Conservation scientists and resource managers often have to design monitoring programs for species that are rare or patchily distributed across large landscapes. Such programs are frequently expensive and seldom can be conducted by one entity. It is essential that a prospective power analysis be undertaken to ensure stated monitoring goals are feasible. We developed a spatially based simulation program that accounts for natural history, habitat use, and sampling scheme to investigate the power of monitoring protocols to detect trends in population abundance over time with occupancy‐based methods. We analyzed monitoring schemes with different sampling efforts for wolverine (Gulo gulo) populations in 2 areas of the U.S. Rocky Mountains. The relation between occupancy and abundance was nonlinear and depended on landscape, population size, and movement parameters. With current estimates for population size and detection probability in the northern U.S. Rockies, most sampling schemes were only able to detect large declines in abundance in the simulations (i.e., 50% decline over 10 years). For small populations reestablishing in the Southern Rockies, occupancy‐based methods had enough power to detect population trends only when populations were increasing dramatically (e.g., doubling or tripling in 10 years), regardless of sampling effort. In general, increasing the number of cells sampled or the per‐visit detection probability had a much greater effect on power than the number of visits conducted during a survey. Although our results are specific to wolverines, this approach could easily be adapted to other territorial species. Poder de Análisis Espacialmente Explícito para el Monitoreo Basado en Ocupación del Glotón (Gulo gulo) en las Montañas Rocallosas de Estados Unidos     

Actual and Potential Use of Population Viability Analyses in Recovery of Plant Species Listed under the U.S. Endangered Species Act

Use of population viability analyses (PVAs) in endangered species recovery planning has been met with both support and criticism. Previous reviews promote use of PVA for setting scientifically based, measurable, and objective recovery criteria and recommend improvements to increase the framework's utility. However, others have questioned the value of PVA models for setting recovery criteria and assert that PVAs are more appropriate for understanding relative trade‐offs between alternative management actions. We reviewed 258 final recovery plans for 642 plants listed under the U.S. Endangered Species Act to determine the number of plans that used or recommended PVA in recovery planning. We also reviewed 223 publications that describe plant PVAs to assess how these models were designed and whether those designs reflected previous recommendations for improvement of PVAs. Twenty‐four percent of listed species had recovery plans that used or recommended PVA. In publications, the typical model was a matrix population model parameterized with ≤5 years of demographic data that did not consider stochasticity, genetics, density dependence, seed banks, vegetative reproduction, dormancy, threats, or management strategies. Population growth rates for different populations of the same species or for the same population at different points in time were often statistically different or varied by >10%. Therefore, PVAs parameterized with underlying vital rates that vary to this degree may not accurately predict recovery objectives across a species’ entire distribution or over longer time scales. We assert that PVA, although an important tool as part of an adaptive‐management program, can help to determine quantitative recovery criteria only if more long‐term data sets that capture spatiotemporal variability in vital rates become available. Lacking this, there is a strong need for viable and comprehensive methods for determining quantitative, science‐based recovery criteria for endangered species with minimal data availability. Uso Actual y Potencial del Análisis de Viabilidad Poblacional para la Recuperación de Especies de Plantas Enlistadas en el Acta de Especies En Peligro de E.U.A     

Maximizing Offspring Production While Maintaining Genetic Diversity in Supplemental Breeding Programs of Highly Fecund Managed Species

Abstract:  Supplemental breeding is an intensive population management strategy wherein adults are captured from nature and spawned in controlled settings, and the resulting offspring are later released into the wild. To be effective, supplemental breeding programs require crossing strategies that maximize offspring production while maintaining genetic diversity within each supplemental year class. We used computer simulations to assess the efficacy of different mating designs to jointly maximize offspring production and maintain high levels of genetic diversity (as measured by the effective population size) under a variety of biological conditions particularly relevant to species with high fecundity and external fertilization, such as many fishes. We investigated four basic supplemental breeding designs involving either monogamous pairings or complete factorial designs (in which every female is mated to every male and vice versa), each with or without the added stipulation that all breeders contribute equally to the total reproductive output. In general, complete factorial designs that did not equalize parental contributions came closest to the goal of maximizing offspring production while still maintaining relatively large effective population sizes. Next, we estimated the effective population size of 10 different supplemental year classes within the breeding program of the robust redhorse (Moxostoma robustum). Two year classes failed to produce progeny, whereas successful year classes used partial factorial designs to realize effective sizes ranging from 2 to 26 individuals. On average, a complete factorial design could increase the effective size of each robust redhorse supplemental year class by 19%.     

Longitudinal monitoring of neutral and adaptive genomic diversity in a reintroduction

Restoration programs in the form of ex-situ breeding combined with reintroductions are becoming critical to counteract demographic declines and species losses. Such programs are increasingly using genetic management to improve conservation outcomes. However, the lack of long-term monitoring of genetic indicators following reintroduction prevents assessments of the trajectory and persistence of reintroduced populations. We carried out an extensive monitoring program in the wild for a threatened small-bodied fish (southern pygmy perch, Nannoperca australis) to assess the long-term genomic effects of its captive breeding and reintroduction. The species was rescued prior to its extirpation from the terminal lakes of Australia's Murray-Darling Basin, and then used for genetically informed captive breeding and reintroductions. Subsequent annual or biannual monitoring of abundance, fitness, and occupancy over a period of 11 years, combined with postreintroduction genetic sampling, revealed survival and recruitment of reintroduced fish. Genomic analyses based on data from the original wild rescued, captive born, and reintroduced cohorts revealed low inbreeding and strong maintenance of neutral and candidate adaptive genomic diversity across multiple generations. An increasing trend in the effective population size of the reintroduced population was consistent with field monitoring data in demonstrating successful re-establishment of the species. This provides a rare empirical example that the adaptive potential of a locally extinct population can be maintained during genetically informed ex-situ conservation breeding and reintroduction into the wild. Strategies to improve biodiversity restoration via ex-situ conservation should include genetic-based captive breeding and longitudinal monitoring of standing genomic variation in reintroduced populations.     

Accounting for Complementarity to Maximize Monitoring Power for Species Management

To choose among conservation actions that may benefit many species, managers need to monitor the consequences of those actions. Decisions about which species to monitor from a suite of different species being managed are hindered by natural variability in populations and uncertainty in several factors: the ability of the monitoring to detect a change, the likelihood of the management action being successful for a species, and how representative species are of one another. However, the literature provides little guidance about how to account for these uncertainties when deciding which species to monitor to determine whether the management actions are delivering outcomes. We devised an approach that applies decision science and selects the best complementary suite of species to monitor to meet specific conservation objectives. We created an index for indicator selection that accounts for the likelihood of successfully detecting a real trend due to a management action and whether that signal provides information about other species. We illustrated the benefit of our approach by analyzing a monitoring program for invasive predator management aimed at recovering 14 native Australian mammals of conservation concern. Our method selected the species that provided more monitoring power at lower cost relative to the current strategy and traditional approaches that consider only a subset of the important considerations. Our benefit function accounted for natural variability in species growth rates, uncertainty in the responses of species to the prescribed action, and how well species represent others. Monitoring programs that ignore uncertainty, likelihood of detecting change, and complementarity between species will be more costly and less efficient and may waste funding that could otherwise be used for management. Contabilización de la Complementariedad para Maximizar el Poder de Monitoreo para el Manejo de Especies     

A comparative approach to assess drivers of success in mammalian conservation recovery programs

The outcomes of species recovery programs have been mixed; high‐profile population recoveries contrast with species‐level extinctions. Each conservation intervention has its own challenges, but to inform more effective management it is imperative to assess whether correlates of wider recovery program success or failure can be identified. To contribute to evidence‐based improvement of future conservation strategies, we conducted a global quantitative analysis of 48 mammalian recovery programs. We reviewed available scientific literature and conducted semistructured interviews with conservation professionals involved in different recovery programs to investigate ecological, management, and political factors associated with population recoveries or declines. Identifying and removing threats was significantly associated with increasing population trend and decreasing conservation dependence, emphasizing that populations are likely to continue to be compromised in the absence of effective threat mitigation and supporting the need for threat monitoring and adaptive management in response to new and potential threats. Lack of habitat and small population size were cited as limiting factors in 56% and 42% of recovery programs, respectively, and both were statistically associated with increased longer term dependence on conservation intervention, demonstrating the importance of increasing population numbers quickly and restoring and protecting habitat. Poor stakeholder coordination and management were also regularly cited by respondents as key weaknesses in recovery programs, indicating the importance of effective leadership and shared goals and management plans. Project outcomes were not influenced by biological or ecological variables such as body mass or habitat, which suggests that these insights into correlates of conservation success and failure are likely to be generalizable across mammals.     

Using Population Viability Criteria to Assess Strategies to Minimize Disease Threats for an Endangered Carnivore

Outbreaks of infectious disease represent serious threats to the viability of many vertebrate populations, but few studies have included quantitative evaluations of alternative approaches to the management of disease. The most prevalent management approach is monitoring for and rapid response to an epizootic. An alternative is vaccination of a subset of the free‐living population (i.e., a “vaccinated core”) such that some individuals are partially or fully immune in the event of an epizootic. We developed a simulation model describing epizootic dynamics, which we then embedded in a demographic simulation to assess these alternative approaches to managing rabies epizootics in the island fox (Urocyon littoralis), a species composed of only 6 small populations on the California Channel Islands. Although the monitor and respond approach was superior to the vaccinated‐core approach for some transmission models and parameter values, this type of reactive management did not protect the population from rabies under many disease‐transmission assumptions. In contrast, a logistically feasible program of prophylactic vaccination for part of the wild population yielded low extinction probabilities across all likely disease‐transmission scenarios, even with recurrent disease introductions. Our use of a single metric of successful management—probability of extreme endangerment (i.e., quasi extinction)—to compare very different management approaches allowed an objective assessment of alternative strategies for controlling the threats posed by infectious disease outbreaks. Utilización de Criterios de Viabilidad Poblacional para Evaluar Estrategias para Minimizar Amenazas de Enfermedades para un Carnívoro en Peligro     

Importance of Well-Designed Monitoring Programs for the Conservation of Endangered Species: Case Study of the Snail Kite

Abstract:  Monitoring natural populations is often a necessary step to establish the conservation status of species and to help improve management decisions. Nevertheless, many monitoring programs do not effectively address primary sources of variability in monitoring data, which ultimately may limit the utility of monitoring in identifying declines and improving management. To illustrate the importance of taking into account detectability and spatial variation, we used a recently proposed estimator of abundance (superpopulation estimator) to estimate population size of and number of young produced by the Snail Kite ( Rostrhamus sociabilis plumbeus ) in Florida. During the last decade, primary recovery targets set by the U.S. Fish and Wildlife Service for the Snail Kite that were based on deficient monitoring programs (i.e., uncorrected counts) were close to being met (by simply increasing search effort during count surveys). During that same period, the Snail Kite population declined dramatically (by 55% from 1997 to 2005) and the number of young decreased by 70% between 1992–1998 and 1999–2005. Our results provide a strong practical case in favor of the argument that investing a sufficient amount of time and resources into designing and implementing monitoring programs that carefully address detectability and spatial variation is critical for the conservation of endangered species.     

Detecting Population Declines over Large Areas with Presence-Absence, Time-to-Encounter, and Count Survey Methods

Abstract:  Ecologists often discount presence-absence surveys as a poor way to gain insight into population dynamics, in part because these surveys are not amenable to many standard statistical tests. Still, presence-absence surveys are sometimes the only feasible alternative for monitoring large areas when funds are limited, especially for sparse or difficult-to-detect species. I undertook a detailed simulation study to compare the power of presence-absence, count, and time-to-encounter surveys to detect regional declines in a population. I used a modeling approach that simulates both population numbers and the monitoring process, accounting for observation and other measurement errors. In gauging the efficacy of presence-absence surveys versus other approaches, I varied the number of survey sites, the spatial variation in encounter rate, the mean encounter rate, and the type of population loss. My results showed that presence-absence data can be as or more powerful than count data in many cases. Quantitative guidelines for choosing between presence-absence surveys and count surveys depend on the biological and logistical constraints governing a conservation monitoring situation. Generally, presence-absence surveys work best when there is little variability in abundance among the survey sites, the organism is rare, and the species is difficult to detect so that the time spent getting to each survey site is less than or equal to the time spent surveying each site. Count surveys work best otherwise. I present a case study with count data on the Northern Flicker ( Colaptes auratus ) from the North American Breeding Bird Survey to illustrate how the method might be used with field-survey data. The case study demonstrates that a count survey would be the most cost-effective design but would entail reduction in the number of sites. If this site reduction is not desirable, a presence-absence survey would be the most cost-effective survey.     

Multimethod,multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves

In many cases, the first step in large‐carnivore management is to obtain objective, reliable, and cost‐effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical‐site‐occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost‐effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well‐coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population‐parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters.     

Conservation and monitoring of a persecuted African lion population by Maasai warriors

Although Africa has many threatened species and biological hot spots, there are few citizen science schemes, particularly in rural communities, and there has been limited evaluation of existing programs. We engaged traditional Maasai warriors (pastoralist men aged 15 to 35) in community‐based conservation and demographic monitoring of a persecuted African lion (Panthera leo) population. Through direct engagement, we investigated whether a citizen science approach employing local warriors, who had no formal education, could produce reliable data on the demographics, predation, and movements of a species with which their communities have been in conflict for generations. Warriors were given benefits such as literacy training and skill enhancement and engaged in the monitoring of the lions. The trained warriors reported on lion sign across an area nearly 4000 km². Scientists worked together with the warriors to verify their reports and gather observations on the lion population. Using the verified reports and collected observations, we examined our scientific knowledge relative to the lion population preceding and during the citizen science program. Our observations showed that data quality and quantity improved with the involvement and training of the participants. Furthermore, because they engaged in conservation and gained personal benefits, the participants came to appreciate a species that was traditionally their foe. We believe engaging other local communities in biodiversity conservation and monitoring may be an effective conservation approach in rural Africa.     

The role of digital data entry in participatory environmental monitoring

Many argue that monitoring conducted exclusively by scientists is insufficient to address ongoing environmental challenges. One solution entails the use of mobile digital devices in participatory monitoring (PM) programs. But how digital data entry affects programs with varying levels of stakeholder participation, from nonscientists collecting field data to nonscientists administering every step of a monitoring program, remains unclear. We reviewed the successes, in terms of management interventions and sustainability, of 107 monitoring programs described in the literature (hereafter programs) and compared these with case studies from our PM experiences in Australia, Canada, Ethiopia, Ghana, Greenland, and Vietnam (hereafter cases). Our literature review showed that participatory programs were less likely to use digital devices, and 2 of our 3 more participatory cases were also slow to adopt digital data entry. Programs that were participatory and used digital devices were more likely to report management actions, which was consistent with cases in Ethiopia, Greenland, and Australia. Programs engaging volunteers were more frequently reported as ongoing, but those involving digital data entry were less often sustained when data collectors were volunteers. For the Vietnamese and Canadian cases, sustainability was undermined by a mismatch in stakeholder objectives. In the Ghanaian case, complex field protocols diminished monitoring sustainability. Innovative technologies attract interest, but the foundation of effective participatory adaptive monitoring depends more on collaboratively defined questions, objectives, conceptual models, and monitoring approaches. When this foundation is built through effective partnerships, digital data entry can enable the collection of more data of higher quality. Without this foundation, or when implemented ineffectively or unnecessarily, digital data entry can be an additional expense that distracts from core monitoring objectives and undermines project sustainability. The appropriate role of digital data entry in PM likely depends more on the context in which it is used and less on the technology itself.     

Comparison of Two Types of Metapopulation Models in Real and Artificial Landscapes

Abstract: Application of metapopulation models is becoming increasingly widespread in the conservation of species in fragmented landscapes. We provide one of the first detailed comparisons of two of the most common modeling techniques, incidence function models and stage-based matrix models, and test their accuracy in predicting patch occupancy for a real metapopulation. We measured patch occupancies and demographic rates for regional populations of the Florida scrub lizard (   Sceloporus woodi ) and compared the observed occupancies with those predicted by each model. Both modeling strategies predicted patch occupancies with good accuracy ( 77–80%) and gave similar results when we compared hypothetical management scenarios involving removal of key habitat patches and degradation of habitat quality. To compare the two modeling approaches over a broader set of conditions, we simulated metapopulation dynamics for 150 artificial landscapes composed of equal-sized patches (2–1024 ha) spaced at equal distances (50–750 m). Differences in predicted patch occupancy were small to moderate (<20%) for about 74% of all simulations, but 22% of the landscapes had differences openface> 50%. Incidence function models and stage-based matrix models differ in their approaches, assumptions, and requirements for empirical data, and our findings provide evidence that the two models can produce different results. We encourage researchers to use both techniques and further examine potential differences in model output. The feasibility of obtaining data for population modeling varies widely among species and limits the modeling approaches appropriate for each species. Understanding different modeling approaches will become increasingly important as conservation programs undertake the challenge of managing for multiple species in a landscape context.     

Efficient species-level monitoring at the landscape scale

Monitoring the population trends of multiple animal species at a landscape scale is prohibitively expensive. However, advances in survey design, statistical methods, and the ability to estimate species presence on the basis of detection-nondetection data have greatly increased the feasibility of species-level monitoring. For example, recent advances in monitoring make use of detection-nondetection data that are relatively inexpensive to acquire, historical survey data, and new techniques in genetic evaluation. The ability to use indirect measures of presence for some species greatly increases monitoring efficiency and reduces survey costs. After adjusting for false absences, the proportion of sample units in a landscape where a species is detected (occupancy) is a logical state variable to monitor. Occupancy monitoring can be based on real-time observation of a species at a survey site or on evidence that the species was at the survey location sometime in the recent past. Temporal and spatial patterns in occupancy data are related to changes in animal abundance and provide insights into the probability of a species' persistence. However, even with the efficiencies gained when occupancy is the monitored state variable, the task of species-level monitoring remains daunting due to the large number of species. We propose that a small number of species be monitored on the basis of specific management objectives, their functional role in an ecosystem, their sensitivity to environmental changes likely to occur in the area, or their conservation importance.     

Genetic and Demographic Threats to the Black Rhinoceros Population in the Ngorongoro Crater

A resident population of 13 black rhinoceros ( Diceros bicornis ) persist in Ngorongoro Crater, Tanzania. The effective population size ( N _e ) may be as few as 5 animals. Projected growth for this population suggests that the effective population size will remain small for the near future, threatening this Iocal population with extinction due to the stochastic factors associated with small population size. A summary of historic and recent demographic data for this population reveals a population crash during the period of heavy poaching that affected this species throughout its range. Although poaching of this species has been brought under control the population remains small. These data and models of projected population growth argue for consideration of more-intensive management within the framework of the small population paradigm. This case is an example of applied conservation resulting from this paradigm used in conjunction with rather than competing with the declining population paradigm. We identify additional monitoring, particularly of density-dependent behaviors, that will be necessary for designing a successful management program. Finally, the use of molecular markers for developing an accurate pedigree for this population is suggested in order to maintain a genetically healthy population. These strategies have broad applicability to black rhinoceros conservation throughout Africa.     

A framework for evaluating and designing citizen science programs for natural resources monitoring

We present a framework of resource characteristics critical to the design and assessment of citizen science programs that monitor natural resources. To develop the framework we reviewed 52 citizen science programs that monitored a wide range of resources and provided insights into what resource characteristics are most conducive to developing citizen science programs and how resource characteristics may constrain the use or growth of these programs. We focused on 4 types of resource characteristics: biophysical and geographical, management and monitoring, public awareness and knowledge, and social and cultural characteristics. We applied the framework to 2 programs, the Tucson (U.S.A.) Bird Count and the Maui (U.S.A.) Great Whale Count. We found that resource characteristics such as accessibility, diverse institutional involvement in resource management, and social or cultural importance of the resource affected program endurance and success. However, the relative influence of each characteristic was in turn affected by goals of the citizen science programs. Although the goals of public engagement and education sometimes complimented the goal of collecting reliable data, in many cases trade‐offs must be made between these 2 goals. Program goals and priorities ultimately dictate the design of citizen science programs, but for a program to endure and successfully meet its goals, program managers must consider the diverse ways that the nature of the resource being monitored influences public participation in monitoring.     

Integrated Monitoring and Information Systems for Managing Aquatic Invasive Species in a Changing Climate

Abstract:  Changes in temperature, precipitation, and other climatic drivers and sea-level rise will affect populations of existing native and non-native aquatic species and the vulnerability of aquatic environments to new invasions. Monitoring surveys provide the foundation for assessing the combined effects of climate change and invasions by providing baseline biotic and environmental conditions, although the utility of a survey depends on whether the results are quantitative or qualitative, and other design considerations. The results from a variety of monitoring programs in the United States are available in integrated biological information systems, although many include only non-native species, not native species. Besides including natives, we suggest these systems could be improved through the development of standardized methods that capture habitat and physiological requirements and link regional and national biological databases into distributed Web portals that allow drawing information from multiple sources. Combining the outputs from these biological information systems with environmental data would allow the development of ecological-niche models that predict the potential distribution or abundance of native and non-native species on the basis of current environmental conditions. Environmental projections from climate models can be used in these niche models to project changes in species distributions or abundances under altered climatic conditions and to identify potential high-risk invaders. There are, however, a number of challenges, such as uncertainties associated with projections from climate and niche models and difficulty in integrating data with different temporal and spatial granularity. Even with these uncertainties, integration of biological and environmental information systems, niche models, and climate projections would improve management of aquatic ecosystems under the dual threats of biotic invasions and climate change.     

Effects of life history and reproduction on recruitment time lags in reintroductions of rare plants

Reintroductions are important components of conservation and recovery programs for rare plant species, but their long-term success rates are poorly understood. Previous reviews of plant reintroductions focused on short-term (e.g., ≤3 years) survival and flowering of founder individuals rather than on benchmarks of intergenerational persistence, such as seedling recruitment. However, short-term metrics may obscure outcomes because the unique demographic properties of reintroductions, including small size and unstable stage structure, could create lags in population growth. We used time-to-event analysis on a database of unusually well-monitored and long-term (4–28 years) reintroductions of 27 rare plant species to test whether life-history traits and population characteristics of reintroductions create time-lagged responses in seedling recruitment (i.e., recruitment time lags [RTLs]), an important benchmark of success and indicator of persistence in reintroduced populations. Recruitment time lags were highly variable among reintroductions, ranging from <1 to 17 years after installation. Recruitment patterns matched predictions from life-history theory with short-lived species (fast species) exhibiting consistently shorter and less variable RTLs than long-lived species (slow species). Long RTLs occurred in long-lived herbs, especially in grasslands, whereas short RTLs occurred in short-lived subtropical woody plants and annual herbs. Across plant life histories, as reproductive adult abundance increased, RTLs decreased. Highly variable RTLs were observed in species with multiple reintroduction events, suggesting local processes are just as important as life-history strategy in determining reintroduction outcomes. Time lags in restoration outcomes highlight the need to scale success benchmarks in reintroduction monitoring programs with plant life-history strategies and the unique demographic properties of restored populations. Drawing conclusions on the long-term success of plant reintroduction programs is premature given that demographic processes in species with slow life-histories take decades to unfold.