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Record W2937057349 · doi:10.1111/acv.12499

The stepping‐stone approach is promising but we need so much more

2019· article· en· W2937057349 on OpenAlexaboutno aff
Aliénor L. M. Chauvenet

Bibliographic record

VenueAnimal Conservation · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationThreatened speciesHarmHabitatEndangered speciesCounterfactual thinkingNothingClimate changeEcologyGeographyEnvironmental ethicsBiologyPolitical scienceDemographyPsychologySociologyLaw

Abstract

fetched live from OpenAlex

Translocation is probably one of the best studied and established conservation actions (Seddon, Strauss & Innes, 2012). Most anthropogenic threats – including invasive species, disease or climate change – directly or indirectly disturb habitat quality and availability for species (Ayyad, 2003), and the idea that we can move threatened populations out of harm's way is very attractive. Translocations have a rich history of both successes and failures. In their excellent introduction, Lloyd et al. (2019) explain how release strategy is known to be a key factor in determining if a translocated population thrives in the wild or not, and has been the subject of much work. We know that the survival of translocated individuals straight after translocation is reduced, especially for captive-bred animals. Obviously, initial survival can have long-term repercussions for the new population, and we are yet to fully address this issue. Lloyd et al. (2019) therefore put forward the idea of the ‘stepping-stone’ approach: release individuals into an existing wild population first, before moving them into historic or novel range to create a new population. Using the Vancouver Island marmot (Marmota vancouverensis), they set out to test their idea. What I like the most about this paper – apart from the rigorous maths and cool models – is the use of a controlled experiment. Often, conservation studies fail to include a counterfactual (Ferraro & Pattanayak, 2006), which weakens their claims: how can we attribute an outcome to an action, if we don't know what would have happened if you did nothing? Lloyd et al. (2019) cleverly design their multi-year capture-mark-recapture experiment in order to compare the annual survival, and survival to prime-breeding age (PBA) of three treatment groups: wild-to-wild, captive-to-wild and captive-intermediate site-wild (stepping-stone treatment). As a result, they are able to conclude on the effectiveness of the proposed stepping-stone method on annual survival and survival to PBA of the Vancouver Island marmot. However, there are two aspects of the work I want to discuss: (1) how stepping-stone effectiveness is measured and (2) how this work scales up to other systems. Lloyd et al. (2019) show that individuals translocated to the intermediate (‘safer’) site initially have higher annual survival than those translocated directly to the final (wild) site. However, when the stepping-stone individuals are moved to the wild site in year 2, their survival decreases to that of the other captive-bred translocated individuals. In year 3, the effect of translocation on annual survival disappears, and all three treatments (including wild-to-wild) have similar rates. Does that show that the stepping-stone approach is an effective conservation tool? If the objective is to address first year survival reduction, then yes. The authors proceed to show that median survival to PBA (another measure of treatment effectiveness) is much higher for the stepping-stone individuals than the captive-to-wild ones, as long as animals are released as yearlings. The picture presented here is clear: using a stepping-stone approach for the marmots removes the first year post-translocation survival slump (but not the second year one), and improves survival to PBA if animals are released young. However, I am left slightly unsatisfied by these results. They don't tell me what the long-term persistence of the population is if the stepping-stone approach is used – and isn't that what it's all about? I would be interested to see a population model that integrates their demographic results and shows the long-term benefits of the stepping-stone approach developed (see e.g. Chauvenet et al., 2012; Correia et al., 2015). My second comment is also the most obvious one: how does this scale up to other species? The Vancouver Island marmot is a large herbivorous rodent, which is social and colonial (Lloyd et al., 2019). By the authors’ own admission, the reason why the stepping-stone approach improves survival (as measured here) is unknown; the observed effect could be due to low predation rates (fewer predators and/or higher group effect from the presence of more conspecifics) or the translocated individuals being able to hibernate in real underground burrows with conspecifics (something they had no experience with until then) or both. More work is needed to confirm this assumption. If we don't know why captive-bred marmots respond well to this approach – is it driven by their behaviour, life-history traits or habitat quality? – there is no way to apply it anywhere else. In my opinion, this may prevent the stepping-stone approach from being taken up by other wildlife managers, despite it being promising. The future of biodiversity is bleak. If habitat destruction, spread of disease, invasive species and poaching were not enough, species also face climate change, which affects habitat availability but also compounds the impacts of all the other threats. Translocations are unambiguously needed to help biodiversity survive into the future (Bonebrake et al., 2018), but what we need are strategies that look beyond a species’ narrow requirements and specialized life-history traits, and can be applied to as many species as possible. I look forward to seeing how Lloyd and colleagues develop this work to improve its applicability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.226
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2019
Admission routes1
Has abstractyes

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