Capability of models to predict leaf N and P across four seasons for six sub-tropical forest evergreen trees

Barta, 2006, The relationship between the methyl-erythritol phosphate pathway leading to emission of volatile isoprenoids and abscisic acid content in leaves, Am. Soc. Plant Biol., 141, 1676 Bell, 1984, Seasonal changes in foliar macronutrients (N, P, K, Ca and Mg) in Eucalyptus saligna Sm. and E. wandoo Blakely growing in rehabilitated bauxite mine soils of the Darling Range, Western Australia, Plant Soil, 81, 377, 10.1007/BF02323052 Booth, 2012, High sensitivity of future global warming to land carbon cycle processes, Environ. Res. Lett., 7, 10.1088/1748-9326/7/2/024002 Cai, 2009, Seasonal differences in leaf-level physiology give lianas a competitive advantage over trees in a tropical seasonal forest, Oecologia, 161, 25, 10.1007/s00442-009-1355-4 Campoy, 2011, Dormancy in temperate fruit trees in a global warming context: a review, Sci. Hortic., 130, 357, 10.1016/j.scienta.2011.07.011 Chapin, 1983, Seasonal changes in nitrogen and phosphorus fractions and autumn retranslocation in evergreen and deciduous taiga trees, Ecology, 64, 376, 10.2307/1937083 Chaturvedi, 2011, Leaf attributes and tree growth in a tropical dry forest, J. Veg. Sci., 22, 917, 10.1111/j.1654-1103.2011.01299.x Cherbuy, 2001, Internal remobilization of carbohydrates, lipids, nitrogen and phosphorus in the Mediterranean evergreen oak Quercus ilex, Tree Physiol., 21, 9, 10.1093/treephys/21.1.9 Cho, 2006, A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method, Remote Sens. Environ., 101, 181, 10.1016/j.rse.2005.12.011 Cho, 2007, Estimation of green grass/herb biomass from airborne hyperspectral imagery using spectral indices and partial least squares regression, Int. J. Appl. Earth Obs. Geoinf., 9, 414, 10.1016/j.jag.2007.02.001 Cho, 2009, Mapping beech (Fagus sylvatica L.) forest structure with airborne hyperspectral imagery, Int. J. Appl. Earth Obs. Geoinf., 11, 201, 10.1016/j.jag.2009.01.006 Cho, 2010, Evaluating variations of physiology-based hyperspectral features along a soil water gradient in a Eucalyptus grandis plantation, Int. J. Remote Sens., 31, 3143, 10.1080/01431160903154390 Cho, 2013, Assessing the effects of subtropical forest fragmentation on leaf nitrogen distribution using remote sensing data, Landscape Ecol., 28, 1479, 10.1007/s10980-013-9908-7 Clevers, 2013, Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3, Int. J. Appl. Earth Obs. Geoinf., 23, 344, 10.1016/j.jag.2012.10.008 Curran, 1989, Remote sensing of foliar chemistry, Remote Sens. Environ., 30, 271, 10.1016/0034-4257(89)90069-2 De Weirdt, 2012, Seasonal leaf dynamics for tropical evergreen forests in a process-based global ecosystem model, Geosci. Model Dev., 5, 1091, 10.5194/gmd-5-1091-2012 Dillen, 2012, Seasonal patterns of foliar reflectance in relation to photosynthetic capacity and color index in two co-occurring tree species, Quercus rubra and Betula papyrifera, Agric. For. Meteorol., 160, 60, 10.1016/j.agrformet.2012.03.001 Drake, 1997, More efficient plants: a consequence of rising atmospheric CO2?, Annu. Rev. Plant Physiol. Plant Mol. Biol., 48, 609, 10.1146/annurev.arplant.48.1.609 Elvidge, 1990, Visible and near infrared reflectance characteristics of dry plant materials, Int. J. Remote Sens., 11, 1775, 10.1080/01431169008955129 Evans, 1989, Photosynthesis and nitrogen relationships in leaves of C3 plants, Oecologia, 78, 9, 10.1007/BF00377192 Ferwerda, 2005, Nitrogen detection with hyperspectral normalized ratio indices across multiple plant species, Int. J. Remote Sens., 26, 4083, 10.1080/01431160500181044 Flores-de-Santiago, 2013, The influence of seasonality in estimating mangrove leaf chlorophyll-a content from hyperspectral data, Wetlands Ecol. Manage., 21, 193, 10.1007/s11273-013-9290-x Food and Agriculture Organization (FAO) of the United Nations (UN), 2012. Global forest land-use change 1990–2005. 169 59 p. <http://foris.fao.org/static/data/fra2010/FP169En.pdf>. Franco, 2005, Leaf functional traits of Neotropical savanna trees in relation to seasonal water deficit, Trees, 19, 326, 10.1007/s00468-004-0394-z Gao, 1996, NDWI - A normalised difference water index for remote sensing of vegetation liquid water from space, Remote Sens. Environ., 58, 257, 10.1016/S0034-4257(96)00067-3 Gitelson, A.A., Merzlyak, M.N., 2004. Non-destructive assessment of chlorophyll, carotenoid and anthocyanin content in higher plant leaves: principles and algorithms. Papers Nat. Resour. 77–94. <http://digitalcommons.unl.edu/natrespapers/263>. Gitelson, 2002, Assessing carotenoid content in plant leaves with reflectance spectroscopy, Photochem. Photobiol., 75, 272, 10.1562/0031-8655(2002)075<0272:ACCIPL>2.0.CO;2 Gitelson, A.A., Keydan, G.P., Merzlyak, M.N., 2006. Three-band model for noninvasive estimation of chlorophyll, carotenoids and anthocyanin contents in higher plant leaves. Papers Nat. Resour. 1–5. <http://digitalcommons.unl.edu/natrespapers/258>. Harris, 2013, Updated high-resolution grids of monthly climatic observations – the CRU TS3.10 Dataset, Int. J. Climatol., 34, 623, 10.1002/joc.3711 Horneck, 1998, Determination of total nitrogen in plant tissue, 81 Huang, 2004, Estimating foliage nitrogen concentration from HYMAP data using continuum removal analysis, Remote Sens. Environ., 93, 18, 10.1016/j.rse.2004.06.008 Huber, 2008, Estimating foliar biochemistry from hyperspectral data in mixed forest canopy, For. Ecol. Manage., 256, 491, 10.1016/j.foreco.2008.05.011 Isaac, 1998, Elemental determination by inductively coupled plasma, 165 Johnson, 2001, Nitrogen influence on fresh-leaf NIR spectra, Remote Sens. Environ., 78, 314, 10.1016/S0034-4257(01)00226-7 Jordan, 1985 Kirschbaum, 2000, Forest growth and species distribution in a changing climate, Tree Physiol., 20, 309, 10.1093/treephys/20.5-6.309 Knox, 2011, Dry season mapping of savanna forage quality, using the hyperspectral Carnegie Airborne Observatory sensor, Remote Sens. Environ., 115, 1478, 10.1016/j.rse.2011.02.007 Knyazikhin, 2012, Hyperspectral remote sensing of foliar nitrogen content, Proc. Nat. Acad. Sci. United States of America, E185 Kokaly, 2001, Investigating a physical basis for spectroscopic estimates of leaf nitrogen concentration, Remote Sens. Environ., 75, 153, 10.1016/S0034-4257(00)00163-2 Kokaly, 1999, Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression, Remote Sens. Environ., 67, 267, 10.1016/S0034-4257(98)00084-4 Kokaly, 2009, Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies, Remote Sens. Environ., 113, S78, 10.1016/j.rse.2008.10.018 Kumar, 2001, Imaging spectroscopy and vegetation science Lin, 2010, Nutrient conservation strategies of a mangrove species Rhizophora stylosa under nutrient limitation, Plant Soil, 326, 469, 10.1007/s11104-009-0026-x Lukac, 2010, Global climate change and tree nutrition: effects of elevated CO2 and temperature, Tree Physiol., 30, 1209, 10.1093/treephys/tpq040 McDonald, 2008 Middleton B.J., Bailey A.K., 2008. Water resources of South Africa, 2005 Study (WR2005) and Book of Maps. In: Water Research Commission Reports No.TT381/08 and TT382/08. Water Research Commission, Pretoria, South Africa. Millard, 2010, Nitrogen storage and remobilization by trees: ecophysiological relevance in a changing world, Tree Physiol., 30, 1083, 10.1093/treephys/tpq042 Mucina, 2006 Mutanga, 2007, Estimating and mapping grass phosphorus concentration in an African savanna using hyperspectral image data, Int. J. Remote Sens., 28, 4897, 10.1080/01431160701253253 Mutanga, 2004, Narrow band vegetation indices overcome the saturation problem in biomass estimation, Int. J. Remote Sens., 19, 3999, 10.1080/01431160310001654923 Mutanga, 2007, Red edge shift and biochemical content in grass canopies, ISPRS J. Photogrammetry Remote Sens., 62, 34, 10.1016/j.isprsjprs.2007.02.001 Nakaji, 2006, Seasonal changes in the relationship between photochemical reflectance index and photosynthetic light use efficiency of Japanese larch needles, Int. J. Remote Sens., 27, 493, 10.1080/01431160500329528 Ollinger, 2008, Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: functional relations and potential climate feedbacks, Proc. Nat. Acad. Sci. United States of America, 105, 19336, 10.1073/pnas.0810021105 Ollinger, 2013, Nitrogen cycling, forest canopy reflectance and emergent properties of ecosystems, Proc. Nat. Acad. Sci. United States of America, 110, E2437, 10.1073/pnas.1304176110 Partridge, 2010, The geomorphic provinces of South Africa, Lesotho and Swaziland: a physiographic subdivision for earth and environmental scientists, Trans. R. Soc. South Africa, 65, 1, 10.1080/00359191003652033 Penuelas, 1995, Semiempirical indexes to assess carotenoids chlorophyll-a ratio from leaf spectral reflectance, Photosynthetica, 31, 221 Ramoelo, 2011, Water-removed spectra increase the retrieval accuracy when estimating savanna grass nitrogen and phosphorus concentrations, ISPRS J. Photogrammetry Remote Sens., 66, 408, 10.1016/j.isprsjprs.2011.01.008 Ramoelo, 2012, Regional estimation of savanna grass nitrogen using the red-edge band of the spaceborne RapidEye sensor, Int. J. Appl. Earth Obs. Geoinf., 19, 151, 10.1016/j.jag.2012.05.009 Ramoelo, 2013, Savanna grass nitrogen to phosphorous ratio estimation using field spectroscopy and the potential for estimation with imaging spectroscopy, Int. J. Appl. Earth Obs. Geoinf., 23, 334, 10.1016/j.jag.2012.10.009 Reef, 2010, Nutrition of mangroves, Tree Physiol., 30, 1148, 10.1093/treephys/tpq048 Reich, 2004, Global patterns of plant leaf N and P in relation to temperature and latitude, Proc. Natl. Acad. Sci. USA, 101, 11001, 10.1073/pnas.0403588101 Richardson, 2013, Climate change, phenology, and phenological control of vegetation feedbacks to the climate system, Agric. For. Meteorol., 169, 156, 10.1016/j.agrformet.2012.09.012 Rouse, J., Haas, R., Schell, J., Deering, D., 1973. Monitoring vegetation systems in the great plains with ERTS. Third ERTS Symposium, United States of America, National Aeronautics and Space Administration (NASA) SP-351 I 309–317. Sabaté, 1995, Nutrient content in Quercus ilex canopies: seasonal and spatial variation within a catchment, Plant Soil, 168–169, 297, 10.1007/BF00029341 Sardans, 2012, The role of plants in the effects of global change on nutrient availability and stoichiometry in the plant-soil system, Plant Physiol., 160, 1741, 10.1104/pp.112.208785 Schlerf, 2010, Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy, Int. J. Appl. Earth Obs. Geoinf., 12, 17, 10.1016/j.jag.2009.08.006 Seppälä, R., Buck, A., Katila, P., 2009. Adaptation of forests and people to climate change. A Global Assessment Report. IUFRO World Series Volume 22. Helsinki. 224 p. Sharma, 1983, Mineral content of leaves of some common tropical forest trees and their associated soils in Ibadan, Nigeria, Can. J. For. Res. Skidmore, 2010, Forage quality of savannas – simultaneously mapping foliar protein and polyphenols for trees and grass using hyperspectral imagery, Remote Sens. Environ., 114, 64, 10.1016/j.rse.2009.08.010 Smith, 2002, Direct estimation of aboveground forest productivity through hyperspectral remote sensing of canopy nitrogen, Ecol. Appl., 12, 1286, 10.1890/1051-0761(2002)012[1286:DEOAFP]2.0.CO;2 Sokolic, F., 2006. The use of satellite remote sensing to determine the spatial and temporal distribution of surface water on the Eastern Shores of Lake St. Lucia. M.Sc. thesis. Master of Science, University of KwaZulu-Natal. Durban: UKZN. Townsend, 2003, Application of imaging spectroscopy to mapping canopy nitrogen in the forest of the central Appalachian Mountains using Hyperion and AVIRIS, IEEE Trans. Geosci. Remote Sens., 41, 1347, 10.1109/TGRS.2003.813205 Tucker, 1979, Red and photographic infrared linear combinations for monitoring vegetation, Remote Sens. Environ., 8, 127, 10.1016/0034-4257(79)90013-0 Ullah, 2012, Estimation of grassland biomass and nitrogen using MERIS data, Int. J. Appl. Earth Obs. Geoinf., 19, 196, 10.1016/j.jag.2012.05.008 United States Department of Energy (US DOE), 2012. Research priorities for tropical ecosystems under climate change workshop report. US Department of Energy Office of Science DOE/SC-0153 U.S. Department of Energy Office of Science. <http://science.energy.gov/ber/news-and-resources/>. Yasamura, 2011, Temporal variation in leaf nitrogen partitioning of broad-leaved evergreen tree, Quercus myrsinaefolia, J. Plant. Res., 124, 115, 10.1007/s10265-010-0358-x Yoder, 1995, Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500nm) at leaf and canopy scales, Remote Sens. Environ., 53, 199, 10.1016/0034-4257(95)00135-N Zhang, 2007, Retrieving seasonal variation in chlorophyll content of overstory and understory sugar maple leaves from leaf-level hyperspectral data, Can. J. Remote Sens., 33, 406, 10.5589/m07-037 Zhou, 2003, Relation between interannual variations in satellite measures of northern forest greenness and climate between 1982 and 1999, J. Geophys. Res., 108, 1, 10.1029/2002JD002510