Uncertainties involved in leaf fall phenology detected by digital camera

Abstract We evaluated the uncertainty in the estimation of year-to-year variability in the timing of leaf fall detected by the analysis of red, green and blue (RGB) values extracted from daily phenological images in a deciduous broad-leaved forest in Japan. We examined (1) the spatial distribution of individual tree species within a 1-ha permanent plot and the spatio-temporal variability of leaf litter of various species for 8 years; and (2) the relationship between the year-to-year variability of leaf fall detected by leaf litter and that detected by phenological images of various species. Uncertainties were caused by (1) the heterogeneous distribution of each species within the whole forest community; (2) the year-to-year variability of the timing of leaf fall among species; and (3) differences in leaf colouring and leaf fall patterns among species. Our results indicate the importance of integrating RGB analysis of each species and of the whole canopy on the basis of spatial locations of individuals and proportions of tree species within a forest to reduce uncertainty.

[1]  Kenlo Nishida Nasahara,et al.  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 , 2014, Ecol. Informatics.

[2]  Kihachiro Kikuzawa,et al.  The basis for variation in leaf longevity of plants. , 1995 .

[3]  Takeshi Ohta,et al.  Climate change and extension of the Ginkgo biloba L. growing season in Japan , 2003 .

[4]  Annette Menzel,et al.  Growing season extended in Europe , 1999, Nature.

[5]  Sylvain Delzon,et al.  Responses of canopy duration to temperature changes in four temperate tree species: relative contributions of spring and autumn leaf phenology , 2009, Oecologia.

[6]  T. Akiyama,et al.  Temporal and spatial variability of soil respiration in a cool temperate broad-leaved forest 1. Measurement of spatial variance and factor analysis , 2003 .

[7]  Richard B Primack,et al.  Leaf-out phenology of temperate woody plants: from trees to ecosystems. , 2011, The New phytologist.

[8]  I. Janssens,et al.  Sensitivity of leaf unfolding to experimental warming in three temperate tree species , 2013 .

[9]  T. Koike Autumn coloring, photosynthetic performance and leaf development of deciduous broad-leaved trees in relation to forest succession. , 1990, Tree physiology.

[10]  S. Nagai,et al.  Vertical integration of leaf area index in a Japanese deciduous broad-leaved forest , 2008 .

[11]  S. Running,et al.  The impact of growing-season length variability on carbon assimilation and evapotranspiration over 88 years in the eastern US deciduous forest , 1999, International journal of biometeorology.

[12]  O. Gordo,et al.  Long‐term temporal changes of plant phenology in the Western Mediterranean , 2009 .

[13]  Cbd Global Biodiversity Outlook 3 , 2017 .

[14]  Hideki Kobayashi,et al.  Utility of information in photographs taken upwards from the floor of closed-canopy deciduous broadleaved and closed-canopy evergreen coniferous forests for continuous observation of canopy phenology , 2013, Ecol. Informatics.

[15]  P. Berry,et al.  Ecological impacts of climate change in Japan: The importance of integrating local and international publications , 2013 .

[16]  Reiko Ide,et al.  Use of digital cameras for phenological observations , 2010, Ecol. Informatics.

[17]  Y. Vitasse,et al.  Chilling and heat requirements for leaf unfolding in European beech and sessile oak populations at the southern limit of their distribution range , 2014, International Journal of Biometeorology.

[18]  Lin Xu,et al.  Phenological responses of Ulmus pumila (Siberian Elm) to climate change in the temperate zone of China , 2012, International Journal of Biometeorology.

[19]  Kenlo Nishida Nasahara,et al.  Detection of Bio-Meteorological Year-to-Year Variation by Using Digital Canopy Surface Images of a Deciduous Broad-Leaved Forest , 2013 .

[20]  Annette Menzel,et al.  Responses of leaf colouring in four deciduous tree species to climate and weather in Germany , 2006 .

[21]  Maurizio Mencuccini,et al.  The relationship between carbon dioxide uptake and canopy colour from two camera systems in a deciduous forest in southern England , 2012, Functional Ecology.

[22]  Mark D. Schwartz,et al.  Comparing carbon flux and high-resolution spring phenological measurements in a northern mixed forest , 2013 .

[23]  O. Sonnentag,et al.  Climate change, phenology, and phenological control of vegetation feedbacks to the climate system , 2013 .

[24]  T. Sakai,et al.  Biometric based estimates of net primary production (NPP) in a cool-temperate deciduous forest stand beneath a flux tower , 2005 .

[25]  P. Adamík,et al.  Long-term temporal changes in central European tree phenology (1946−2010) confirm the recent extension of growing seasons , 2014, International Journal of Biometeorology.

[26]  Hideki Kobayashi,et al.  Relationship between spatio-temporal characteristics of leaf-fall phenology and seasonal variations in near surface- and satellite-observed vegetation indices in a cool-temperate deciduous broad-leaved forest in Japan , 2014 .

[27]  Sylvain Delzon,et al.  Assessing the effects of climate change on the phenology of European temperate trees , 2011 .

[28]  Josep Peñuelas,et al.  Phenology Feedbacks on Climate Change , 2009, Science.

[29]  S. Nagai,et al.  Review: Development of an in situ observation network for terrestrial ecological remote sensing: the Phenological Eyes Network (PEN) , 2015, Ecological Research.

[30]  Hans W. Linderholm,et al.  Growing season changes in the last century , 2006 .

[31]  P. Ciais,et al.  Influence of spring and autumn phenological transitions on forest ecosystem productivity , 2010, Philosophical Transactions of the Royal Society B: Biological Sciences.

[32]  Hella Ellen Ahrends,et al.  Quantitative phenological observations of a mixed beech forest in northern Switzerland with digital photography , 2008 .

[33]  A. Hodgson,et al.  Unmanned Aerial Vehicles (UAVs) for Surveying Marine Fauna: A Dugong Case Study , 2013, PloS one.

[34]  Jun Yoshino,et al.  Effects of canopy phenology on deciduous overstory and evergreen understory carbon budgets in a cool-temperate forest ecosystem under ongoing climate change , 2015, Ecological Research.

[35]  R. Suzuki,et al.  Unmanned Aerial Survey of Fallen Trees in a Deciduous Broadleaved Forest in Eastern Japan , 2014, PloS one.

[36]  Andrew D. Richardson,et al.  Predicting Climate Change Impacts on the Amount and Duration of Autumn Colors in a New England Forest , 2013, PloS one.

[37]  J. Peñuelas,et al.  European phenological response to climate change matches the warming pattern , 2006 .

[38]  Piers J. Sellers,et al.  A Global Climatology of Albedo, Roughness Length and Stomatal Resistance for Atmospheric General Circulation Models as Represented by the Simple Biosphere Model (SiB) , 1989 .

[39]  Mark D. Schwartz,et al.  Monitoring global change with phenology: The case of the spring green wave , 1994 .

[40]  K. Kikuzawa Leaf survival of woody plants in deciduous broad-leaved forests. 2. Small trees and shrubs , 1984 .

[41]  H. Doi Response of the Morus bombycis growing season to temperature and its latitudinal pattern in Japan , 2012, International Journal of Biometeorology.

[42]  W. Sutherland,et al.  A 250-year index of first flowering dates and its response to temperature changes , 2010, Proceedings of the Royal Society B: Biological Sciences.

[43]  Kenlo Nishida Nasahara,et al.  Using digital camera images to detect canopy condition of deciduous broad-leaved trees , 2011 .

[44]  K. Kikuzawa Leaf survival of woody plants in deciduous broad-leaved forests. 1. Tall trees , 1983 .

[45]  D. Hollinger,et al.  Use of digital webcam images to track spring green-up in a deciduous broadleaf forest , 2007, Oecologia.

[46]  Quansheng Ge,et al.  Multiple phenological responses to climate change among 42 plant species in Xi’an, China , 2013, International Journal of Biometeorology.

[47]  Annette Menzel,et al.  Detecting plant seasonality from webcams using Bayesian multiple change point analysis , 2013 .

[48]  Airam Rodríguez,et al.  The Eye in the Sky: Combined Use of Unmanned Aerial Systems and GPS Data Loggers for Ecological Research and Conservation of Small Birds , 2012, PloS one.