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1,043 results on '"Penuelas, Josep"'

51. A Methodology to Derive Global Maps of Leaf Traits Using Remote Sensing and Climate Data

Author

Moreno-Martinez, Alvaro, Camps-Valls, Gustau, Kattge, Jens, Robinson, Nathaniel, Reichstein, Markus, van Bodegom, Peter, Kramer, Koen, Cornelissen, J. Hans C., Reich, Peter, Bahn, Michael, Niinemets, Ulo, Peñuelas, Josep, Craine, Joseph, Cerabolini, Bruno E. L., Minden, Vanessa, Laughlin, Daniel C., Sack, Lawren, Allred, Brady, Baraloto, Christopher, Byun, Chaeho, Soudzilovskaia, Nadejda A., and Running, Steven W.

Subjects
Statistics - Applications, Physics - Applied Physics
Abstract

This paper introduces a modular processing chain to derive global high-resolution maps of leaf traits. In particular, we present global maps at 500 m resolution of specific leaf area, leaf dry matter content, leaf nitrogen and phosphorus content per dry mass, and leaf nitrogen/phosphorus ratio. The processing chain exploits machine learning techniques along with optical remote sensing data (MODIS/Landsat) and climate data for gap filling and up-scaling of in-situ measured leaf traits. The chain first uses random forests regression with surrogates to fill gaps in the database ($> 45 \% $ of missing entries) and maximize the global representativeness of the trait dataset. Along with the estimated global maps of leaf traits, we provide associated uncertainty estimates derived from the regression models. The process chain is modular, and can easily accommodate new traits, data streams (traits databases and remote sensing data), and methods. The machine learning techniques applied allow attribution of information gain to data input and thus provide the opportunity to understand trait-environment relationships at the plant and ecosystem scales.

Published
2020
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52. A systematic global stocktake of evidence on human adaptation to climate change

Author

Berrang-Ford, Lea, Siders, AR, Lesnikowski, Alexandra, Fischer, Alexandra Paige, Callaghan, Max W, Haddaway, Neal R, Mach, Katharine J, Araos, Malcolm, Shah, Mohammad Aminur Rahman, Wannewitz, Mia, Doshi, Deepal, Leiter, Timo, Matavel, Custodio, Musah-Surugu, Justice Issah, Wong-Parodi, Gabrielle, Antwi-Agyei, Philip, Ajibade, Idowu, Chauhan, Neha, Kakenmaster, William, Grady, Caitlin, Chalastani, Vasiliki I, Jagannathan, Kripa, Galappaththi, Eranga K, Sitati, Asha, Scarpa, Giulia, Totin, Edmond, Davis, Katy, Hamilton, Nikita Charles, Kirchhoff, Christine J, Kumar, Praveen, Pentz, Brian, Simpson, Nicholas P, Theokritoff, Emily, Deryng, Delphine, Reckien, Diana, Zavaleta-Cortijo, Carol, Ulibarri, Nicola, Segnon, Alcade C, Khavhagali, Vhalinavho, Shang, Yuanyuan, Zvobgo, Luckson, Zommers, Zinta, Xu, Jiren, Williams, Portia Adade, Canosa, Ivan Villaverde, van Maanen, Nicole, van Bavel, Bianca, van Aalst, Maarten, Turek-Hankins, Lynée L, Trivedi, Hasti, Trisos, Christopher H, Thomas, Adelle, Thakur, Shinny, Templeman, Sienna, Stringer, Lindsay C, Sotnik, Garry, Sjostrom, Kathryn Dana, Singh, Chandni, Siña, Mariella Z, Shukla, Roopam, Sardans, Jordi, Salubi, Eunice A, Safaee Chalkasra, Lolita Shaila, Ruiz-Díaz, Raquel, Richards, Carys, Pokharel, Pratik, Petzold, Jan, Penuelas, Josep, Pelaez Avila, Julia, Murillo, Julia B Pazmino, Ouni, Souha, Niemann, Jennifer, Nielsen, Miriam, New, Mark, Nayna Schwerdtle, Patricia, Nagle Alverio, Gabriela, Mullin, Cristina A, Mullenite, Joshua, Mosurska, Anuszka, Morecroft, Mike D, Minx, Jan C, Maskell, Gina, Nunbogu, Abraham Marshall, Magnan, Alexandre K, Lwasa, Shuaib, Lukas-Sithole, Megan, Lissner, Tabea, Lilford, Oliver, Koller, Steven F, Jurjonas, Matthew, Joe, Elphin Tom, Huynh, Lam TM, Hill, Avery, Hernandez, Rebecca R, Hegde, Greeshma, Hawxwell, Tom, Harper, Sherilee, Harden, Alexandra, Haasnoot, Marjolijn, and Gilmore, Elisabeth A

Subjects
Climate Action, Atmospheric Sciences, Physical Geography and Environmental Geoscience, Environmental Science and Management
Abstract

Assessing global progress on human adaptation to climate change is an urgent priority. Although the literature on adaptation to climate change is rapidly expanding, little is known about the actual extent of implementation. We systematically screened >48,000 articles using machine learning methods and a global network of 126 researchers. Our synthesis of the resulting 1,682 articles presents a systematic and comprehensive global stocktake of implemented human adaptation to climate change. Documented adaptations were largely fragmented, local and incremental, with limited evidence of transformational adaptation and negligible evidence of risk reduction outcomes. We identify eight priorities for global adaptation research: assess the effectiveness of adaptation responses, enhance the understanding of limits to adaptation, enable individuals and civil society to adapt, include missing places, scholars and scholarship, understand private sector responses, improve methods for synthesizing different forms of evidence, assess the adaptation at different temperature thresholds, and improve the inclusion of timescale and the dynamics of responses.

Published
2021

53. The three major axes of terrestrial ecosystem function

Author

Migliavacca, Mirco, Musavi, Talie, Mahecha, Miguel D, Nelson, Jacob A, Knauer, Jürgen, Baldocchi, Dennis D, Perez-Priego, Oscar, Christiansen, Rune, Peters, Jonas, Anderson, Karen, Bahn, Michael, Black, T Andrew, Blanken, Peter D, Bonal, Damien, Buchmann, Nina, Caldararu, Silvia, Carrara, Arnaud, Carvalhais, Nuno, Cescatti, Alessandro, Chen, Jiquan, Cleverly, Jamie, Cremonese, Edoardo, Desai, Ankur R, El-Madany, Tarek S, Farella, Martha M, Fernández-Martínez, Marcos, Filippa, Gianluca, Forkel, Matthias, Galvagno, Marta, Gomarasca, Ulisse, Gough, Christopher M, Göckede, Mathias, Ibrom, Andreas, Ikawa, Hiroki, Janssens, Ivan A, Jung, Martin, Kattge, Jens, Keenan, Trevor F, Knohl, Alexander, Kobayashi, Hideki, Kraemer, Guido, Law, Beverly E, Liddell, Michael J, Ma, Xuanlong, Mammarella, Ivan, Martini, David, Macfarlane, Craig, Matteucci, Giorgio, Montagnani, Leonardo, Pabon-Moreno, Daniel E, Panigada, Cinzia, Papale, Dario, Pendall, Elise, Penuelas, Josep, Phillips, Richard P, Reich, Peter B, Rossini, Micol, Rotenberg, Eyal, Scott, Russell L, Stahl, Clement, Weber, Ulrich, Wohlfahrt, Georg, Wolf, Sebastian, Wright, Ian J, Yakir, Dan, Zaehle, Sönke, and Reichstein, Markus

Subjects
Life on Land, Carbon Cycle, Carbon Dioxide, Climate, Datasets as Topic, Ecosystem, Humidity, Plants, Principal Component Analysis, Water Cycle, General Science & Technology
Abstract

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

Published
2021

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