title = {{CTFS-ForestGEO}: a worldwide network monitoring forests in an era of global change},
  author = {Anderson-Teixeira, Kristina J. and Davies, Stuart J. and Bennett, Amy C. and Gonzalez-Akre, Erika B. and Muller-Landau, Helene C. and Joseph Wright, S. and Abu Salim, Kamariah and Almeyda Zambrano, Ang{\~e}lica M. and Alonso, Alfonso and Baltzer, Jennifer L. and Basset, Yves and Bourg, Norman A. and Broadbent, Eben N. and Brockelman, Warren Y. and Bunyavejchewin, Sarayudh and Burslem, David F. R. P. and Butt, Nathalie and Cao, Min and Cardenas, Dairon and Chuyong, George B. and Clay, Keith and Cordell, Susan and Dattaraja, Handanakere S. and Deng, Xiaobao and Detto, Matteo and Du, Xiaojun and Duque, Alvaro and Erikson, David L. and Ewango, Corneille E.N. and Fischer, Gunter A. and Fletcher, Christine and Foster, Robin B. and Giardina, Christian P. and Gilbert, Gregory S. and Gunatilleke, Nimal and Gunatilleke, Savitri and Hao, Zhanqing and Hargrove, William W. and Hart, Terese B. and Hau, Billy C.H. and He, Fangliang and Hoffman, Forrest M. and Howe, Robert W. and Hubbell, Stephen P. and Inman-Narahari, Faith M. and Jansen, Patrick A. and Jiang, Mingxi and Johnson, Daniel J. and Kanzaki, Mamoru and Kassim, Abdul Rahman and Kenfack, David and Kibet, Staline and Kinnaird, Margaret F. and Korte, Lisa and Kral, Kamil and Kumar, Jitendra and Larson, Andrew J. and Li, Yide and Li, Xiankun and Liu, Shirong and Lum, Shawn K.Y. and Lutz, James A. and Ma, Keping and Maddalena, Damian M. and Makana, Jean-Remy and Malhi, Yadvinder and Marthews, Toby and Mat Serudin, Rafizah and McMahon, Sean M. and McShea, William J. and Memiaghe, Her{v\` e} R. and Mi, Xiangcheng and Mizuno, Takashi and Morecroft, Michael and Myers, Jonathan A. and Novotny, Vojtech and de Oliveira, Alexandre A. and Ong, Perry S. and Orwig, David A. and Ostertag, Rebecca and den Ouden, Jan and Parker, Geoffrey G. and Phillips, Richard P. and Sack, Lawren and Sainge, Moses N. and Sang, Weiguo and Sri-ngernyuang, Kriangsak and Sukumar, Raman and Sun, I-Fang and Sungpalee, Witchaphart and Suresh, Hebbalalu Sathyanarayana and Tan, Sylvester and Thomas, Sean C. and Thomas, Duncan W. and Thompson, Jill and Turner, Benjamin L. and Uriarte, Maria and Valencia, Renato and Vallejo, Marta I. and Vicentini, Alberto and Vr{\v s}ka, Tom{\` a}{\v s} and Wang, Xihua and Wang, Xugao and Weiblen, George and Wolf, Amy and Xu, Han and Yap, Sandra and Zimmerman, Jess},
  journal = {Global Change Biology},
  year = {2015},
  number = {2},
  pages = {528--549},
  volume = {21},
  abstract = {Global change is impacting forests worldwide, threatening biodiversity and ecosystem services including climate regulation. Understanding how forests respond is critical to forest conservation and climate protection. This review describes an international network of 59 long-term forest dynamics research sites (CTFS-ForestGEO) useful for characterizing forest responses to global change. Within very large plots (median size 25 ha), all stems ≥1 cm diameter are identified to species, mapped, and regularly recensused according to standardized protocols. CTFS-ForestGEO spans 25°S–61°N latitude, is generally representative of the range of bioclimatic, edaphic, and topographic conditions experienced by forests worldwide, and is the only forest monitoring network that applies a standardized protocol to each of the world's major forest biomes. Supplementary standardized measurements at subsets of the sites provide additional information on plants, animals, and ecosystem and environmental variables. CTFS-ForestGEO sites are experiencing multifaceted anthropogenic global change pressures including warming (average 0.61 °C), changes in precipitation (up to ±30% change), atmospheric deposition of nitrogen and sulfur compounds (up to 3.8 g N m−2 yr−1 and 3.1 g S m−2 yr−1), and forest fragmentation in the surrounding landscape (up to 88% reduced tree cover within 5 km). The broad suite of measurements made at CTFS-ForestGEO sites makes it possible to investigate the complex ways in which global change is impacting forest dynamics. Ongoing research across the CTFS-ForestGEO network is yielding insights into how and why the forests are changing, and continued monitoring will provide vital contributions to understanding worldwide forest diversity and dynamics in an era of global change.},
  doi = {10.1111/gcb.12712},
  file = {pubs/Teixeira_GCB_2014.pdf},
  issn = {1365-2486},
  keywords = {biodiversity, Center for Tropical Forest Science (CTFS), climate change, demography, forest dynamics plot, Forest Global Earth Observatory (ForestGEO), long-term monitoring, spatial analysis},
  owner = {jkumar},
  timestamp = {2014.09.26},
  url = {},
  note = {\url{}}
  title = {Characterization and Classification of Vegetation Canopy Structure and Distribution within the {G}reat {S}moky {M}ountains {N}ational {P}ark using {LiDAR}},
  author = {Jitendra Kumar and Jon Weiner and William W. Hargrove and Steven P. Norman and Forrest M. Hoffman and Doug Newcomb},
  booktitle = {Proceedings of the 15th {IEEE} International Conference on Data Mining Workshops ({ICDMW} 2015)},
  year = {2015},
  editor = {Peng Cui and Jennifer Dy and Charu Aggarwal and Zhi-Hua Zhou and Alexander Tuzhilin and Hui Xiong and Xindong Wu},
  month = nov,
  organization = {Institute of Electrical and Electronics Engineers (IEEE)},
  pages = {1478--1485},
  publisher = {Conference Publishing Services (CPS)},
  abstract = {Vegetation canopy structure is a critically important habitat characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape provided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and characterized the vegetation canopy structures for 139,859 hectares (540 sq.\ miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.},
  day = {17},
  doi = {10.1109/ICDMW.2015.178},
  note = {\url{https;//10.1109/ICDMW.2015.178}},
  file = {pubs/Kumar_ICDM_20151117.pdf},
  owner = {jkumar},
  timestamp = {2016.12.27}
  title = {Root structural and functional dynamics in terrestrial biosphere models: evaluation and recommendations},
  author = {Warren, Jeffrey M. and Hanson, Paul J. and Iversen, Colleen M. and Kumar, Jitendra and Walker, Anthony P. and Wullschleger, Stan D. and Warren, Jeffrey and Hanson, Paul and Iversen, Colleen and Kumar, Jitendra and Walker, Anthony and Wullschleger, Stan},
  journal = {New Phytologist},
  year = {2015},
  number = {1},
  pages = {59--78},
  volume = {205},
  abstract = { There is wide breadth of root function within ecosystems that should be considered when modeling the terrestrial biosphere. Root structure and function are closely associated with control of plant water and nutrient uptake from the soil, plant carbon (C) assimilation, partitioning and release to the soils, and control of biogeochemical cycles through interactions within the rhizosphere. Root function is extremely dynamic and dependent on internal plant signals, root traits and morphology, and the physical, chemical and biotic soil environment. While plant roots have significant structural and functional plasticity to changing environmental conditions, their dynamics are noticeably absent from the land component of process-based Earth system models used to simulate global biogeochemical cycling. Their dynamic representation in large-scale models should improve model veracity. Here, we describe current root inclusion in models across scales, ranging from mechanistic processes of single roots to parameterized root processes operating at the landscape scale. With this foundation we discuss how existing and future root functional knowledge, new data compilation efforts, and novel modeling platforms can be leveraged to enhance root functionality in large-scale terrestrial biosphere models by improving parameterization within models, and introducing new components such as dynamic root distribution and root functional traits linked to resource extraction.},
  doi = {10.1111/nph.13034},
  note = {\url{}},
  file = {pubs/Warren_NewPhytologist_2015.pdf},
  issn = {1469-8137},
  keywords = {hydraulic redistribution, nitrogen uptake, root function, root model, root plasticity, water uptake},
  owner = {jkumar},
  timestamp = {2014.09.26},
  url = {}