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Record W2779029320 · doi:10.1111/gcb.14030

Global environmental change effects on plant community composition trajectories depend upon management legacies

2017· article· en· W2779029320 on OpenAlexaff
Michael P. Perring, Markus Bernhardt‐Römermann, Lander Baeten, Gabriele Midolo, Haben Blondeel, Leen Depauw, Dries Landuyt, Sybryn L. Maes, Emiel De Lombaerde, María Mercedes Carón, Mark Vellend, Jörg Brunet, Markéta Chudomelová, Guillaume Decocq, Martin Diekmann, Thomas Dirnböck, Inken Dörfler, Tomasz Durak, Pieter De Frenne, Frank S. Gilliam, Radim Hédl, Thilo Heinken, P.W.F.M. Hommel, Bogdan Jaroszewicz, K. J. Kirby, Martin Kopecký, Jonathan Lenoir, Daijiang Li, Frantíšek Máliš, Fraser Mitchell, Tobias Naaf, Miles Newman, Petr Petřík, Kamila Reczyńska, Wolfgang Schmidt, Tibor Standovár, Krzysztof Świerkosz, Hans Van Calster, Ondřej Vild, Eva Wagner, Monika Wulf, Kris Verheyen

Bibliographic record

VenueGlobal Change Biology · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversité de Sherbrooke
FundersEuropean Research CouncilVlaamse regeringUniversiteit GentGrantová Agentura České RepublikyFonds Wetenschappelijk OnderzoekAgentúra na Podporu Výskumu a Vývoja
KeywordsSpecies richnessUnderstoryEnvironmental changeForest managementEcologyPlant communityTemperate forestGlobal changeTemperate rainforestGeographyCoppicingTraitIndicator valueClimate changeEnvironmental resource managementTemperate climateEcosystemEnvironmental scienceWoody plantCanopyBiology

Abstract

fetched live from OpenAlex

The contemporary state of functional traits and species richness in plant communities depends on legacy effects of past disturbances. Whether temporal responses of community properties to current environmental changes are altered by such legacies is, however, unknown. We expect global environmental changes to interact with land-use legacies given different community trajectories initiated by prior management, and subsequent responses to altered resources and conditions. We tested this expectation for species richness and functional traits using 1814 survey-resurvey plot pairs of understorey communities from 40 European temperate forest datasets, syntheses of management transitions since the year 1800, and a trait database. We also examined how plant community indicators of resources and conditions changed in response to management legacies and environmental change. Community trajectories were clearly influenced by interactions between management legacies from over 200 years ago and environmental change. Importantly, higher rates of nitrogen deposition led to increased species richness and plant height in forests managed less intensively in 1800 (i.e., high forests), and to decreases in forests with a more intensive historical management in 1800 (i.e., coppiced forests). There was evidence that these declines in community variables in formerly coppiced forests were ameliorated by increased rates of temperature change between surveys. Responses were generally apparent regardless of sites' contemporary management classifications, although sometimes the management transition itself, rather than historic or contemporary management types, better explained understorey responses. Main effects of environmental change were rare, although higher rates of precipitation change increased plant height, accompanied by increases in fertility indicator values. Analysis of indicator values suggested the importance of directly characterising resources and conditions to better understand legacy and environmental change effects. Accounting for legacies of past disturbance can reconcile contradictory literature results and appears crucial to anticipating future responses to global environmental change.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
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 science0.0000.001
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 head0.036
GPT teacher head0.278
Teacher spread0.242 · 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

Citations139
Published2017
Admission routes1
Has abstractyes

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