# BiodiversityImprovesProductivity
Positive Biodiversity–Productivity Relationship Predominant in Global Forests
The biodiversity–productivity relationship (BPR) is foundational to our understanding of the global extinction crisis and its impacts on ecosystem functioning. Understanding BPR is critical for the accurate valuation and effective conservation of biodiversity. Using ground-sourced data from 777,126 permanent plots, spanning 44 countries and most terrestrial biomes, we reveal a globally consistent positive concave-down BPR, whereby a continued biodiversity loss would result in an accelerating decline in forest productivity worldwide. The value of biodiversity in maintaining commercial forest productivity alone—US$166–490 billion per year according to our estimation—is by itself over two to six times the total estimated cost that would be necessary for effective global conservation. This highlights the need for a worldwide re-assessment of biodiversity values, forest management strategies, and conservation priorities.
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# ForestValueMoreThanCommercial
Forest value: More than commercial—Response
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From a policy/management perspective, the positive biodiversity-productivity relationship across the world's forests helps justify rewarding landowners for preserving or enhancing the diversity of their native or planted forests. Establishing the underlying biophysical relationship between species richness and productivity, and translating that into economic terms, reveals where markets fail to fully capture the true long-term economic value of forests, as opposed to the short-term commercial value, and thus where conservation attention is most needed.
Publications
Updated July, 2022. Please visit Science-i for the updated list
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Cazzolla Gatti, R., P. B. Reich, J. G. P. Gamarra, T. Crowther, C. Hui, A. Morera, J.-F. Bastin, S. de-Miguel, G.-J. Nabuurs, J.-C. Svenning, J. M. Serra-Diaz, C. Merow, B. Enquist, M. Kamenetsky, J. Lee, J. Zhu, J. Fang, D. F. Jacobs, B. Pijanowski, A. Banerjee, R. A. Giaquinto, G. Alberti, A. M. Almeyda Zambrano, E. Alvarez-Davila, A. Araujo-Murakami, V. Avitabile, G. A. Aymard, R. Balazy, C. Baraloto, J. G. Barroso, M. L. Bastian, P. Birnbaum, R. Bitariho, J. Bogaert, F. Bongers, O. Bouriaud, P. H. S. Brancalion, F. Q. Brearley, E. N. Broadbent, F. Bussotti, W. Castro da Silva, R. G. César, G. Češljar, V. Chama Moscoso, H. Y. H. Chen, E. Cienciala, C. J. Clark, D. A. Coomes, S. Dayanandan, M. Decuyper, L. E. Dee, J. Del Aguila Pasquel, G. Derroire, M. N. K. Djuikouo, T. Van Do, J. Dolezal, I. Đ. Đorđević, J. Engel, T. M. Fayle, T. R. Feldpausch, J. K. Fridman, D. J. Harris, A. Hemp, G. Hengeveld, B. Herault, M. Herold, T. Ibanez, A. M. Jagodzinski, B. Jaroszewicz, K. J. Jeffery, V. K. Johannsen, T. Jucker, A. Kangur, V. N. Karminov, K. Kartawinata, D. K. Kennard, S. Kepfer-Rojas, G. Keppel, M. L. Khan, P. K. Khare, T. J. Kileen, H. S. Kim, H. Korjus, A. Kumar, A. Kumar, D. Laarmann, N. Labrière, M. Lang, S. L. Lewis, N. Lukina, B. S. Maitner, Y. Malhi, A. R. Marshall, O. V. Martynenko, A. L. Monteagudo Mendoza, P. V. Ontikov, E. Ortiz-Malavasi, N. C. Pallqui Camacho, A. Paquette, M. Park, N. Parthasarathy, P. L. Peri, P. Petronelli, S. Pfautsch, O. L. Phillips, N. Picard, D. Piotto, L. Poorter, J. R. Poulsen, H. Pretzsch, H. Ramírez-Angulo, Z. Restrepo Correa, M. Rodeghiero, R. D. P. Rojas Gonzáles, S. G. Rolim, F. Rovero, E. Rutishauser, P. Saikia, C. Salas-Eljatib, D. Schepaschenko, M. Scherer-Lorenzen, V. Šebeň, M. Silveira, F. Slik, B. Sonké, A. F. Souza, K. J. Stereńczak, M. Svoboda, H. Taedoumg, N. Tchebakova, J. Terborgh, E. Tikhonova, A. Torres-Lezama, F. van der Plas, R. Vásquez, H. Viana, A. C. Vibrans, E. Vilanova, V. A. Vos, H.-F. Wang, B. Westerlund, L. J. T. White, S. K. Wiser, T. Zawiła-Niedźwiecki, L. Zemagho, Z.-X. Zhu, I. C. Zo-Bi, and Liang, J. 2022. The number of tree species on Earth. Proceedings of the National Academy of Sciences 119:e2115329119.
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Santoro, M., O. Cartus, U. Wegmüller, S. Besnard, N. Carvalhais, A. Araza, M. Herold, J. Liang, J. Cavlovic, and M. E. Engdahl. 2022. Global estimation of above-ground biomass from spaceborne C-band scatterometer observations aided by LiDAR metrics of vegetation structure. Remote Sensing of Environment 279:113114.
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Araza, A., S. de Bruin, M. Herold, S. Quegan, N. Labriere, P. Rodriguez-Veiga, V. Avitabile, M. Santoro, E. T. A. Mitchard, C. M. Ryan, O. L. Phillips, S. Willcock, H. Verbeeck, J. Carreiras, L. Hein, M.-J. Schelhaas, A. M. Pacheco-Pascagaza, P. da Conceição Bispo, G. V. Laurin, G. Vieilledent, F. Slik, A. Wijaya, S. L. Lewis, A. Morel, Liang, H. Sukhdeo, D. Schepaschenko, J. Cavlovic, H. Gilani, and R. Lucas. 2022. A comprehensive framework for assessing the accuracy and uncertainty of global above-ground biomass maps. Remote Sensing of Environment 272:112917.
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Leite, R. V., C. A. Silva, E. N. Broadbent, C. H. d. Amaral, V. Liesenberg, D. R. A. d. Almeida, M. Mohan, S. Godinho, A. Cardil, C. Hamamura, B. L. d. Faria, P. H. S. Brancalion, A. Hirsch, G. E. Marcatti, A. P. Dalla Corte, A. M. A. Zambrano, M. B. T. d. Costa, E. A. T. Matricardi, A. L. d. Silva, L. R. R. Y. Goya, R. Valbuena, B. A. F. d. Mendonça, C. H. L. Silva Junior, L. E. O. C. Aragão, M. García, Liang, T. Merrick, A. T. Hudak, J. Xiao, S. Hancock, L. Duncason, M. P. Ferreira, D. Valle, S. Saatchi, and C. Klauberg. 2022. Large scale multi-layer fuel load characterization in tropical savanna using GEDI spaceborne lidar data. Remote Sensing of Environment 268:112764.
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Santoro, M., O. Cartus, N. Carvalhais, D. M. A. Rozendaal, V. Avitabile, A. Araza, S. de Bruin, M. Herold, S. Quegan, P. Rodríguez-Veiga, H. Balzter, J. Carreiras, D. Schepaschenko, M. Korets, M. Shimada, T. Itoh, Á. Moreno Martínez, J. Cavlovic, R. Cazzolla Gatti, P. da Conceição Bispo, N. Dewnath, N. Labrière, Liang, J. Lindsell, E. T. A. Mitchard, A. Morel, A. M. Pacheco Pascagaza, C. M. Ryan, F. Slik, G. Vaglio Laurin, H. Verbeeck, A. Wijaya, and S. Willcock. 2021. The global forest above-ground biomass pool for 2010 estimated from high-resolution satellite observations. Earth Syst. Sci. Data 13:3927-3950.
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da Costa, M. B. T., C. A. Silva, E. N. Broadbent, R. V. Leite, M. Mohan, V. Liesenberg, J. Stoddart, C. H. do Amaral, D. R. A. de Almeida, A. L. da Silva, L. R. Ré Y. Goya, V. A. Cordeiro, F. Rex, A. Hirsch, G. E. Marcatti, A. Cardil, B. A. F. de Mendonça, C. Hamamura, A. P. D. Corte, E. A. T. Matricardi, A. T. Hudak, A. M. A. Zambrano, R. Valbuena, B. L. de Faria, C. H. L. Silva Junior, L. Aragao, M. E. Ferreira, Liang, S. d. P. C. Carvalho, and C. Klauberg. 2021. Beyond trees: Mapping total aboveground biomass density in the Brazilian savanna using high-density UAV-lidar data. Forest Ecology and Management 491:119155.
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Luo, W., Zhang, C.*, Zhao, X., Liang, J. Understanding patterns and potential drivers of forest diversity in northeastern China using machine-learning algorithms. Journal of Vegetation Science 32(2): e13022
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Morera, A., Bonet, J. A., Liang, J., & de-Miguel, S. 2021. Performance of Statistical and Machine Learning-Based Methods for Predicting Biogeographical Patterns of Fungal Productivity in Forest Ecosystems. Forest Ecosystems 8 (1), 1-14.
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Hao, M., von Gadow, K., Alavi, S.J., Álvarez-González, J.G., Baluarte-Vásquez, J.R., Corral-Rivas, J., Hui, G., Korol, M., Kumar, R. & Liang, J. A classification of woody communities based on biological dissimilarity. Applied Vegetation Science 24: e12565. A classification of woody communities based on biological dissimilarity. Applied Vegetation Science 24:e12565.
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Liang, J., and J. G. P. Gamarra. 2020. The importance of sharing global forest data in a world of crises. Scientific Data 7:424.
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Luo, W., H. S. Kim, X. Zhao, D. Ryu, I. Jung, H. Cho, N. Harris, S. Ghosh, C. Zhang, and Liang, J. 2020. New forest biomass carbon stock estimates in Northeast Asia based on multisource data. Global Change Biology 26(12): 7045-7066. doi: 10.1111/gcb.15376.
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Adrián, C., d.-M. Sergio, S. Carlos Alberto, B. R. Peter, E. C. David, H. S. B. Pedro, C. V. Alexander, G. P. G. Javier, Z. Mo, C. P. Bryan, H. Cang, W. C. Thomas, H. Bruno, P. Daniel, S.-E. Christian, B. Eben, M. A. Z. Angelica, P. Nicolas, E. O. C. A. Luiz, B. Jean-Francois, R. Devin, H. Johan van den, L. P. Pablo, and Liang, J. 2020. Recent deforestation drove the spike in Amazonian fires. Environmental Research Letters 15:121003.
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Brancalion, P. H. S., E. N. Broadbent, S. de-Miguel, A. Cardil, M. R. Rosa, C. T. Almeida, D. R. A. Almeida, S. Chakravarty, M. Zhou, J. G. P. Gamarra, Liang, J., R. Crouzeilles, B. Hérault, L. E. O. C. Aragão, C. A. Silva, and A. M. Almeyda-Zambrano. 2020. Emerging threats linking tropical deforestation and the COVID-19 pandemic. Perspectives in Ecology and Conservation 18(4): 243-246. doi: 10.1016/j.pecon.2020.09.006.
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Zohner, C. M., L. Mo, S. S. Renner, J.-C. Svenning, Y. Vitasse, B. M. Benito, A. Ordonez, F. Baumgarten, J.-F. Bastin, V. Sebald, P. B. Reich, Liang, J., etc. 2020. Late-spring frost risk between 1959 and 2017 decreased in North America but increased in Europe and Asia. Proceedings of the National Academy of Sciences 117:12192-12200.
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Marshall, A. R., P. J. Platts, R. L. Chazdon, H. Seki, M. J. Campbell, O. L. Phillips, R. E. Gereau, R. Marchant, Liang, J., and J. Herbohn. 2020. Conceptualising the global forest response to liana proliferation. Frontiers in Forests and Global Change 3:35.
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W Ma, G. Lin, and Liang, J. 2020. Estimating dynamics of central hardwood forests using random forests. Ecological Modelling 419-1:108947.
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Tang, X., X. Pei, N. Lei, X. Luo, L. Liu, L. Shi, G. Chen, and Liang, J.. 2020. Global patterns of soil autotrophic respiration and its relation to climate, soil and vegetation characteristics. Geoderma 369:114339.
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Steidinger, BS, TW Crowther, Liang, J., M. E. Van Nuland, G. D. A. Werner, P. B. Reich, G. J. Nabuurs, S. de-Miguel, M. Zhou, N. Picard, and GFBI consortium. 2019. Climatic controls of decomposition drive the global biogeography of forest-tree symbioses. Nature 569:404-408.
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W Luo, Liang, J., R. Cazzolla Gatti, X. Zhao, and C. Zhang. 2019. Parameterization of biodiversity–productivity relationship and its scale dependency using georeferenced tree-level data. Journal of Ecology 107(3): 1106-1119.
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Ma, Wu, Xiaoping Zhou, Liang, J., and Mo Zhou. 2019. Coastal Alaska forests under climate change: What to expect? Forest Ecology and Management448: 432-444.
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Cazzolla Gatti, Liang, J., A. Velichevskaya, and M. Zhou. 2019. Sustainable palm oil may not be so sustainable. Science of The Total Environment 652:48-51.
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R Cazzolla Gatti, Callaghan, T., Velichevskaya, A., Dudko, A., Fabbio, L., Battipaglia, G. and Liang, J., 2019. Accelerating upward treeline shift in the Altai Mountains under last-century climate change. Scientific Reports, 9: 7678.
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L Zeller, Liang, J. and Pretzsch, H., 2018. Tree species richness enhances stand productivity while stand structure can have opposite effects, based on forest inventory data from Germany and the United States of America. Forest Ecosystems, 5(1), p.4.
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Paquette, A., A. Hector, B. Castagneyrol, M. Vanhellemont, J. Koricheva, M. Scherer-Lorenzen, K. Verheyen, L. Abdala-Roberts, H. Auge, N. Barsoum, J. Bauhus, C. Baum, H. Bruelheide, B. Castagneyrol, J. Cavender-Bares, N. Eisenhauer, O. Ferlian, G. Ganade, D. Godbold, D. Gravel, J. Hall, A. Hector, R. Hobbs, D. Hoelscher, K. B. Hulvey, M. Huxham, H. Jactel, J. Koricheva, H. Kreft, Liang, J., S. Mereu, C. Messier, R. Montgomery, B. Muys, C. Nock, A. Paquette, J. Parker, W. Parker, V. Parra-Tabla, M. P. Perring, Q. Ponette, C. Potvin, P. B. Reich, B. Rewald, H. Sandén, M. Scherer-Lorenzen, A. Smith, R. Standish, M. Vanhellemont, K. Verheyen, M. Weih, M. Wollni, D. C. Zemp, and TreeDivNet. 2018. A million and more trees for science. Nature Ecology & Evolution 2:763-766.
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Lee, J; Gangnon, R; Zhu, J; Liang, J. Uncertainty of a detected spatial cluster in 1D: quantification and visualization. Stat 6 (1), 345-359
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Liang, J., W. Crowther, N. Picard, S. Wiser, M. Zhou, G. Alberti, E.-D. Schulze, A. D. McGuire, F. Bozzato, H. Pretzsch, S. de-Miguel, A. Paquette, B. Hérault, M. Scherer-Lorenzen, C. B. Barrett, H. B. Glick, G. M. Hengeveld, G.-J. Nabuurs, S. Pfautsch, H. Viana, A. C. Vibrans, C. Ammer, P. Schall, D. Verbyla, N. Tchebakova, M. Fischer, J. V. Watson, H. Y. H. Chen, X. Lei, M.-J. Schelhaas, H. Lu, D. Gianelle, E. I. Parfenova, C. Salas, E. Lee, B. Lee, H. S. Kim, H. Bruelheide, D. A. Coomes, D. Piotto, T. Sunderland, B. Schmid, S. Gourlet-Fleury, B. Sonké, R. Tavani, J. Zhu, S. Brandl, J. Vayreda, F. Kitahara, E. B. Searle, V. J. Neldner, M. R. Ngugi, C. Baraloto, L. Frizzera, R. Bałazy, J. Oleksyn, T. Zawiła-Niedźwiecki, O. Bouriaud, F. Bussotti, L. Finér, B. Jaroszewicz, T. Jucker, F. Valladares, A. M. Jagodzinski, P. L. Peri, C. Gonmadje, W. Marthy, T. O’Brien, E. H. Martin, A. R. Marshall, F. Rovero, R. Bitariho, P. A. Niklaus, P. Alvarez-Loayza, N. Chamuya, R. Valencia, F. Mortier, V. Wortel, N. L. Engone-Obiang, L. V. Ferreira, D. E. Odeke, R. M. Vasquez, S. L. Lewis, and P. B. Reich. 2016. Positive biodiversity-productivity relationship predominant in global forests. Science 354 (6309): aaf8957. DOI: 10.1126/science.aaf8957