MétaCan
Menu
Back to cohort
Record W1745651044 · doi:10.1111/conl.12197

Bombing for Biodiversity in the United States: Response to Zentelis & Lindenmayer 2015

2015· article· en· W1745651044 on OpenAlexaff
Jocelyn L. Aycrigg, R. Travis Belote, Matthew S. Dietz, Gregory H. Aplet, Richard A. Fischer

Bibliographic record

VenueConservation Letters · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsCanadian Parks and Wilderness Society
Fundersnot available
KeywordsBiodiversityGeographyEnvironmental resource managementNational parkEcosystem servicesLand useEcologyEnvironmental protectionEcosystemEnvironmental scienceArchaeologyBiology

Abstract

fetched live from OpenAlex

Zentelis & Lindenmayer (2015) contend military training areas (MTAs) “have the potential to make a significant formal contribution to biodiversity conservation,” yet their conservation value has not been rigorously assessed. We believe their paper is an important step in raising awareness of the potential conservation value of MTAs to policy makers, scientists, and conservation professionals. Here, we offer an empirical evaluation of their statements regarding size, distribution, and representation of ecological systems (i.e., vegetation communities) within MTAs for the contiguous United States (CONUS) by comparing MTAs with lands managed by other U.S. federal agencies. We used lands managed by Department of Defense (DoD) as a proxy for MTAs. By combining the Protected Areas Database of the U.S. (PAD-US; USGS-GAP 2012) and the National GAP Land Cover (USGS-GAP 2011), we determined total number of ecological systems across all units of DoD and other agencies; and proportion of each ecological system that each agency represents across all lands. DoD lands occur in every state (Figure S1) and represent 467 of 565 total ecological systems within CONUS on 8.1 million hectares (Table S1). This ecological diversity is exceeded only by the National Park Service (NPS), which represents 479 ecological systems across 10.2 million hectares. In contrast, U.S. Forest Service (USFS) and Bureau of Land Management (BLM) lands, despite being 8.5 and 8.6 times larger than DoD lands, represent only 458 and 293 ecosystems, respectively. Therefore, even though DoD lands comprise only 5% of the total area of federal lands, they represent 82.6% of the diversity of ecological systems, whereas USFS and BLM comprise 42% and 43% of the total federal land area, but neither represents as much diversity as DoD lands. Similarly, Stein et al. (2008) found DoD lands disproportionately represented more imperiled species (e.g., vascular plants) per unit area than other federal lands. DoD lands also contribute to total representation of ecological systems on federal lands, as three ecological systems occur on DoD lands only. These ecological systems are relatively rare (i.e., occur on <10,000 hectares throughout CONUS) and have >50–100% of their area on federal lands within DoD. Similar to other federal agencies, the majority of ecological systems have <10% of their entire or federal distribution within DoD lands (Figure S2, USFS is an exception). As part of the entire collective of federal lands, DoD lands increase federal representation of 50 ecological systems by >5% (Figure S3). Our results are likely a consequence of a mandate that DoD lands be intentionally distributed across the U.S. to train the military under a variety of geographic conditions. They contrast with lands managed by BLM, NPS, USFS, and U.S. Fish and Wildlife Service (FWS), which have been obtained through various opportunities and agency-specific conservation priorities (Aycrigg et al. 2013) and not specifically established to maximize biological diversity (Scott et al. 2001). Our empirical analysis of DoD lands within CONUS support the contentions of Zentelis & Lindenmayer (2015) that DoD lands (i.e., MTAs) contribute to biodiversity conservation and should be considered a conservation asset. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.054
GPT teacher head0.281
Teacher spread0.227 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations22
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueConservation LettersSame topicEcology and Vegetation Dynamics StudiesFrench-language works237,207