Revisiting the Dynamics of Forest Area Change: A Panel Data Assessment

2020 ◽  
Vol 35 (2-3) ◽  
pp. 107-127
Author(s):  
George Halkos ◽  
Antonis Skouloudis
Keyword(s):  
Panel Data ◽  
Forest Area ◽  
Area Change ◽  
Data Assessment ◽  
Forest Area Change

scholarly journals NDVI-derived forest area change and its driving factors in China

PLoS ONE ◽  
2018 ◽  
Vol 13 (10) ◽  
pp. e0205885 ◽  
Author(s):  
Lizhuang Liang ◽  
Feng Chen ◽  
Lei Shi ◽  
Shukui Niu
Keyword(s):  
Forest Area ◽  
Driving Factors ◽  
Area Change ◽  
Forest Area Change

scholarly journals Gross changes in forest area shape the future carbon balance of tropical forests

2017 ◽  
Author(s):  
Wei Li ◽  
Philippe Ciais ◽  
Chao Yue ◽  
Thomas Gasser ◽  
Shushi Peng ◽  
...  
Keyword(s):  
Land Use ◽  
Time Horizon ◽  
Secondary Forest ◽  
Forest Area ◽  
Carbon Pools ◽  
Response Curves ◽  
Area Change ◽  
Legacy Effect ◽  
The Future ◽  
Forest Area Change

Abstract. Bookkeeping models are used to estimate land-use change (LUC) carbon fluxes (ELUC). These models combine time series of areas subject to different LUC types with response curves of carbon pools in ecosystems and harvested products after a unit change of land use. The level of detail of bookkeeping models depends on the number of response curves used for different regions, the carbon pools they represent, and the diversity of LUC types considered. The uncertainty of bookkeeping models arises from data used to define response curves (usually local data) and their representativeness of large regions. Here, we compare biomass recovery curves derived from a recent synthesis of secondary forest plots data by Poorter et al. (2016) with the curves used in bookkeeping models from Houghton (1999) and Hansis et al. (2015) in Latin America. We find that both Houghton (1999) and Hansis et al. (2015) overestimate the long-term (100 years) biomass carbon density of secondary forest, by about 25 %. We also show the importance of considering gross forest area change in addition to the net forest area change for estimating regional ELUC. To do so, simulations are constructed with a bookkeeping model calibrated with three different sets of response curves (linear, exponential and logarithmic) to study ELUC created by a pulse of net forest area change, with different gross-to-net forest area change ratios (γAnetAgross). Following the initial pulse of forest area change, ELUC is subsequently calculated over 100 years. Considering a region subject to a net gain in forest area during one year, different values of gross forest area changes that sum up to this initial net gain can change the magnitude and even the sign of ELUC with a given time horizon after the initial forest area change. In other words, in the case of a net gain in forest area composed of a large gross loss and a large gross gain, the initial gross loss has an important legacy effect that the system can be a net source of CO2 to the atmosphere. We show the existence of a critical value of γAnetAgross above which ELUC switches from CO2 sink to source with a given time horizon after the initial forest area change. This critical ratio derived from the structure of the bookkeeping model is compared against real-world high resolution Landsat TM observations of gross forest area change in the Amazon to distinguish areas where current forest land turnover will legate LUC carbon emissions or sinks in 20 years, 50 years and 100 years in the future.

An economic model of international wood supply, forest stock and forest area change

2006 ◽  
Vol 21 (1) ◽  
pp. 73-86 ◽  
Author(s):  
James A. Turner ◽  
Joseph Buongiorno ◽  
Shushuai Zhu
Keyword(s):  
Economic Model ◽  
Forest Area ◽  
Wood Supply ◽  
Area Change ◽  
Forest Area Change

scholarly journals Factors affecting forest area change in Southeast Asia during 1980-2010

PLoS ONE ◽  
2018 ◽  
Vol 13 (5) ◽  
pp. e0197391 ◽  
Author(s):  
Nobuo Imai ◽  
Takuya Furukawa ◽  
Riyou Tsujino ◽  
Shumpei Kitamura ◽  
Takakazu Yumoto
Keyword(s):  
Southeast Asia ◽  
Forest Area ◽  
Area Change ◽  
Factors Affecting ◽  
Forest Area Change

scholarly journals The effect of forest area change in tropical islands towards baseflow and streamflow

2021 ◽  
Vol 847 (1) ◽  
pp. 012032
Author(s):  
N L Khomsiati ◽  
N Suryoputro ◽  
A Yulistyorini ◽  
G Idfi ◽  
N E B Alias
Keyword(s):  
Forest Area ◽  
Tropical Islands ◽  
Area Change ◽  
Forest Area Change

scholarly journals The Change of Forest Area in Alytus and Vilnius Counties (Lithuania)

2018 ◽  
Vol 8 ◽  
pp. 33-37
Author(s):  
Giedre Ivaviciute
Keyword(s):  
National Parks ◽  
Current Situation ◽  
Status Quo ◽  
Forest Area ◽  
Logical Analysis ◽  
Area Change ◽  
Forest Area Change ◽  
Pine Trees ◽  
The Status ◽  
Forest Enterprises

The article presents the analysis of the current situation of the forest area in Alytus and Vilnius counties. Comparative, analytical as well as statistical and logical analysis methods were used for the investigation. The aim of the investigation is to carry out the analysis of the Alytus and Vilnius counties forest area during the period between the years 2006 and 2018. The object of the investigation – Alytus and Vilnius counties forest area. Tasks of the investigation: 1. To describe the status quo of forest in Alytus and Vilnius counties. 2. To analyze and compare the forest area change in Alytus and Vilnius counties during the period between the years 2006 and 2018. The study found that forests prevailing in Alytus and Vilnius Counties are 50-59 years old. It was determined that pine trees prevail in Alytus County (71.05 percent) and in Vilnius County (16.38 percent) as well. The type of ownership prevailing in both Alytus and Vilnius counties is the forests of state significance managed by forest enterprises, national parks and state reserves. In Alytus County, during the period between the years 2006 and 2018, the forest area decreased by 4123.16 ha or 1.55 percent, in Vilnius County increased by 9593.16 ha or 2,35 percent.

scholarly journals Correction: Factors affecting forest area change in Southeast Asia during 1980-2010

PLoS ONE ◽  
2018 ◽  
Vol 13 (6) ◽  
pp. e0199908 ◽  
Author(s):  
Nobuo Imai ◽  
Takuya Furukawa ◽  
Riyou Tsujino ◽  
Shumpei Kitamura ◽  
Takakazu Yumoto
Keyword(s):  
Southeast Asia ◽  
Forest Area ◽  
Correction Factors ◽  
Area Change ◽  
Factors Affecting ◽  
Forest Area Change

scholarly journals Forest Area Change in the Shifting Landscape Mosaic of the Continental United States from 2001 to 2016

Land ◽  
2020 ◽  
Vol 9 (11) ◽  
pp. 417
Author(s):  
Kurt Riitters ◽  
Karen Schleeweis ◽  
Jennifer Costanza
Keyword(s):  
United States ◽  
Forest Area ◽  
Landscape Context ◽  
Forest Loss ◽  
Landscape Mosaic ◽  
Forest Change ◽  
Area Change ◽  
Agriculture Land ◽  
Forest Area Change ◽  
Loss Rates

The landscape context (i.e., anthropogenic setting) of forest change partly determines the social-ecological outcomes of the change. Furthermore, forest change occurs within, is constrained by, and contributes to a dynamic landscape context. We illustrate how information about local landscape context can be incorporated into regional assessments of forest area change. We examined the status and change of forest area in the continental United States from 2001 to 2016, quantifying landscape context by using a landscape mosaic classification that describes the dominance and interface (i.e., juxtaposition) of developed and agriculture land in relation to forest and other land. The mosaic class changed for five percent of total land area and three percent of total forest area. The least stable classes were those comprising the developed interface. Forest loss rates were highest in developed-dominated landscapes, but the forest area in those landscapes increased by 18 percent as the expansion of developed landscapes assimilated more forest area than was lost from earlier developed landscapes. Conversely, forest loss rates were lowest in agriculture-dominated landscapes where there was a net loss of five percent of forest area, even as the area of those landscapes also increased. Exposure of all land to nearby forest removal, fire, and stress was highest in natural-dominated landscapes, while exposure to nearby increases in developed and agriculture land was highest in developed- and agriculture-dominated landscapes. We discuss applications of our approach for mapping, monitoring, and modeling landscape and land use change.

A satellite data set for tropical forest area change assessment

2011 ◽  
Vol 32 (22) ◽  
pp. 7009-7031 ◽  
Author(s):  
Rene Beuchle ◽  
Hugh D. Eva ◽  
Hans-Jürgen Stibig ◽  
Catherine Bodart ◽  
Andreas Brink ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Satellite Data ◽  
Forest Area ◽  
Data Set ◽  
Area Change ◽  
Change Assessment ◽  
Forest Area Change
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