{"id":"W4414559345","doi":"10.1111/gcb.70493","title":"Diversity in Resource Use Strategies Promotes Productivity in Young Planted Tree Species Mixtures","year":2025,"lang":"en","type":"article","venue":"Global Change Biology","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal; Ontario Forest Research Institute; University of Alberta; Université du Québec en Outaouais; McGill University; Ministry of Natural Resources and Forestry","funders":"European Social Fund; Interreg; European Regional Development Fund; Australian Research Council; Smithsonian Tropical Research Institute; U.S. Forest Service; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; HORIZON EUROPE Framework Programme; Deutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-Leipzig; Centre de Coopération Internationale en Recherche Agronomique pour le Développement; Technische Universität Berlin; Université de Bordeaux; Helmholtz-Zentrum für Umweltforschung; Universiteit Gent; Smithsonian Institution; Vetenskapsrådet; Sveriges Lantbruksuniversitet; Deutsche Forschungsgemeinschaft; Georg-August-Universität Göttingen; Centro Euro-Mediterraneo sui Cambiamenti Climatici; Fondation BNP Paribas; BNP Paribas Cardif; Austrian Science Fund; Albert-Ludwigs-Universität Freiburg; Biodiversa+; Svenska Forskningsrådet Formas; Mendelova Univerzita v Brně; National Science Foundation; University of Minnesota; Belgian Federal Science Policy Office; Universität Rostock; Fundação de Amparo à Pesquisa do Estado de São Paulo; Universidade de São Paulo; Universität für Bodenkultur Wien; European Commission; Université du Québec à Montréal; Agence Nationale de la Recherche; Universität Leipzig; U.S. Department of Agriculture","keywords":"Species richness; Productivity; Trait; Species diversity; Diversity (politics); Selection (genetic algorithm); Biodiversity; Functional diversity","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008479943,0.0003791524,0.0004725785,0.0007027307,0.0006227069,0.0008467033,0.000364164,0.0002780055,0.0009412989],"category_scores_gemma":[0.0008041312,0.0002893989,0.0003830847,0.0003774099,0.0005290973,0.0005809189,0.001104062,0.0004505399,0.000131094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005392779,"about_ca_system_score_gemma":0.0003775589,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001852414,"about_ca_topic_score_gemma":0.00799329,"domain_scores_codex":[0.9996338,0.000080055,0.00003443294,0.0001513917,0.00004450652,0.00005585426],"domain_scores_gemma":[0.9991148,0.0002270913,0.0002213361,0.0000951547,0.00006309358,0.0002784621],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001154114,0.0004599306,0.4262345,0.0001531842,0.0003675007,0.0002476527,0.0006260505,0.001244641,0.5553842,0.000530142,0.00008552208,0.01351253],"study_design_scores_gemma":[0.0000162305,0.0003249104,0.9911147,0.000007989462,0.00006789501,0.0001400266,0.0002250509,0.002272577,0.005141254,0.0003593343,0.0003140858,0.00001581654],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995782,0.00005216097,0.0001930377,0.000004777282,0.000001050523,0.000003140269,0.00002367314,0.000005498523,0.0001384482],"genre_scores_gemma":[0.9990599,0.00004725389,0.0006084628,0.00003042918,0.000003158115,0.00001081971,0.000112274,0.000005234793,0.0001224094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001852414,"threshold_uncertainty_score":0.004484653,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03725774457537833,"score_gpt":0.2646688493503775,"score_spread":0.2274111047749992,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}