Abundance of the New Zealand subantarctic southern right whale population estimated from photo-identification and genotype mark-recapture

The abundance of New Zealand subantarctic southern right whales (Eubalaena australis) was estimated for the first time using mark-recapture methods based on photo-identification and microsatellite genotyping (13 loci). Individual identification photographs of 383 whales and microsatellite genotypes of 235 whales were collected during annual austral winter field surveys from 1995 to 1998. Given the 4-year survey period and lack of geographic and demographic closure, we estimated super-population abundance using the POPAN Jolly-Seber model implemented in the software programme MARK. Models with constant survivorship but time-varying capture probability and probability of entry into the population were the most suitable due to the survey design. This provided estimates of abundance in 1998 of 908 non-calf whales (95% C.L. = 755, 1,123) for the photo-identification and 910 non-calf whales (95% C.L. = 641, 1,354) for the microsatellite genotype data sets. The current estimate of 900 whales may represent less than 5% of the pre-whaling abundance in New Zealand waters.     

Chilean Blue Whales as a Case Study to Illustrate Methods to Estimate Abundance and Evaluate Conservation Status of Rare Species

Abstract: Often abundance of rare species cannot be estimated with conventional design‐based methods, so we illustrate with a population of blue whales (Balaenoptera musculus) a spatial model‐based method to estimate abundance. We analyzed data from line‐transect surveys of blue whales off the coast of Chile, where the population was hunted to low levels. Field protocols allowed deviation from planned track lines to collect identification photographs and tissue samples for genetic analyses, which resulted in an ad hoc sampling design with increased effort in areas of higher densities. Thus, we used spatial modeling methods to estimate abundance. Spatial models are increasingly being used to analyze data from surveys of marine, aquatic, and terrestrial species, but estimation of uncertainty from such models is often problematic. We developed a new, broadly applicable variance estimator that showed there were likely 303 whales (95% CI 176–625) in the study area. The survey did not span the whales' entire range, so this is a minimum estimate. We estimated current minimum abundance relative to pre‐exploitation abundance (i.e., status) with a population dynamics model that incorporated our minimum abundance estimate, likely population growth rates from a meta‐analysis of rates of increase in large baleen whales, and two alternative assumptions about historic catches. From this model, we estimated that the population was at a minimum of 9.5% (95% CI 4.9–18.0%) of pre‐exploitation levels in 1998 under one catch assumption and 7.2% (CI 3.7–13.7%) of pre‐exploitation levels under the other. Thus, although Chilean blue whales are probably still at a small fraction of pre‐exploitation abundance, even these minimum abundance estimates demonstrate that their status is better than that of Antarctic blue whales, which are still <1% of pre‐exploitation population size. We anticipate our methods will be broadly applicable in aquatic and terrestrial surveys for rarely encountered species, especially when the surveys are intended to maximize encounter rates and estimate abundance.     

Five approaches to producing actionable science in conservation

The knowledge produced by conservation scientists must be actionable in order to address urgent conservation challenges. To understand the process of creating actionable science, we interviewed 71 conservation scientists who had participated in 1 of 3 fellowship programs focused on training scientists to become agents of change. Using a grounded theory approach, we identified 16 activities that these researchers employed to make their scientific products more actionable. Some activities were more common than others and, arguably, more foundational. We organized these activities into 3 nested categories (motivations, strategies, and tactics). Using a co-occurrence matrix, we found that most activities were positively correlated. These correlations allowed us to identify 5 approaches, framed as profiles, to actionable science: the discloser, focused on open access; the educator, focused on science communication; the networker, focused on user needs and building relationships; the collaborator, focused on boundary spanning; and the pluralist, focused on knowledge coproduction resulting in valuable outcomes for all parties. These profiles build on one another in a hierarchy determined by their complexity and level of engagement, their potential to support actionable science, and their proximity to ideal coproduction with knowledge users. Our results provide clear guidance for conservation scientists to generate actionable science to address the global biodiversity conservation challenge.     

Considering science needs to deliver actionable science

Conservation practitioners, natural resource managers, and environmental stewards often seek out scientific contributions to inform decision-making. This body of science only becomes actionable when motivated by decision makers considering alternative courses of action. Many in the science community equate addressing stakeholder science needs with delivering actionable science. However, not all efforts to address science needs deliver actionable science, suggesting that the synonymous use of these two constructs (delivering actionable science and addressing science needs) is not trivial. This can be the case when such needs are conveyed by people who neglect decision makers responsible for articulating a priority management concern and for specifying how the anticipated scientific information will aid the decision-making process. We argue that the actors responsible for articulating these science needs and the process used to identify them are decisive factors in the ability to deliver actionable science, stressing the importance of examining the provenance and the determination of science needs. Guided by a desire to enhance communication and cross-literacy between scientists and decision makers, we identified categories of actors who may inappropriately declare science needs (e.g., applied scientists with and without regulatory affiliation, external influencers, reluctant decision makers, agents in place of decision makers, and boundary organization representatives). We also emphasize the importance of, and general approach to, undertaking needs assessments or gap analyses as a means to identify priority science needs. We conclude that basic stipulations to legitimize actionable science, such as the declaration of decisions of interest that motivate science needs and using a robust process to identify priority information gaps, are not always satisfied and require verification. To alleviate these shortcomings, we formulated practical suggestions for consideration by applied scientists, decision makers, research funding entities, and boundary organizations to help foster conditions that lead to science output being truly actionable.     

Bridging information domains to improve ecological understanding of biological invasions in a marine ecosystem

We devised a practical method for integrating information on 2 marine invasive species using 3 different approaches: standardized ecological monitoring, online-reporting databases, and surveys of anglers and crabbers. Focusing on 2 recently introduced species with different characteristics, the Asian shore crab (Hemigrapsus sanguineus) and Chinese mitten crab (Eriocheir sinensis), in the Hudson-Raritan watershed of New York and New Jersey, we used sensitivity analyses to explore the relative contribution of each information source to knowledge of species abundance and distribution. All 3 information sources contributed something unique to understanding abundance and distribution of the introduced crabs. Online and survey data on Asian shore crabs significantly affected predictions of abundance, whereas monitoring data did not. When survey data were omitted, abundance estimates were unchanged over time, but when they were included, the model predicted an increased abundance in 2012. All 3 data sets for the Asian shore crab significantly affected estimates of species coverage; surveys had the biggest influence, increasing range size by 4097.25 km². For the catadromous Chinese mitten crab, ecological monitoring data collected in freshwater shortly after the original sighting significantly shaped model estimates for abundance and documented the establishment phase of the mitten crab in an area outside the spatial scope of the surveyed resource users. However, the survey data significantly enlarged mitten crab range-size estimates by 6498.01 km². By demonstrating that data integration produced an image of the invasion process that would not have emerged had we used any 1 method individually, model results provide evidence for the advantages of an interdisciplinary approach.     

Exploring human–nature interactions in national parks with social media photographs and computer vision

Understanding the activities and preferences of visitors is crucial for managing protected areas and planning conservation strategies. Conservation culturomics promotes the use of user-generated online content in conservation science. Geotagged social media content is a unique source of in situ information on human presence and activities in nature. Photographs posted on social media platforms are a promising source of information, but analyzing large volumes of photographs manually remains laborious. We examined the application of state-of-the-art computer-vision methods to studying human–nature interactions. We used semantic clustering, scene classification, and object detection to automatically analyze photographs taken in Finnish national parks by domestic and international visitors. Our results showed that human–nature interactions can be extracted from user-generated photographs with computer vision. The different methods complemented each other by revealing broad visual themes related to level of the data set, landscape photogeneity, and human activities. Geotagged photographs revealed distinct regional profiles for national parks (e.g., preferences in landscapes and activities), which are potentially useful in park management. Photographic content differed between domestic and international visitors, which indicates differences in activities and preferences. Information extracted automatically from photographs can help identify preferences among diverse visitor groups, which can be used to create profiles of national parks for conservation marketing and to support conservation strategies that rely on public acceptance. The application of computer-vision methods to automatic content analysis of photographs should be explored further in conservation culturomics, particularly in combination with rich metadata available on social media platforms.     

Assessing conservation status with extensive but low-resolution data: Application of frequentist and Bayesian models to endangered Athabasca River rainbow trout

Use of extensive but low-resolution abundance data is common in the assessment of species at-risk status based on quantitative decline criteria under International Union for Conservation of Nature (IUCN) and national endangered species legislation. Such data can be problematic for 3 reasons. First, statistical power to reject the null hypothesis of no change is often low because of small sample size and high sampling uncertainty leading to a high frequency of type II errors. Second, range-wide assessments composed of multiple site-specific observations do not effectively weight site-specific trends into global trends. Third, uncertainty in site-specific temporal trends and relative abundance are not propagated at the appropriate spatial scale. A common result is the propensity to underestimate the magnitude of declines and therefore fail to identify the appropriate at-risk status for a species. We used 3 statistical approaches, from simple to more complex, to estimate temporal decline rates for a designatable unit (DU) of rainbow trout in the Athabasca River watershed in western Canada. This DU is considered a native species for purposes of listing because of its genetic composition characterized as >0.95 indigenous origin in the face of continuing introgressive hybridization with introduced populations in the watershed. Analysis of abundance trends from 57 time series with a fixed-effects model identified 33 sites with negative trends, but only 2 were statistically significant. By contrast, a hierarchical linear mixed model weighted by site-specific abundance provided a DU-wide decline estimate of 16.4% per year and a 3-generation decline of 93.2%. A hierarchical Bayesian mixed model yielded a similar 3-generation decline trend of 91.3% and the posterior distribution showed that the estimate had a >99% probability of exceeding thresholds for an endangered listing. We conclude that the Bayesian approach was the most useful because it provided a probabilistic statement of threshold exceedance in support of an at-risk status recommendation.     

Predicting landscape-scale biodiversity recovery by natural tropical forest regrowth

Natural forest regrowth is a cost-effective, nature-based solution for biodiversity recovery, yet different socioenvironmental factors can lead to variable outcomes. A critical knowledge gap in forest restoration planning is how to predict where natural forest regrowth is likely to lead to high levels of biodiversity recovery, which is an indicator of conservation value and the potential provisioning of diverse ecosystem services. We sought to predict and map landscape-scale recovery of species richness and total abundance of vertebrates, invertebrates, and plants in tropical and subtropical second-growth forests to inform spatial restoration planning. First, we conducted a global meta-analysis to quantify the extent to which recovery of species richness and total abundance in second-growth forests deviated from biodiversity values in reference old-growth forests in the same landscape. Second, we employed a machine-learning algorithm and a comprehensive set of socioenvironmental factors to spatially predict landscape-scale deviation and map it. Models explained on average 34% of observed variance in recovery (range 9–51%). Landscape-scale biodiversity recovery in second-growth forests was spatially predicted based on socioenvironmental landscape factors (human demography, land use and cover, anthropogenic and natural disturbance, ecosystem productivity, and topography and soil chemistry); was significantly higher for species richness than for total abundance for vertebrates (median range-adjusted predicted deviation 0.09 vs. 0.34) and invertebrates (0.2 vs. 0.35) but not for plants (which showed a similar recovery for both metrics [0.24 vs. 0.25]); and was positively correlated for total abundance of plant and vertebrate species (Pearson r = 0.45, p = 0.001). Our approach can help identify tropical and subtropical forest landscapes with high potential for biodiversity recovery through natural forest regrowth.     

Microtargeting for conservation

Widespread human action and behavior change is needed to achieve many conservation goals. Doing so at the requisite scale and pace will require the efficient delivery of outreach campaigns. Conservation gains will be greatest when efforts are directed toward places of high conservation value (or need) and tailored to critical actors. Recent strategic conservation planning has relied primarily on spatial assessments of biophysical attributes, largely ignoring the human dimensions. Elsewhere, marketers, political campaigns, and others use microtargeting—predictive analytics of big data—to identify people most likely to respond positively to particular messages or interventions. Conservationists have not yet widely capitalized on these techniques. To investigate the effectiveness of microtargeting to improve conservation, we developed a propensity model to predict restoration behavior among 203,645 private landowners in a 5,200,000 ha study area in the Chesapeake Bay Watershed (U.S.A.). To isolate the additional value microtargeting may offer beyond geospatial prioritization, we analyzed a new high-resolution land-cover data set and cadastral data to identify private owners of riparian areas needing restoration. Subsequently, we developed and evaluated a restoration propensity model based on a database of landowners who had conducted restoration in the past and those who had not (n = 4978). Model validation in a parallel database (n = 4989) showed owners with the highest scorers for propensity to conduct restoration (i.e., top decile) were over twice as likely as average landowners to have conducted restoration (135%). These results demonstrate that microtargeting techniques can dramatically increase the efficiency and efficacy of conservation programs, above and beyond the advances offered by biophysical prioritizations alone, as well as facilitate more robust research of many social–ecological systems.     

Exploring the effects of reductions in krill biomass in the Southern Ocean on blue whales using a state-dependent foraging model

Many species of baleen whales were hunted to near extinction in the Southern Hemisphere. The recovery of these populations will be affected by the availability of krill, a major dietary component, in the Southern Ocean. We combine a novel energetics model for baleen whales with a state dependent foraging model to explore the impacts of an expanding krill fishery on baleen whales. We parameterize the model for blue whales, but with simple modifications it could be applied to most baleen whales. We predict that an expanding fishery will have a small but significant impact on the blue whale population through decreased birth rates. However, spreading the catch limit throughout the range of krill can reduce these effects. In addition, whales may be able to reduce these impacts through adaptive changes in foraging behavior. The relationship between krill abundance and blue whale foraging and reproductive success is nonlinear, such that larger reductions in krill biomass, potentially following a loss of sea ice due to climate change, could have a much larger negative impact on the recovery of blue whales.     

Harnessing the potential of integrated systematics for conservation of taxonomically complex,megadiverse plant groups

The value of natural history collections for conservation science research is increasingly recognized, despite their well-documented limitations in terms of taxonomic, geographic, and temporal coverage. Specimen-based analyses are particularly important for tropical plant groups for which field observations are scarce and potentially unreliable due to high levels of diversity-amplifying identification challenges. Specimen databases curated by specialists are rich sources of authoritatively identified, georeferenced occurrence data, and such data are urgently needed for large genera. We compared entries in a monographic database for the large Neotropical genus Myrcia in 2007 and 2017. We classified and quantified differences in specimen records over this decade and determined the potential impact of these changes on conservation assessments. We distinguished misidentifications from changes due to taxonomic remodeling and considered the effects of adding specimens and georeferences. We calculated the potential impact of each change on estimates of extent of occurrence (EOO), the most frequently used metric in extinction-risk assessments of tropical plants. We examined whether particular specimen changes were associated with species for which changes in EOO over the decade were large enough to change their conservation category. Corrections to specimens previously misidentified or lacking georeferences were overrepresented in such species, whereas changes associated with taxonomic remodeling (lumping and splitting) were underrepresented. Among species present in both years, transitions to less threatened status outnumbered those to more threatened (8% vs 3%, respectively). Species previously deemed data deficient transitioned to threatened status more often than to not threatened (10% vs 7%, respectively). Conservation scientists risk reaching unreliable conclusions if they use specimen databases that are not actively curated to reflect changing knowledge.     

Quantifying the probability of detection of wild ungulates with the Judas technique

The Judas technique is often used in control or eradication of particular vertebrate pests. The technique exploits the tendency of individuals to form social groups. A radio collar is affixed to an individual and its subsequent monitoring facilitates the detection of other conspecifics. Efficacy of this technique would be improved if managers could estimate the probability that a Judas individual would detect conspecifics. To calculate this probability, we estimated association rates of Judas individuals with other Judas individuals, given the length of time the Judas has been deployed. We developed a simple model of space-use for individual Judas animals and constrained detection probabilities to those specific areas. We then combined estimates for individual Judas animals to infer the probability that a wild individual could be detected in an area of interest via Judas surveillance. We illustrated the method by using data from a feral goat eradication program on Isla Santiago, Galápagos, and a feral pig eradication program on Santa Cruz Island, California. Association probabilities declined as the proximity between individual areas of use of a Judas pair decreased. Unconditional probabilities of detection within individual areas of use averaged 0.09 per month for feral pigs and 0.11 per month for feral goats. Probabilities that eradication had been achieved, given no detections of wild conspecifics, and an uninformative prior probability of eradication were 0.79 (90% CI 0.22–0.99) for feral goats and 0.87 (90% CI 0.44–1.0) for feral pigs. We envisage several additions to the analyses used that could improve estimates of Judas detection probability. Analyses such as these can help managers increase the efficacy of eradication efforts, leading to more effective effects to restore native biodiversity.     

Photographic mark-recapture analysis of clustered mammal-eating killer whales around the Aleutian Islands and Gulf of Alaska

We used photographic mark-recapture methods to estimate the number of mammal-eating “transient” killer whales using the coastal waters from the central Gulf of Alaska to the central Aleutian Islands, around breeding rookeries of endangered Steller sea lions. We identified 154 individual killer whales from 6,489 photographs collected between July 2001 and August 2003. A Bayesian mixture model estimated seven distinct clusters (95% probability interval = 7–10) of individuals that were differentially covered by 14 boat-based surveys exhibiting varying degrees of association in space and time. Markov Chain Monte Carlo methods were used to sample identification probabilities across the distribution of clusters to estimate a total of 345 identified and undetected whales (95% probability interval = 255–487). Estimates of covariance between surveys, in terms of their coverage of these clusters, indicated spatial population structure and seasonal movements from these near-shore waters, suggesting spatial and temporal variation in the predation pressure on coastal marine mammals.     

Evaluating the outcomes of genetic rescue attempts

Augmenting gene flow is a powerful tool for the conservation of small, isolated populations. However, genetic rescue attempts have largely been limited to populations at the brink of extinction, in part due to concerns over negative outcomes (e.g., outbreeding depression). Increasing habitat fragmentation may necessitate more proactive genetic management. Broader application of augmented gene flow will, in turn, require rigorous evaluation to increase confidence and identify pitfalls in this approach. To date, there has been no assessment of best monitoring practices for genetic rescue attempts. We used genomically explicit, individual-based simulations to examine the effectiveness of common approaches (i.e., tests for increases in fitness, migrant ancestry, heterozygosity, and abundance) for determining whether genetic rescue or outbreeding depression occurred. Statistical power to detect the effects of gene flow on fitness was high (≥0.8) when effect sizes were large, a finding consistent with those from previous studies on severely inbred populations. However, smaller effects of gene flow on fitness can appreciably affect persistence probability but current evaluation approaches fail to provide results from which reliable inferences can be drawn. The power of the metrics we examined to evaluate genetic rescue attempts depended on the time since gene flow and whether gene flow was beneficial or deleterious. Encouragingly, the use of multiple metrics provided nonredundant information and improved inference reliability, highlighting the importance of intensive monitoring efforts. Further development of best practices for evaluating genetic rescue attempts will be crucial for a responsible transition to increased use of translocations to decrease extinction risk.     

How to address data privacy concerns when using social media data in conservation science

Social media data are being increasingly used in conservation science to study human–nature interactions. User-generated content, such as images, video, text, and audio, and the associated metadata can be used to assess such interactions. A number of social media platforms provide free access to user-generated social media content. However, similar to any research involving people, scientific investigations based on social media data require compliance with highest standards of data privacy and data protection, even when data are publicly available. Should social media data be misused, the risks to individual users' privacy and well-being can be substantial. We investigated the legal basis for using social media data while ensuring data subjects’ rights through a case study based on the European Union's General Data Protection Regulation. The risks associated with using social media data in research include accidental and purposeful misidentification that has the potential to cause psychological or physical harm to an identified person. To collect, store, protect, share, and manage social media data in a way that prevents potential risks to users involved, one should minimize data, anonymize data, and follow strict data management procedure. Risk-based approaches, such as a data privacy impact assessment, can be used to identify and minimize privacy risks to social media users, to demonstrate accountability and to comply with data protection legislation. We recommend that conservation scientists carefully consider our recommendations in devising their research objectives so as to facilitate responsible use of social media data in conservation science research, for example, in conservation culturomics and investigations of illegal wildlife trade online.     

Shared ways of thinking in Brazil about the science–practice interface in ecology and conservation

The debate in the literature on the science–practice interface suggests a diversity of opinions on how to link science and practice to improve conservation. Understanding this diversity is key to addressing unequal power relations, avoiding the consideration of only dominant views, and identifying strategies to link science and practice. In turn, linking science and practice should promote conservation decisions that are socially robust and scientifically informed. To identify and describe the viewpoints of scientists and decision makers on how the science–practice interface should work in order to improve conservation decisions, we interviewed Brazilian scientists (ecologists and conservation scientists, n = 11) and decision makers (n = 11). We used Q methodology and asked participants to rank their agreement with 48 statements on how the science–practice interface should work in order to improve conservation decisions. We used principal component analysis to identify shared viewpoints. The predominant viewpoint, shared by scientists and decision makers, was characterized by valuing the integration of scientific and strategic knowledge to address environmental problems. The second viewpoint, held mostly by decision makers, was distinguished by assigning great importance to science in the decision-making process and calling for problem-relevant research. The third viewpoint, shared only by scientists, was characterized by an unwillingness to collaborate and a perception of scientists as producers of knowledge that may help decision makers. Most participants agreed organizations should promote collaboration and that actors and knowledge from both science and practice are relevant. Disagreements concerned specific roles assigned to actors, willingness to collaborate, and organizational and institutional arrangements considered effective to link science and practice. Our results suggest there is ample room for collaborations and that impediments lie mainly in existing organizations and formal institutional arrangements rather than in negative attitudes between scientists and decision makers.     

Conservation lessons from taboos and trolley problems

Governments pass conservation laws, adopt policies, and make plans yet frequently fail to implement them. Implementation of conservation, however, often requires costly sacrifice: people foregoing benefit for the benefit of biodiversity. Decisions involve trade-offs with outcomes that depend on the values at stake and people's perceptions of those values. Psychology, ethics, and behavioral science have each addressed the challenge of making difficult, often tragic, trade-off decisions. Based on these literatures, values can be classified as secular or sacred, where sacred values are those for which compensation may be unthinkable (e.g., freedom). Taboo trade-offs emerge when secular values are pitted against sacred ones. These are difficult to discuss, much less negotiate. Confronting taboo trade-offs in conservation may require discursive approaches to better understand particular attributes of decisions that place sacred human values at risk. Tragic trade-offs emerge when sacred values are pitted against one another. The trolley problem—a forced choice between 2 unthinkable outcomes—is a simple heuristic illustrating ethical challenges of tragic trade-offs. Behavior studies illustrate that people have a strong aversion to losses where an active choice was made, resulting in a bias toward status quo decisions. Faced with tragic, trolley-problem-like choices, people tend to avoid taking responsibility for action, defer decisions, evade opinions on painful choices, and regret unfortunate outcomes of actions. To help close the implementation gap, conservation actors may need to directly address the psychological, ethical, and behavioral barriers created by the remorse, regret, and moral residue of implementing conservation choices that have tragic outcomes. Recognition of these predictable features of the human psyche may foster better administrative structures to support action with durable outcomes as well as new research directions.     

Aligning the logics of inquiry and action to address the biodiversity crisis

Despite an abundance of research reaffirming biodiversity's importance to the health of the planet and society, species continue to go extinct at an alarming rate. Why has continued research on the value of biodiversity not had the intended effect and what can be done about it? We considered biodiversity loss as a public value failure and the result of a misalignment between the logic of inquiry (which guides scientists) and the logic of action (which guides practitioners). We drew lessons from our own research to propose the creation of a national biodiversity strategy designed to link the logic of inquiry with the logic of action and coordinate the production of actionable conservation science and informed conservation action.     

Evaluating surrogates of genetic diversity for conservation planning

Protected-area systems should conserve intraspecific genetic diversity. Because genetic data require resources to obtain, several approaches have been proposed for generating plans for protected-area systems (prioritizations) when genetic data are not available. Yet such surrogate-based approaches remain poorly tested. We evaluated the effectiveness of potential surrogate-based approaches based on microsatellite genetic data collected across the Iberian Peninsula for 7 amphibian and 3 reptilian species. Long-term environmental suitability did not effectively represent sites containing high genetic diversity (allelic richness). Prioritizations based on long-term environmental suitability had similar performance to random prioritizations. Geographic distances and resistance distances based on contemporary environmental suitability were not always effective surrogates for identification of combinations of sites that contain individuals with different genetic compositions. Our results demonstrate that population genetic data based on commonly used neutral markers can inform prioritizations, and we could not find an adequate substitute. Conservation planners need to weigh the potential benefits of genetic data against their acquisition costs.     

Using experimental reintroductions to resolve the roles of habitat quality and metapopulation dynamics on patch occupancy in fragmented landscapes

Declines of species in fragmented landscapes can potentially be reversed either by restoring connectivity or restoring local habitat quality. Models fitted to snapshot occupancy data can be used to predict the effectiveness of these actions. However, such inferences can be misleading if the reliability of the habitat and landscape metrics used is unknown. The only way to unambiguously resolve the roles of habitat quality and metapopulation dynamics is to conduct experimental reintroductions to unoccupied patches so that habitat quality can be measured directly from data on vital rates. We, therefore, conducted a 15-year study that involved reintroducing a threatened New Zealand bird to unoccupied forest fragments to obtain reliable data on their habitat quality and reassess initial inferences made by modeling occupancy against habitat and landscape metrics. Although reproductive rates were similar among fragments, subtle differences in adult survival rates resulted in λ (finite rate of increase) estimations of <0.9 for 9 of the 12 fragments that were previously unoccupied. This was the case for only 1 of 14 naturally occupied fragments. This variation in λ largely explained the original occupancy pattern, reversing our original conclusion from occupancy modeling that this occupancy pattern was isolation driven and suggesting that it would be detrimental to increase connectivity without improving local habitat quality. These results illustrate that inferences from snapshot occupancy should be treated with caution and subjected to testing through experimental reintroductions in selected model systems.