Remotely-Sensed Phenology of Forests under Changing Climate Conditions

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Ecophysiology and Biology".

Deadline for manuscript submissions: closed (20 February 2020) | Viewed by 7209

Special Issue Editors


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Guest Editor
Council for Agricultural Research and Economics (CREA), Research Centre for Engineering and Agro-Food Processing (CREA-IT), 00186 Rome, Italy
Interests: vegetation phenology dynamics; landscape disturbance; fire spatio-temporal behavior; land cover change processes; remotely sensed data analysis; geoprocessing techniques; multivariate statistical methods
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Co-Guest Editor
Council for Agricultural Research and Economics (CREA), Research Centre for Engineering and Agro-Food Processing (CREA-IT), 00186 Rome, Italy
Interests: biodiversity; forest ecology; forest management; ecosystems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With facing the current global change, phenology has become a major concern because of its ability to monitor, understand, and predict the periodicity of the biological events related to the climate, from an intra- and inter-specific level, to a global scale; it plays a pivotal role in how climate change affects ecosystem services, trophic exchanges, and species niche ranges. Forest phenology is an integrative environmental science embracing biometeorology, ecology, and evolutionary biology; it determines ecosystem services at local and global scales, controlling the interannual variability of both gross primary productivity (GPP), and net ecosystem productivity (NEP) and exchange (NEE), and influencing biodiversity patterns, water cycle, and carbon balance. In this framework, remote sensing has the potential to fill the gap between traditional phenological (field) observations and the large-scale view of global models, in order to enable the mapping and monitoring of phenology at an ecosystem level, and to provide an integrative framework at a landscape scale. Remotely-sensed phenology is defined as the seasonal pattern of variation of vegetation indices (i.e., greening, senescence, dormancy, etc.) in vegetated land surfaces observed from satellite remote sensing. Satellite observations constitute a spatially aggregated signal from heterogeneous surface conditions that may not be representative of any single plant species’ response. The length of the time series, high temporal frequency, internal consistency, and continuous availability of the satellite measurements are fundamental requirements when dealing with ecosystem responses to climate change dynamics.
This Special Issue of Forests is focused on quantifying and modeling remotely sensed phenology under climate change conditions through novel methodological approaches. We particularly welcome studies that aim to answer the main questions connected to the changing climate by exploiting remote sensing potentialities, namely: How have the patterns of phenology shifted within different ecological zones over the last decades? What are the key factors affecting vegetation growing season change in recent years? How do the increased intensity and frequency of climate-induced stresses affect forests structure, distribution, and composition, with consequent changes in biomass production? What are the forests’ adaptive responses to changing climate conditions?

Dr. Sofia Bajocco
Dr. Marco Bascietto
Guest Editors

Manuscript Submission Information

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Keywords

  • Phenology
  • Remote sensing
  • Climate change
  • Anomalies
  • Disturbance
  • Phenological metrics
  • Mapping
  • Monitoring
  • Modelling
  • Temporal trend
  • Spatial pattern
  • Biomass
  • Biodiversity
  • Adaptation

Published Papers (2 papers)

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Research

20 pages, 6164 KiB  
Article
Relative Contribution of Growing Season Length and Amplitude to Long-Term Trend and Interannual Variability of Vegetation Productivity over Northeast China
by Yuke Zhou
Forests 2020, 11(1), 112; https://doi.org/10.3390/f11010112 - 16 Jan 2020
Cited by 8 | Viewed by 2650
Abstract
In the context of global warming, the terrestrial ecosystem productivity over the Northern Hemisphere presents a substantially enhanced trend. The magnitude of summer vegetation maximum growth, known as peak growth, remains only partially understood for its role in regulating changes in vegetation productivity. [...] Read more.
In the context of global warming, the terrestrial ecosystem productivity over the Northern Hemisphere presents a substantially enhanced trend. The magnitude of summer vegetation maximum growth, known as peak growth, remains only partially understood for its role in regulating changes in vegetation productivity. This study aimed to estimate the spatiotemporal dynamics of the length of growing season (LOS) and maximum growth magnitude (MAG) over Northeast China (NEC) using a long-term satellite record of normalized difference vegetation index (NDVI) for the period 1982–2015, and quantifying their relative contribution to the long-term trend and inter-annual variability (IAV) of vegetation productivity. Firstly, the key phenological metrics, including MAG and start and end of growing season (SOS, EOS), were derived. Secondly, growing season vegetation productivity, measured as the Summary of Vegetation Index (VIsum), was obtained by cumulating NDVI values. Thirdly, the relative impacts of LOS and MAG on the trend and IAV in VIsum were explored using the relative importance (RI) method at pixel and vegetation cover type level. For the entire NEC, LOS, and MAG exhibited a slightly decreasing trend and a weak increasing trend, respectively, thus resulting in an insignificant change in VIsum. The temporal phases of VIsum presented a consistent pace with LOS, but changed asynchronously with MAG. There was an underlying cycle of about 10 years in the changes of LOS, MAG, and VIsum. At a regional scale, VIsum tended to maintain a rising trend in the northern coniferous forest and grassland in western and southern NEC. The spatial distribution of the temporal trends of LOS and MAG generally show a contrasting pattern, in which LOS duration is expected to shorten (negative trend) in the central cropland and in some southwestern grasslands (81.5% of the vegetated area), while MAG would increase (positive trend) in croplands, southern grasslands, and northern coniferous forests (16.5%). The correlation index for the entire NEC suggested that LOS was negatively associated with MAG, indicating that the extended vegetation growth duration would result in a lower growth peak and vice versa. Across the various vegetation types, LOS was a substantial factor in controlling both the trend and IAV of VIsum (RI = 75%). There was an opposite spatial pattern in the relative contribution of LOS and MAG to VIsum, where LOS dominated in the northern coniferous forests and in the eastern broadleaf forests, with MAG mainly impacting croplands and the western grasslands (RI = 27%). Although LOS was still the key factor controlling the trend and IAV of VIsum during the study period, this situation may change in the case peak growth amplitude gradually increases in the future. Full article
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24 pages, 9346 KiB  
Article
Forest Phenology Dynamics to Climate Change and Topography in a Geographic and Climate Transition Zone: The Qinling Mountains in Central China
by Haoming Xia, Yaochen Qin, Gary Feng, Qingmin Meng, Yaoping Cui, Hongquan Song, Ying Ouyang and Gangjun Liu
Forests 2019, 10(11), 1007; https://doi.org/10.3390/f10111007 - 11 Nov 2019
Cited by 40 | Viewed by 3915
Abstract
Forest ecosystems in an ecotone and their dynamics to climate change are growing ecological and environmental concerns. Phenology is one of the most critical biological indicators of climate change impacts on forest dynamics. In this study, we estimated and visualized the spatiotemporal patterns [...] Read more.
Forest ecosystems in an ecotone and their dynamics to climate change are growing ecological and environmental concerns. Phenology is one of the most critical biological indicators of climate change impacts on forest dynamics. In this study, we estimated and visualized the spatiotemporal patterns of forest phenology from 2001 to 2017 in the Qinling Mountains (QMs) based on the enhanced vegetation index (EVI) from MODerate-resolution Imaging Spectroradiometer (MODIS). We further analyzed this data to reveal the impacts of climate change and topography on the start of the growing season (SOS), end of the growing season (EOS), and the length of growing season (LOS). Our results showed that forest phenology metrics were very sensitive to changes in elevation, with a 2.4 days delayed SOS, 1.4 days advanced EOS, and 3.8 days shortened LOS for every 100 m increase in altitude. During the study period, on average, SOS advanced by 0.13 days year−1, EOS was delayed by 0.22 days year−1, and LOS increased by 0.35 day year−1. The phenological advanced and delayed speed across different elevation is not consistent. The speed of elevation-induced advanced SOS increased slightly with elevation, and the speed of elevation-induced delayed EOS shift reached a maximum value of 1500 m from 2001 to 2017. The sensitivity of SOS and EOS to preseason temperature displays that an increase of 1 °C in the regionally averaged preseason temperature would advance the average SOS by 1.23 days and delay the average EOS by 0.72 days, respectively. This study improved our understanding of the recent variability of forest phenology in mountain ecotones and explored the correlation between forest phenology and climate variables in the context of the ongoing climate warming. Full article
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