scholarly journals Synthesizing published knowledge of boreal forest cover change for large-scale landscape dynamics modelling

2003 ◽  
Vol 79 (1) ◽  
pp. 132-146 ◽  
Author(s):  
Dennis Yemshanov ◽  
Ajith H Perera
Keyword(s):  
Boreal Forest ◽  
Large Scale ◽  
Forest Canopy ◽  
Forest Cover ◽  
Forest Succession ◽  
Simulation Models ◽  
Limiting Factors ◽  
Sources Of Information ◽  
Forest Cover Change ◽  
Discrete State

We reviewed the published knowledge on forest succession in the North American boreal biome for its applicability in modelling forest cover change over large extents. At broader scales, forest succession can be viewed as forest cover change over time. Quantitative case studies of forest succession in peer-reviewed literature are reliable sources of information about changes in forest canopy composition. We reviewed the following aspects of forest succession in literature: disturbances; pathways of post-disturbance forest cover change; timing of successional steps; probabilities of post-disturbance forest cover change, and effects of geographic location and ecological site conditions on forest cover change. The results from studies in the literature, which were mostly based on sample plot observations, appeared to be sufficient to describe boreal forest cover change as a generalized discrete-state transition process, with the discrete states denoted by tree species dominance. In this paper, we outline an approach for incorporating published knowledge on forest succession into stochastic simulation models of boreal forest cover change in a standardized manner. We found that the lack of details in the literature on long-term forest succession, particularly on the influence of pre-disturbance forest cover composition, may be limiting factors in parameterizing simulation models. We suggest that the simulation models based on published information can provide a good foundation as null models, which can be further calibrated as detailed quantitative information on forest cover change becomes available. Key words: probabilistic model, transition matrix, boreal biome, landscape ecology

Economic crisis, small-scale agriculture, and forest cover change in southern Cameroon

2000 ◽  
Vol 27 (3) ◽  
pp. 284-290 ◽  
Author(s):  
W.D. SUNDERLIN ◽  
O. NDOYE ◽  
H. BIKIÉ ◽  
N. LAPORTE ◽  
B. MERTENS ◽  
...  
Keyword(s):  
Population Growth ◽  
Economic Crisis ◽  
Rural Population ◽  
Structural Adjustment ◽  
Large Scale ◽  
Forest Cover ◽  
Small Scale ◽  
Forest Cover Change ◽  
Macroeconomic Shocks ◽  
Adjustment Policies

The rate of forest cover loss in the humid tropics of Cameroon is one of the highest in Central Africa. The aim of the large-scale, two-year research project described here was to understand the effect of the country's economic crisis and policy change on small-scale agricultural systems and land-clearing practices. Hypotheses were tested through surveys of more than 5000 households in 125 villages, and through time-series remote sensing analysis at two sites. The principal findings are that: (1) the rate of deforestation increased significantly in the decade after the 1986 onset of the crisis, as compared to the decade prior to the crisis; (2) the main proximate causes of this change were sudden rural population growth and a shift from production of cocoa and coffee to plantain and other food crops; and (3) the main underlying causes were macroeconomic shocks and structural adjustment policies that led to rural population growth and farming system changes. The implication of this study is that it is necessary to understand and anticipate the undesirable consequences of macroeconomic shocks and adjustment policies for forest cover. Such policies, even though they are often not formulated with natural resource consequences in mind, are often of greater relevance to the fate of forests than forest policy.

scholarly journals The spatial pattern of forest cover changes in Lithuania during the second half of the twentieth century

2015 ◽  
Vol 22 (4) ◽  
Author(s):  
Daiva Juknelienė ◽  
Gintautas Mozgeris
Keyword(s):  
World War Ii ◽  
Forest Cover ◽  
Agricultural Land ◽  
Moran’S I ◽  
Sources Of Information ◽  
Forest Cover Change ◽  
Moran's I ◽  
Local Patterns ◽  
Forest Cover Changes ◽  
Global And Local

The trends of forest cover change in Lithuanian municipalities are introduced in the current paper. Two sources of information on the forest cover in 1950s and today (2013) were used in this study: (i) a geographic forest cover database developed using historical orthophotomaps based on aerial photography, which was carried out in the period just after the World War II, and (ii) the information originating from the State Forest Cadaster and referring to the year 2013. These two layers were compared using GIS overlay techniques. The data was made available for the analyses aggregated up to the municipality level. The Global Moran’s I statistic and Anselin Local Moran’s I were used to identify global and local patterns in the distribution of forest cover characteristics in Lithuanian municipalities, respectively. The  main finding of this study was that the  proportion of the  forest cover in 1950 was 26.5%, i. e. notably differing from the official statistics – 19.7%. The proportion of the forest cover increased in all municipalities during the period 1950–2013. The largest increase in forest cover proportion was in the areas less suitable for agriculture. The relatively largest areas of new forests were identified in the south-eastern part of Lithuania, the deforestation was relatively slowest around less forested municipalities, while the afforestation was relatively slowest around the agricultural Pakruojis municipality. Deforestation was most commonly associated with the forest transformation into agricultural land, less often into scrublands or waters.

scholarly journals Assessing the tropical forest cover change in northern parts of Sonitpur and Udalguri District of Assam, India

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ranjit Mahato ◽  
Gibji Nimasow ◽  
Oyi Dai Nimasow ◽  
Dhoni Bushi
Keyword(s):  
Protected Areas ◽  
National Park ◽  
Large Scale ◽  
Forest Cover ◽  
Ground Truth ◽  
Forest Cover Change ◽  
Wildlife Sanctuary ◽  
Remotely Sensed Data ◽  
Ground Truth Data ◽  
Increasing Trends

AbstractSonitpur and Udalguri district of Assam possess rich tropical forests with equally important faunal species. The Nameri National Park, Sonai-Rupai Wildlife Sanctuary, and other Reserved Forests are areas of attraction for tourists and wildlife lovers. However, these protected areas are reportedly facing the problem of encroachment and large-scale deforestation. Therefore, this study attempts to estimate the forest cover change in the area through integrating the remotely sensed data of 1990, 2000, 2010, and 2020 with the Geographic Information System. The Maximum Likelihood algorithm-based supervised classification shows acceptable agreement between the classified image and the ground truth data with an overall accuracy of about 96% and a Kappa coefficient of 0.95. The results reveal a forest cover loss of 7.47% from 1990 to 2000 and 7.11% from 2000 to 2010. However, there was a slight gain of 2.34% in forest cover from 2010 to 2020. The net change of forest to non-forest was 195.17 km2 in the last forty years. The forest transition map shows a declining trend of forest remained forest till 2010 and a slight increase after that. There was a considerable decline in the forest to non-forest (11.94% to 3.50%) from 2000–2010 to 2010–2020. Further, a perceptible gain was also observed in the non-forest to the forest during the last four decades. The overlay analysis of forest cover maps show an area of 460.76 km2 (28.89%) as forest (unchanged), 764.21 km2 (47.91%) as non-forest (unchanged), 282.67 km2 (17.72%) as deforestation and 87.50 km2 (5.48%) as afforestation. The study found hotspots of deforestation in the closest areas of National Park, Wildlife Sanctuary, and Reserved Forests due to encroachments for human habitation, agriculture, and timber/fuelwood extractions. Therefore, the study suggests an early declaration of these protected areas as Eco-Sensitive Zone to control the increasing trends of deforestation.

Investigating the interactions between Forest Cover Change and Hydroclimatic patterns in the Bolivian Amazon basin over the last 30 years

2020 ◽  
Author(s):  
Sly Wongchuig Correa ◽  
Jhan Carlo Espinoza ◽  
Hans Segura ◽  
Thomas Condom ◽  
Clémentine Junquas
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Amazon Basin ◽  
Forest Cover ◽  
Hydrological Modeling ◽  
European Space Agency ◽  
Forest Cover Change ◽  
Wet Season ◽  
Climatic Index ◽  
Bolivian Amazon

<p>Large evidences support the strong impacts on rainfall amount and the increasing of dry-season length on the Amazonian forest. All of these effects are usually attributed to large scale atmospheric circulation and to land cover changes as part of anthropogenic effects. In this research we assess statistical and modeling approaches to investigate the interaction between changes in forest cover and hydroclimate processes on a regional and local scale.</p><p>Henceforth, the deforestation areas and climatic indexes for the southern Amazon basin (south of 14°S) were evaluated. The deforestation map was estimated for the 1992-2018 period, based on global land cover maps at 300 m of spatial resolution produced by the European Space Agency (ESA) Climate Change Initiative (CCI) by using several remote sensing datasets. The CHIRPS rainfall dataset (P) for the 1981-2018 period was used to estimate the dry day frequency (DDF, P<1mm) and the wet day frequency (WDF, P>10mm). In addition, the mean actual seasonal evapotranspiration (AET) was GLEAM and ET-Amazon evapotranspiration datasets for the 1980-2018 and 2003-2013 periods respectively. In order to determine the local and the regional climatic effect for each pixel of the climatic index (DDF, WDF and AET), the deforestation fraction was estimated considering different spatial radii of influence (20 to 50 km).</p><p>The first results indicate a particular pattern in the southern Bolivian Amazon where two groups of areas were identified, considering the common period of analysis (1992-2018). One of them shows a significant relationship between increasing trend of DDF and decreasing trend of WDF while deforestation fraction is high, what mainly occurs during the wet season. In addition, this region is clearly placed in areas with values of deforestation fraction above ~30%, a closest value to the usually estimated Amazon Tipping Point (~40%). Below this value, the second group is also located in regions with positive trends of DDF and negative trends of WDF. This region has probably a strongest link with the large-scale climate.</p><p>Considering these preliminary results, the statistical approaches developed in this research could give some insights about the interactions between forest change and the regional hydro climatology, which might improve the understanding of this interaction based on large-scale hydrological modeling.</p>

Potential Impact of the Eurasian Boreal Forest on North Pacific Climate Variability*

2007 ◽  
Vol 20 (6) ◽  
pp. 981-992 ◽  
Author(s):  
Michael Notaro ◽  
Zhengyu Liu
Keyword(s):  
Boreal Forest ◽  
North Pacific ◽  
Vegetation Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Kuroshio Extension ◽  
Vegetation Feedback ◽  
North Asia ◽  
The Impact ◽  
The Kuroshio

Abstract The authors demonstrate that variability in vegetation cover can potentially influence oceanic variability through the atmospheric bridge. Experiments aimed at isolating the impact of variability in forest cover along the poleward side of the Asian boreal forest on North Pacific SSTs are performed using the fully coupled model, Fast Ocean Atmosphere Model–Lund Potsdam Jena (FOAM-LPJ), with dynamic atmosphere, ocean, and vegetation. The northern edge of the simulated Asian boreal forest is characterized by substantial variability in annual forest cover, with an east–west dipole pattern marking its first EOF mode. Simulations in which vegetation cover is allowed to vary over north/central Russia exhibit statistically significant greater SST variance over the Kuroshio Extension. Anomalously high forest cover over North Asia supports a lower surface albedo with higher temperatures and lower sea level pressure, leading to a reduction in cold advection into northern China and in turn a decrease in cold air transport into the Kuroshio Extension region. Variability in the large-scale circulation pattern is indirectly impacted by the aforementioned vegetation feedback, including the enhancement in upper-level jet wind variability along the north–south flanks of the East Asian jet stream.

Forestation does not necessarily reduce soil erosion in a karst watershed in southwestern China

2020 ◽  
pp. 030913332095861
Author(s):  
Siwen Feng ◽  
Lu Wu ◽  
Boyi Liang ◽  
Hongya Wang ◽  
Hongyan Liu ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Large Scale ◽  
Satellite Images ◽  
Forest Cover ◽  
Phase Relationship ◽  
Southwestern China ◽  
Forest Cover Change ◽  
Sediment Delivery ◽  
Karst Areas ◽  
Tillage Erosion

Forestation as part of the Returning Farmland to Forest Project was implemented to mitigate soil erosion in southwestern China. However, whether forestation has effectively reduced soil erosion in southwestern China remains unclear, mostly because of the lack of monitoring forest cover change and soil erosion at watershed scales. We interpreted forest cover change from satellite images and simulated soil erosion changes for the period of 1986–2018 in the Chong’an River Basin with the Water and Tillage Erosion Model and Sediment Delivery Model. Our results show that the change in forest cover has the highest correlation coefficient with the sediment yield in the watershed, with an obvious inverse phase relationship between them for all the simulated years. From 2002 to 2014, large-scale forestation and frequent droughts caused the forest cover to vary, resulting in significant changes in the annual soil erosion amount. Because crevices favoring tree growth are more developed in limestone than in dolomite, the forest cover reduction on dolomite is significantly higher than that on limestone under severe droughts in karst areas. Our study implied that the function of forestation in preventing soil erosion depends on lithology in karst areas.

scholarly journals Assessment of Large Scale Land Cover Change Classifications and Drivers of Deforestation in Indonesia

2015 ◽  
Vol XL-7/W3 ◽  
pp. 557-562 ◽  
Author(s):  
A. Wijaya ◽  
R. A. Sugardiman Budiharto ◽  
A. Tosiani ◽  
D. Murdiyarso ◽  
L.V. Verchot
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Spatial Information ◽  
Brazilian Amazon ◽  
Congo Basin ◽  
Reliable Estimate ◽  
Forest Conversion ◽  
Forest Cover Change ◽  
Forest Change

Indonesia possesses the third largest tropical forests coverage following Brazilian Amazon and Congo Basin regions. This country, however, suffered from the highest deforestation rate surpassing deforestation in the Brazilian Amazon in 2012. National capacity for forest change assessment and monitoring has been well-established in Indonesia and the availability of national forest inventory data could largely assist the country to report their forest carbon stocks and change over more than two decades. This work focuses for refining forest cover change mapping and deforestation estimate at national scale applying over 10,000 scenes of Landsat scenes, acquired in 1990, 1996, 2000, 2003, 2006, 2009, 2011 and 2012. Pre-processing of the data includes, geometric corrections and image mosaicking. The classification of mosaic Landsat data used multi-stage visual observation approaches, verified using ground observations and comparison with other published materials. There are 23 land cover classes identified from land cover data, presenting spatial information of forests, agriculture, plantations, non-vegetated lands and other land use categories. We estimated the magnitude of forest cover change and assessed drivers of forest cover change over time. Forest change trajectories analysis was also conducted to observe dynamics of forest cover across time. This study found that careful interpretations of satellite data can provide reliable information on forest cover and change. Deforestation trend in Indonesia was lower in 2000-2012 compared to 1990-2000 periods. We also found that over 50% of forests loss in 1990 remains unproductive in 2012. Major drivers of forest conversion in Indonesia range from shrubs/open land, subsistence agriculture, oil palm expansion, plantation forest and mining. The results were compared with other available datasets and we obtained that the MOF data yields reliable estimate of deforestation.

scholarly journals Combined biogeophysical and biogeochemical effects of large-scale forest cover changes in the MPI earth system model

2010 ◽  
Vol 7 (1) ◽  
pp. 387-428 ◽  
Author(s):  
S. Bathiany ◽  
M. Claussen ◽  
V. Brovkin ◽  
T. Raddatz ◽  
V. Gayler
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Forest Canopy ◽  
Forest Cover ◽  
Co2 Concentration ◽  
Earth System Model ◽  
System Model ◽  
Climate Mitigation ◽  
Earth System ◽  
The Tropics

Abstract. Afforestation and reforestation have become popular instruments of climate mitigation policy, as forests are known to store large quantities of carbon. However, they also modify the fluxes of energy, water and momentum at the land surface. Previous studies have shown that these biogeophysical effects can counteract the carbon drawdown and, in boreal latitudes, even overcompensate it due to large albedo differences between forest canopy and snow. This study investigates the role forest cover plays for global climate by conducting deforestation and afforestation experiments with the earth system model of the Max Planck Institute for Meteorology (MPI-ESM). Complete deforestation of the tropics (18.75° S–15° N) exerts a global warming of 0.4 °C due to an increase in CO2 concentration by initially 60 ppm and a decrease in evapotranspiration in the deforested areas. In the northern latitudes (45° N–90° N), complete deforestation exerts a global cooling of 0.25 °C after 100 years, while afforestation leads to an equally large warming, despite the counteracting changes in CO2 concentration. Earlier model studies are qualitatively confirmed by these findings. As the response of temperature as well as terrestrial carbon pools is not of equal sign at every land cell, considering forests as cooling in the tropics and warming in high latitudes seems to be true only for the spatial mean, but not on a local scale.

The impact of large scale agriculture on forest and wildlife in Diga Woreda, Western Ethiopia

2017 ◽  
Vol 1 (02) ◽  
pp. 100-113
Author(s):  
OLANI GANFURE JALETA ◽  
HABTE JEBESSA DEBELLA
Keyword(s):  
Land Cover ◽  
Large Scale ◽  
Forest Cover ◽  
Satellite Image ◽  
Forest Cover Change ◽  
State Farm ◽  
Degraded Lands ◽  
Local Study ◽  
The Impact ◽  
Western Ethiopia

Jaleta OG, Jebessa H. 2018. The impact of large scale agriculture on forest and wildlife in Diga Woreda, Western Ethiopia. Asian J Agric 1: 100-113. Large-scale agriculture uses agricultural machinery to mechanize the practices of agriculture. It is one of the leading causes of the loss of forest and wildlife in many countries including our country, Ethiopia. Information on forest cover change that occurred from 1986 to 2006 in Diga Woreda/district (Woyessa Dimtu, Bekiltu Gudina, and Melka Beti Jirma Kebeles) was compared with the present time using Geographic Information System (GIS). The objective of this study was to investigate the impact of large-scale agriculture on forest cover change by using the satellite image of the study area and other data collecting methods such as household's interview, KI, FGD and observation (survey) to detect its effect on wildlife. The study employed both qualitative and quantitative data as well as primary and secondary data sources to collect necessary information. The information providers were purposively selected from sample ‘kebeles' based on their age and experiences, that is, to get a detail and accurate information elders and experts who have lived in the area for many years and who know more how and when the Hanger-Didessa state farm had established were selected. The state farm covered a large area, that is, about four districts such as Sasiga, Diga, Arjo and Guto Gida. For this study, Diga was selected because of its socio-economic characteristics, deforested (degraded) area, local loss of larger mammals and forest cover changes observed in the district. The descriptive research method was used to assess community's knowledge, perception, skill, and feeling about the impact of Local Study Area (LSA) on forest and wildlife in the area. Land cover change analysis for 1986 to 2006 showed that the land cover of the study area is classified as grazing, wood, agricultural, settlement and degraded lands. The result of the analysis showed that agriculture, settlement and degraded lands increased from 19.68% to 32.72%, 12.12% to 26.85% and 2.76% to 4.72% respectively in an expense of a decrease in the grass (grazing) and woodlands. Therefore, LSA is the primary cause for the loss of forest and wildlife in the study area.

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