Abstract :

Among the natural disturbances, drought may cause significant change in forest ecosystems by shifting phenology and productivity. Digital cameras have been used in phenological observations for their high accuracy and the colour index values (digital-number of red, green and blue) derived from long-term continuous digital camera imagery are useful as proxies for investigating a forest canopy’s response to drought. Here, we examine the interaction between colour indices (the strength of red (Sred), the strength of green (Sgreen), green excess index (GEI)), productivity (gross primary productivity (GPP)) and drought (standardised precipitation evapotranspiration index (SPEI)) and climatic factors. We use forest canopy images derived from a digital camera and flux tower-based productivity from 2010 to 2016 to show the rainforest’s responses to drought in phenology and productivity. The SPEI indicated the occurrence of drought condition in 2014. The lowest values of the SPEI (-0.403 mmday-1), and total precipitation (1062 mmyr-1), and the highest values of average air temperature (21.3°C), potential evapotranspiration (3.31 mmday-1) and rain use efficiency (2.26 gCL-1) were found in 2014. Leaf color variation period (CVP) become longer with an advance in foliage green-up after drought. The peak GEI values were found at the end of the CVPs. The GPP and the Sgreen had positive and the Sred had negative relationship with drought index. The GPP dropped during the drought and bounced back after the drought due to a longer leaf CVP. The Sgreen and GEI were significantly (p<0.05) related to GPP during the drought. During the CVP of the drought, the Sgreen and GEI were significantly correlated (p<0.05) with total P, PET and average Ta, meanwhile, there was only a significant relationship (p<0.05) between the GPP with PET and avg Ta. Among the variables, the GPP was more significant (p < 0.001) with avg Ta. There was also a relationship between the colour indices and GPP with climatic factors on a yearly time series. Our results indicate an understanding of the phenology and productivity response of rainforests to drought, which might be useful for ecologists when predicting the effects of future climatic change on rainforest phenology and productivity.

---

Keywords :

Colour indices; Digital camera images; Drought; Gross primary productivity (GPP); leaf colour variation period (CVP); Standardised Precipitation Evapotranspiration Index (SPEI)

---

References :

1. Ahrends, H.E., Brügger, R., Stöckli, R., Schenk, J., Michna, P., Jeanneret, F., Wanner, H., Eugster, W., 2008. Quantitative phenological observations of a mixed beech forest in northern Switzerland with digital photography. J. Geophys. Res. Biogeosciences 113, 1–11. https://doi.org/10.1029/2007JG000650
2. Alberton, B., Torres, S., Cancian, L.F., Borges, B.D., Almeida, J., Mariano, G.C., Patricia, L., Morellato, C., 2017. Introducing digital cameras to monitor plant phenology in the tropics : applications for conservation. Perspect. Ecol. Conserv. 15, 82–90. https://doi.org/10.1016/j.pecon.2017.06.004
3. Anderson, L.O., Malhi, Y., Aragão, L.E.O.C., Ladle, R., Arai, E., Barbier, N., Phillips, O., 2010.
4. Remote sensing detection of droughts in Amazonian forest canopies. New Phytol. 187, 733–750.
https://doi.org/10.1111/j.1469-8137.2010.03355.x
5. Badeck, F.W., Bondeau, A., Böttcher, K., Doktor, D., Lucht, W., Schaber, J., Sitch, S., 2004.
6. Responses of spring phenology to climate change. New Phytol. 162, 295–309. https://doi.org/10.1111/j.1469-8137.2004.01059.x
7. Bernal, M., Estiarte, M., Peñuelas, J., 2011. Drought advances spring growth phenology of the Mediterranean shrub Erica multiflora. Plant Biol. 13, 252–257. https://doi.org/10.1111/j.1438-8677.2010.00358.x
8. Bogdziewicz, M., Fernández‐Martínez, M., Espelta, J.M., Ogaya, R., Penuelas, J., 2020. Is forest fecundity resistant to drought? Results from an 18‐year rainfall‐reduction experiment. New Phytol. https://doi.org/10.1111/nph.16597
9. Cao, Z., Li, Y., Liu, Y., Chen, Y., Wang, Y., 2018. When and where did the Loess Plateau turn “green”? Analysis of the tendency and breakpoints of the normalized difference vegetation index. L. Degrad. Dev. 29, 162–175. https://doi.org/10.1002/ldr.2852
10. Carter, J.M., Orive, M.E., Gerhart, L.M., Stern, J.H., Marchin, R.M., Nagel, J., Ward, J.K., 2017.
11. Warmest extreme year in U.S. history alters thermal requirements for tree phenology. Oecologia 183, 1197–1210. https://doi.org/10.1007/s00442-017-3838-z
12. Caudullo, G., Barredo, J.I., 2019. A georeferenced dataset of drought and heat-induced tree mortality in Europe. One Ecosyst. 4. https://doi.org/10.3897/oneeco.4.e37753
13. Čehulić, I., Sever, K., Bogdan, I.K., Jazbec, A., Škvorc, Ž., Bogdan, S., 2019. Drought impact on leaf phenology and spring frost susceptibility in a Quercus robur L. provenance trial. Forests 10. https://doi.org/10.3390/f10010050
14. Ciais, P., Reichstein, M., Viovy, N., Granier, A., Ogée, J., Allard, V., Aubinet, M., Buchmann, N., Bernhofer, C., Carrara, A., Chevallier, F., De Noblet, N., Friend, A.D., Friedlingstein, P., Grünwald, T., Heinesch, B., Keronen, P., Knohl, A., Krinner, G., Loustau, D., Manca, G., Matteucci, G., Miglietta, F., Ourcival, J.M., Papale, D., Pilegaard, K., Rambal, S., Seufert, G., Soussana, J.F., Sanz, M.J., Schulze, E.D., Vesala, T., Valentini, R., 2005.
15. Europe-wide reduction in primary productivity caused by the heat and drought in 2003.
Nature 437, 529–533. https://doi.org/10.1038/nature03972
16. Copeland, S.M., HarrISon, S. p., LatIMer, andrew M., DaMScHen, ellen I., ESkelInen, anu M., Fernandez-GoInG, B., SpaSoJevIc, M.J., Anacker, B. l., THorne, J.H., 2016. Ecological effects of extreme drought on Californian herbaceous plant communities. Ecol. Monogr. 86, 295–311.
17. Dahlin, K.M., Ponte, D. Del, Setlock, E., Nagelkirk, R., 2017. Global patterns of drought deciduous phenology in semi-arid and savanna-type ecosystems. Ecography (Cop.). 40, 314–323. https://doi.org/10.1111/ecog.02443
18. Dai, A., 2013. Increasing drought under global warming in observations and models. Nat. Clim. Chang. 3, 52–58. https://doi.org/10.1038/nclimate1633
19. Dai, J., Wang, H., Ge, Q., 2014. The spatial pattern of leaf phenology and its response to climate change in China. Int. J. Biometeorol. 58, 521–528. https://doi.org/10.1007/s00484-013-0679-2
20. Fei, X., Song, Q., Zhang, Y., Liu, Y., Sha, L., Yu, G., Zhang, L., Duan, C., Deng, Y., Wu, C., Lu, Z., Luo, K., Chen, A., Xu, K., Liu, W., Huang, H., Jin, Y., Zhou, R., Li, J., Lin, Y.,
21. Zhou, L., Fu, Y., Bai, X., Tang, X., Gao, J., Zhou, W., Grace, J., 2018. Carbon exchanges and their responses to temperature and precipitation in forest ecosystems in Yunnan, Southwest China. Sci. Total Environ. 616–617, 824–840.
https://doi.org/10.1016/j.scitotenv.2017.10.239
22. Fensham, R.J., Laffineur, B., Allen, C.D., 2019. To what extent is drought-induced tree mortality a natural phenomenon? Glob. Ecol. Biogeogr. 28, 365–373. https://doi.org/10.1111/geb.12858
23. Frank, Dorothea, Reichstein, M., Bahn, M., Thonicke, K., Frank, David, Mahecha, M.D., Smith, P., van der Velde, M., Vicca, S., Babst, F., Beer, C., Buchmann, N., Canadell, J.G., Ciais,
24. P., Cramer, W., Ibrom, A., Miglietta, F., Poulter, B., Rammig, A., Seneviratne, S.I., Walz, A., Wattenbach, M., Zavala, M.A., Zscheischler, J., 2015. Effects of climate extremes on the terrestrial carbon cycle: Concepts, processes and potential future impacts. Glob. Chang. Biol. 21, 2861–2880. https://doi.org/10.1111/gcb.12916
25. Gamoun, M., 2016. Rain Use Efficiency, Primary Production and Rainfall Relationships in Desert Rangelands of Tunisia. L. Degrad. Dev. 27, 738–747. https://doi.org/10.1002/ldr.2418
26. George H. Hargreaves, Zohrab A. Samani, 1985. Reference Crop Evapotranspiration from Temperature. Appl. Eng. Agric. 1, 96–99. https://doi.org/10.13031/2013.26773
27. Gillespie, A.R., Kahle, A.B., Walker, R.E., 1987. Color enhancement of highly correlated images. II. Channel ratio and “chromaticity” transformation techniques. Remote Sens. Environ. 22, 343–365.
https://doi.org/10.1016/0034-4257(87)90088-5
28. Gilmanov, T.G., Soussana, J.F., Aires, L., Allard, V., Ammann, C., Balzarolo, M., Barcza, Z., Bernhofer, C., Campbell, C.L., Cernusca, A., Cescatti, A., Clifton-Brown, J., Dirks, B.O.M., Dore, S., Eugster, W., Fuhrer, J., Gimeno, C., Gruenwald, T., Haszpra, L., Hensen, A., Ibrom, A., Jacobs, A.F.G., Jones, M.B., Lanigan, G., Laurila, T., Lohila, A., G.Manca, Marcolla, B., Nagy, Z., Pilegaard, K., Pinter, K., Pio, C., Raschi, A., Rogiers, N., Sanz,
29. M.J., Stefani, P., Sutton, M., Tuba, Z., Valentini, R., Williams, M.L., Wohlfahrt, G., 2007. Partitioning European grassland net ecosystem CO2 exchange into gross primary productivity and ecosystem respiration using light response function analysis. Agric. Ecosyst. Environ. 121, 93–120. https://doi.org/10.1016/j.agee.2006.12.008
30. Gonçalves, N.B., Lopes, A.P., Dalagnol, R., Wu, J., Pinho, D.M., Nelson, B.W., 2020. Both near-surface and satellite remote sensing confirm drought legacy effect on tropical forest leaf phenology after 2015/2016 ENSO drought. Remote Sens. Environ. 237, 111489. https://doi.org/10.1016/j.rse.2019.111489
31. Gouveia, C.M., Trigo, R.M., Beguería, S., Vicente-Serrano, S.M., 2017. Drought impacts on vegetation activity in the Mediterranean region: An assessment using remote sensing data and multi-scale drought indicators. Glob. Planet. Change 151, 15–27. https://doi.org/10.1016/j.gloplacha.2016.06.011
32. Güsewell, S., Furrer, R., Gehrig, R., Pietragalla, B., 2017. Changes in temperature sensitivity of spring phenology with recent climate warming in Switzerland are related to shifts of the preseason. Glob. Chang. Biol. 23, 5189–5202. https://doi.org/10.1111/gcb.13781
33. Hollinger, D.Y., Kelliher, F.M., Byers, J.N., Hunt, J.E., McSeveny, T.M., Weir, P.L., 1994. Carbon dioxide exchange between an undisturbed old-growth temperate forest and the atmosphere. Ecology 75, 134–150.
https://doi.org/10.2307/1939390
34. Huang, F., Wang, P., Chang, S., Li, B., 2018. Rain use efficiency changes and its effects on land surface phenology in the Songnen Plain, Northeast China 16. https://doi.org/10.1117/12.2325086
35. Huxman, T.E., Smith, M.D., Fay, P.A., Knapp, A.K., Shaw, M.R., Lolk, M.E., Smith, S.D., Tissue, D.T., Zak, J.C., Weltzin, J.F., Pockman, W.T., Sala, O.E., Haddad, B.M., Harte, J., Koch, G.W., Schwinning, S., Small, E.E., Williams, D.G., 2004. Convergence across biomes to a common rain-use efficiency. Nature 429, 651–654.
https://doi.org/10.1038/nature02561
36. Ide, R., Nakaji, T., Motohka, T., Oguma, H., 2011. Advantages of visible-band spectral remote sensing at both satellite and near-surface scales for monitoring the seasonal dynamics of GPP in a Japanese larch forest. J. Agric. Meteorol 67 (2), 75–84. https://doi.org/10.2480/agrmet.67.2.4
37. Inoue, T., Nagai, S., Saitoh, T.M., Muraoka, H., Nasahara, K.N., Koizumi, H., 2014. Detection of the different characteristics of year-to-year variation in foliage phenology among deciduous broad-leaved tree species by using daily continuous canopy surface images. Ecol. Inform. 22, 58–68. https://doi.org/10.1016/j.ecoinf.2014.05.009
38. Lauenroth, W.K., Burke, I.C., Paruelo, J.M., 2000. Patterns of production and precipitation-use efficiency of winter wheat and native grasslands in the central Great Plains of the United States. Ecosystems 3, 344–351. https://doi.org/10.1007/s100210000031
39. Li, H., Aide, T.M., Ma, Y., Liu, W., Cao, M., 2007. Demand for rubber is causing the loss of high diversity rain forest in SW China. Biodivers. Conserv. 16, 1731–1745. https://doi.org/10.1007/s10531-006-9052-7
40. Li, M.Y., Fang, L.D., Duan, C.Y., Cao, Y., Yin, H., Ning, Q.R., Hao, G.Y., 2020. Greater risk of hydraulic failure due to increased drought threatens pine plantations in Horqin Sandy Land of northern China. For. Ecol. Manage. 461. https://doi.org/10.1016/j.foreco.2020.117980
41. Liu, D., Zhang, C., Ogaya, R., Estiarte, M., Peñuelas, J., 2020. Effects of decadal experimental drought and climate extremes on vegetation growth in Mediterranean forests and shrublands. J. Veg. Sci. 13, jvs.12902. https://doi.org/10.1111/jvs.12902
42. McKee, T.B., Doesken, N.J., Kleist, J., 1993. The relationship of drought frequency and duration to time scales. Eighth Conf. Appl. Clim. Anaheim, 179–184.
43. Myo, S.T.Z., Zhang, Y., Song, Q.H., Deng, Y., Fei, X., Zhou, R., Lin, Y., Zhou, L., Zhang, P., 2019. Analysis of canopy temperature depression between tropical rainforest and rubber plantation in Southwest China. IForest 12, 518–526. https://doi.org/10.3832/ifor3101-012
44. Nagai, S., Ichie, T., Yoneyama, A., Kobayashi, H., Inoue, T., Ishii, R., Suzuki, R., Itioka, T., 2016. Usability of time-lapse digital camera images to detect characteristics of tree phenology in a tropical rainforest. Ecol. Inform. 32, 91–106.
https://doi.org/10.1016/j.ecoinf.2016.01.006
45. Nagai, S., Saitoh, T.M., Kurumado, K., Tamagawa, I., Kobayashi, H., Inoue, T., Suzuki, R., Gamo, M., Muraoka, H., Nishida Nasahara, K., 2013. Detection of Bio-Meteorological Year-to-Year Variation by Using Digital Canopy Surface Images of a Deciduous Broad-Leaved Forest. SOLA 9, 106–110. https://doi.org/10.2151/sola.2013-024
46. Ogaya, R., Liu, D., Barbeta, A., Peñuelas, J., 2020. Stem Mortality and Forest Dieback in a 20Years Experimental Drought in a Mediterranean Holm Oak Forest. Front. For. Glob. Chang. 2, 1–9. https://doi.org/10.3389/ffgc.2019.00089
47. Onyewotu, L.O.Z., Stigter, C.J., Oladipo, E.O., Owonubi, J.J., 1998. Yields of millet between shelterbelts in semi-arid northern Nigeria, with a traditional and a scientific method of determining sowing date, and at two levels of organic manuring. Netherlands J. Agric. Sci. 46, 53–64.
48. Palmer, W.C., 1965. Meteorological drought. Pereira, J.S., Mateus, J.A., Aires, L.M., Pita, G., Pio, C., David, J.S., Andrade, V., Banza, J., David, T.S., Paço, T.A., Rodrigues, A., 2007. Net ecosystem carbon exchange in three contrasting Mediterranean ecosystems – The effect of drought. Biogeosciences 4, 791–802.
https://doi.org/10.5194/bg-4-791-2007
49. Pollastrini, M., Puletti, N., Selvi, F., Iacopetti, G., Bussotti, F., 2019. Widespread Crown Defoliation After a Drought and Heat Wave in the Forests of Tuscany (Central Italy) and Their Recovery—A Case Study From Summer 2017. Front. For. Glob. Chang. 2, 1–8. https://doi.org/10.3389/ffgc.2019.00074
50. Prevéy, J., Vellend, M., Rüger, N., Hollister, R.D., Bjorkman, A.D., Myers-Smith, I.H., Elmendorf, S.C., Clark, K., Cooper, E.J., Elberling, B., Fosaa, A.M., Henry, G.H.R., Høye, T.T., Jónsdóttir, I.S., Klanderud, K., Lévesque, E., Mauritz, M., Molau, U., Natali, S.M.,
51. Oberbauer, S.F., Panchen, Z.A., Post, E., Rumpf, S.B., Schmidt, N.M., Schuur, E.A.G., Semenchuk, P.R., Troxler, T., Welker, J.M., Rixen, C., 2017. Greater temperature sensitivity of plant phenology at colder sites: implications for convergence across northern latitudes. Glob. Chang. Biol. 23, 2660–2671. https://doi.org/10.1111/gcb.13619
52. Saatchi, S., Asefi-Najafabady, S., Malhi, Y., Aragão, L.E.O.C., Anderson, L.O., Myneni, R.B., Nemani, R., 2013. Persistent effects of a severe drought on Amazonian forest canopy. Proc. Natl. Acad. Sci. U. S. A. 110, 565–570. https://doi.org/10.1073/pnas.1204651110
53. Salinger, M.J., Stigter, C.J., Das, H.P., 2000. Agrometeorological adaptation strategies to increasing climate variability and climate change. Agric. For. Meteorol. 103, 167–184.
54. Sonnentag, O., Detto, M., Vargas, R., Ryu, Y., Runkle, B.R.K., Kelly, M., Baldocchi, D.D., 2011. Tracking the structural and functional development of a perennial pepperweed
55. (Lepidium latifolium L.) infestation using a multi-year archive of webcam imagery and eddy covariance measurements. Agric. For. Meteorol. 151, 916–926. https://doi.org/10.1016/j.agrformet.2011.02.011
56. Sonnentag, O., Hufkens, K., Teshera-sterne, C., Young, A.M., Friedl, M., Braswell, B.H., Milliman, T., Keefe, J.O., Richardson, A.D., 2012. Digital repeat photography for phenological research in forest ecosystems. Agric. For. Meteorol. 152, 159–177. https://doi.org/10.1016/j.agrformet.2011.09.009
57. Stovall, A.E.L., Shugart, H., Yang, X., 2019. Tree height explains mortality risk during an intense drought. Nat. Commun. 10. https://doi.org/10.1038/s41467-019-12380-6
58. Toomey, M., Friedl, M.A., Frolking, S., Hufkens, K., Klosterman, S., Sonnentag, O., Baldocchi, D.D., Bernacchi, C.J., Biraud, S.C., Bohrer, G., Brzostek, E., Burns, S.P., Coursolle, C.,
59. Hollinger, D.Y., Margolis, H.A., Mccaughey, H., Monson, R.K., Munger, J.W., Pallardy, S., Phillips, R.P., Torn, M.S., Wharton, S., Zeri, M., Richardson, A.D., 2015. Greenness indices from digital cameras predict the timing and seasonal dynamics of canopy-scale photosynthesis. Ecol. Appl. 25, 99–115.
60. Vicente-Serrano, S.M., Beguería, S., López-Moreno, J.I., 2010. A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. J. Clim. 23, 1696–1718.
https://doi.org/10.1175/2009JCLI2909.1
61. Vicente-Serrano, S.M., Beguería, S., Lorenzo-Lacruz, J., Camarero, J.J., López-Moreno, J.I., Azorin-Molina, C., Revuelto, J., Morán-Tejeda, E., Sanchez-Lorenzo, A., 2012. Performance of drought indices for ecological, agricultural, and hydrological applications. Earth Interact. 16. https://doi.org/10.1175/2012EI000434.1
62. Vicente-Serrano, S.M., Gouveia, C., Camarero, J.J., Beguería, S., Trigo, R., López-Moreno, J.I., Azorín-Molina, C., Pasho, E., Lorenzo-Lacruz, J., Revuelto, J., Morán-Tejeda, E., SanchezLorenzo, A., 2013. Response of vegetation to drought time-scales across global land biomes. Proc. Natl. Acad. Sci. U. S. A. 110, 52–57.
https://doi.org/10.1073/pnas.1207068110
63. Vitasse, Y., Porté, A.J., Kremer, A., Michalet, R., Delzon, S., 2009. Responses of Canopy Duration to Temperature Changes in Four Temperate Tree Species_Relative Contributions of Spring and Autumn Leaf Phenology. Oecologia 161, 187–198. https://doi.org/110.1007/s00442-009- 1363-4
64. Westergaard-Nielsen, A., Lund, M., Hansen, B.U., Tamstorf, M.P., 2013. Camera derived vegetation greenness index as proxy for gross primary production in a low Arctic wetland area. ISPRS J. Photogramm. Remote Sens. 86, 89–99.
https://doi.org/10.1016/j.isprsjprs.2013.09.006
65. Woebbecke, D.M., Meyer, G.E., Bargen, K. Von, Mortensen, D.A., 1995. Color Indices for Weed Identification Under Various Soil, Residue, and Lighting Conditions. Trans. ASAE 38, 259–269. https://doi.org/10.13031/2013.27838
66. Xu, C., McDowell, N.G., Fisher, R.A., Wei, L., Sevanto, S., Christoffersen, B.O., Weng, E., Middleton, R.S., 2019. Increasing impacts of extreme droughts on vegetation productivity under climate change. Nat. Clim. Chang. 9, 948–953. https://doi.org/10.1038/s41558-019-0630-6
67. Yan, L., Luo, Y., Sherry, R.A., Bell, J.E., Zhou, X., Xia, J., 2014. Rain use efficiency as affected by climate warming and biofuel harvest: Results from a 12-year field experiment. GCB Bioenergy 6, 556–565.
https://doi.org/10.1111/gcbb.12081
68. Yu, R., Schwartz, M.D., Donnelly, A., Liang, L., 2015. An observation-based progression modeling approach to spring and autumn deciduous tree phenology. Int. J. Biometeorol. 335–349. https://doi.org/10.1007/s00484-015-1031-9
69. Yu, Z., Lu, C., Cao, P., Tian, H., Hessl, A., Pederson, N., 2018. Earlier leaf-flushing suppressed ecosystem productivity by draining soil water in the Mongolian Plateau. Agric. For. Meteorol. 250–251, 1–8.
https://doi.org/10.1016/j.agrformet.2017.11.035
70. Zahir, A., Abbasi, B.H., Adil, M., Anjum, S., Zia, M., Ihsan-Ul-Haq, 2014. Synergistic effects of drought stress and photoperiods on phenology and secondary metabolism of Silybum marianum. Appl. Biochem. Biotechnol. 174, 693–707. https://doi.org/10.1007/s12010-0141098-5
71. Zhang, Q., Kong, D., Singh, V.P., Shi, P., 2017. Response of vegetation to different time-scales drought across China: Spatiotemporal patterns, causes and implications. Glob. Planet. Change 152, 1–11.
https://doi.org/10.1016/j.gloplacha.2017.02.008
72. Zhang, Y., Xiao, X., Zhou, S., Ciais, P., McCarthy, H., Luo, Y., 2016. Canopy and physiological controls of GPP during drought and heat wave. Geophys. Res. Lett. 43, 3325–3333. https://doi.org/10.1002/2016GL068501
73. Zhao, A., Zhang, A., Liu, J., Feng, L., Zhao, Y., 2019. Assessing the effects of drought and “Grain for Green” Program on vegetation dynamics in China’s Loess Plateau from 2000 to 2014. Catena 175, 446–455.
https://doi.org/10.1016/j.catena.2019.01.013
74. Zhao, A., Zhanga, A., Caoc, S., Liud, X., Liue, J., Chenga, D., 2018. Responses of vegetation productivity to multi-scale drought in Loess Plateau, China. Catena 163, 165–171. https://doi.org/10.1016/j.catena.2017.12.016
75. Zhao, Junbin, Zhang, Y., Tan, Z., Song, Q., Liang, N., Yu, L., Zhao, Junfu, 2012. Using digital cameras for comparative phenological monitoring in an evergreen broad-leaved forest and a seasonal rain forest. Ecol. Inform. 10, 65–72. https://doi.org/10.1016/j.ecoinf.2012.03.001
76. Zhao, Y., Wang, X., Vázquez-Jiménez, R., 2018. Evaluating the performance of remote sensed rain-use efficiency as an indicator of ecosystem functioning in semi-arid ecosystems. Int. J. Remote Sens. 39, 3344–3362.
https://doi.org/10.1080/01431161.2018.1439598
77. Zhou, R., Zhang, Y., Song, Q., Lin, Y., Sha, L., Jin, Y., 2019. Relationship between gross primary production and canopy colour indices from digital camera images in a rubber (Hevea brasiliensis ) plantation , Southwest China Forest Ecology and Management Relationship between gross primary production and canopy colou. For. Ecol. Manage. 437, 222–231. https://doi.org/10.1016/j.foreco.2019.01.019