scholarly journals Land-Cover Change and the Future of the Apennine Brown Bear: A Perspective from the Past

2008 ◽  
Vol 89 (6) ◽  
pp. 1502-1511 ◽  
Author(s):  
Alessandra Falcucci ◽  
Luigi Maiorano ◽  
Paolo Ciucci ◽  
Edward O. Garton ◽  
Luigi Boitani
Author(s):  
Philip Mzava ◽  
Patrick Valimba ◽  
Joel Nobert

Abstract Over the past half-century, the risk of urban flooding in Dar es Salaam has increased due to changes in land cover coupled with climatic changes. This paper aimed to quantify the impacts of climate and land-cover changes on the magnitudes and frequencies of flood runoffs in urban Dar es Salaam, Tanzania. A calibrated and validated SWAT rainfall-runoff model was used to generate flood hydrographs for the period 1969–2050 using historical rainfall data and projected rainfall based on the CORDEX-Africa regional climate model. Results showed that climate change has a greater impact on change in peak flows than land-cover change when the two are treated separately in theory. It was observed that, in the past, the probability of occurrence of urban flooding in the study area was likely to be increased up to 1.5-fold by climate change relative to land-cover change. In the future, this figure is estimated to decrease to 1.1-fold. The coupled effects of climate and land-cover changes cause a much bigger impact on change in peak flows than any separate scenario; this scenario represents the actual scenario on the ground. From the combined effects of climate and land-cover changes, the magnitudes of mean peak flows were determined to increase between 34.4 and 58.6% in the future relative to the past. However, the change in peak flows from combined effects of climate and land-cover changes will decrease by 36.3% in the future relative to the past; owing to the lesser variations in climate and land-cover changes in the future compared with those of the past.


2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Kiros Tsegay Deribew

AbstractThe main grassland plain of Nech Sar National Park (NSNP) is a federally managed protected area in Ethiopia designated to protect endemic and endangered species. However, like other national parks in Ethiopia, the park has experienced significant land cover change over the past few decades. Indeed, the livelihoods of local populations in such developing countries are entirely dependent upon natural resources and, as a result, both direct and indirect anthropogenic pressures have been placed on natural parks. While previous research has looked at land cover change in the region, these studies have not been spatially explicit and, as a result, knowledge gaps in identifying systematic transitions continue to exist. This study seeks to quantify the spatial extent and land cover change trends in NSNP, identify the strong signal transitions, and identify and quantify the location of determinants of change. To this end, the author classifies panchromatic aerial photographs in 1986, multispectral SPOT imagery in 2005, and Sentinel imagery in 2019. The spatial extent and trends of land cover change analysis between these time periods were conducted. The strong signal transitions were systematically identified and quantified. Then, the basic driving forces of the change were identified. The locations of these transitions were also identified and quantified using the spatially explicit statistical model. The analysis revealed that over the past three decades (1986–2019), nearly 52% of the study area experienced clear landscape change, out of which the net change and swap change attributed to 39% and 13%, respectively. The conversion of woody vegetation to grassland (~ 5%), subsequently grassland-to-open-overgrazed land (28.26%), and restoration of woody vegetation (0.76%) and grassland (0.72%) from riverine forest and open-overgrazed land, respectively, were found to be the fully systematic transitions whereas the rest transitions were recorded either partly systematic or random transitions. The location of these most systematic land cover transitions identified through the spatially explicit statistical modeling showed drivers due to biophysical conditions, accessibility, and urban/market expansions, coupled with successive government policies for biodiversity management, geo-politics, demographic, and socioeconomic factors. These findings provide important insights into biodiversity loss, land degradation, and ecosystem disruption. Therefore, the model for predicted probability generally suggests a 0.75 km and 0.72 km buffers which are likely to protect forest and grassland from conversion to grassland and open-overgrazed land, respectively.


2016 ◽  
Vol 24 (1) ◽  
pp. 39-39 ◽  
Author(s):  
Rob Marchant ◽  
Stephen Rucina

2015 ◽  
Vol 6 (2) ◽  
pp. 1-17 ◽  
Author(s):  
Daniel Unger ◽  
I-Kuai Hung ◽  
Kenneth Farrish ◽  
Darinda Dans

The Haynesville Shale lies under areas of Louisiana and Texas and is one of the largest gas plays in the U.S. Encompassing approximately 2.9 million ha, this area has been subject to intensive exploration for oil and gas, while over 90% of it has traditionally been used for forestry and agriculture. In order to detect the landscape change in the past few decades, Landsat Thematic Mapper (TM) imagery for six years (1984, 1989, 1994, 2000, 2006, and 2011) was acquired. Unsupervised classifications were performed to classify each image into four cover types: agriculture, forest, well pad, and other. Change detection was then conducted between two classified maps of different years for a time series analysis. Finally, landscape metrics were calculated to assess landscape fragmentation. The overall classification accuracy ranged from 84.7% to 88.3%. The total amount of land cover change from 1984 to 2011 was 24%, with 0.9% of agricultural land and 0.4% of forest land changed to well pads. The results of Patch-Per-Unit area (PPU) index indicated that the well pad class was highly fragmented, while agriculture (4.4-8.6 per sq km) consistently showed a higher magnitude of fragmentation than forest (0.8-1.4 per sq km).


2014 ◽  
Vol 5 (1) ◽  
pp. 177-195 ◽  
Author(s):  
J. Pongratz ◽  
C. H. Reick ◽  
R. A. Houghton ◽  
J. I. House

Abstract. Reasons for the large uncertainty in land use and land cover change (LULCC) emissions go beyond recognized issues related to the available data on land cover change and the fact that model simulations rely on a simplified and incomplete description of the complexity of biological and LULCC processes. The large range across published LULCC emission estimates is also fundamentally driven by the fact that the net LULCC flux is defined and calculated in different ways across models. We introduce a conceptual framework that allows us to compare the different types of models and simulation setups used to derive land use fluxes. We find that published studies are based on at least nine different definitions of the net LULCC flux. Many multi-model syntheses lack a clear agreement on definition. Our analysis reveals three key processes that are accounted for in different ways: the land use feedback, the loss of additional sink capacity, and legacy (regrowth and decomposition) fluxes. We show that these terminological differences, alone, explain differences between published net LULCC flux estimates that are of the same order as the published estimates themselves. This has consequences for quantifications of the residual terrestrial sink: the spread in estimates caused by terminological differences is conveyed to those of the residual sink. Furthermore, the application of inconsistent definitions of net LULCC flux and residual sink has led to double-counting of fluxes in the past. While the decision to use a specific definition of the net LULCC flux will depend on the scientific application and potential political considerations, our analysis shows that the uncertainty of the net LULCC flux can be substantially reduced when the existing terminological confusion is resolved.


2015 ◽  
Vol 15 (23) ◽  
pp. 13555-13568 ◽  
Author(s):  
T. Verbeke ◽  
J. Lathière ◽  
S. Szopa ◽  
N. de Noblet-Ducoudré

Abstract. Dry deposition is a key component of surface–atmosphere exchange of compounds, acting as a sink for several chemical species. Meteorological factors, chemical properties of the trace gas considered and land surface properties are strong drivers of dry deposition efficiency and variability. Under both climatic and anthropogenic pressure, the vegetation distribution over the Earth has been changing a lot over the past centuries and could be significantly altered in the future. In this study, we perform a modeling investigation of the potential impact of land-cover changes between the present day (2006) and the future (2050) on dry deposition velocities at the surface, with special interest for ozone (O3) and nitric acid (HNO3), two compounds which are characterized by very different physicochemical properties. The 3-D chemistry-transport model LMDz-INCA is used, considering changes in vegetation distribution based on the three future projections, RCPs 2.6, 4.5 and 8.5, and present-day (2007) meteorology. The 2050 RCP 8.5 vegetation distribution leads to a rise of up to 7 % (+0.02 cm s−1) in the surface deposition velocity calculated for ozone (Vd,O3) and a decrease of −0.06 cm s−1 in the surface deposition velocity calculated for nitric acid (Vd,HNO3) relative to the present-day values in tropical Africa and up to +18 and −15 %, respectively, in Australia. When taking into account the RCP 4.5 scenario, which shows dramatic land-cover change in Eurasia, Vd,HNO3 increases by up to 20 % (annual-mean value) and reduces Vd,O3 by the same magnitude in this region. When analyzing the impact of surface dry deposition change on atmospheric chemical composition, our model calculates that the effect is lower than 1 ppb on annual-mean surface ozone concentration for both the RCP 8.5 and RCP 2.6 scenarios. The impact on HNO3 surface concentrations is more disparate between the two scenarios regarding the spatial repartition of effects. In the case of the RCP 4.5 scenario, a significant increase of the surface O3 concentration reaching locally by up to 5 ppb (+5 %) is calculated on average during the June–August period. This scenario also induces an increase of HNO3 deposited flux exceeding locally 10 % for monthly values. Comparing the impact of land-cover change to the impact of climate change, considering a 0.93 °C increase of global temperature, on dry deposition velocities, we estimate that the strongest increase over lands occurs in the Northern Hemisphere during winter, especially in Eurasia, by +50 % (+0.07 cm s−1) for Vd,O3 and +100 % (+0.9 cm s−1) for Vd,HNO3. However, different regions are affected by both changes, with climate change impact on deposition characterized by a latitudinal gradient, while the land-cover change impact is much more heterogeneous depending on vegetation distribution modification described in the future RCP scenarios. The impact of long-term land-cover changes on dry deposition is shown to be significant and to differ strongly from one scenario to another. It should therefore be considered in biosphere–atmospheric chemistry interaction studies in order to have a fully consistent picture.


2015 ◽  
Vol 15 (13) ◽  
pp. 18459-18485
Author(s):  
T. Verbeke ◽  
J. Lathière ◽  
S. Szopa ◽  
N. de Noblet-Ducoudré

Abstract. Dry deposition is a key component of surface–atmosphere exchange of compounds, acting as a sink for several chemical species. Meteorological factors, chemical properties of the trace gas considered and land surface properties are strong drivers of dry deposition efficiency and variability. Under both climatic and anthropogenic pressure, the vegetation distribution over the Earth has been changing a lot over the past centuries, and could be significantly altered in the future. In this study, we perform a modeling investigation of the potential impact of land-cover changes between present-day (2006) and the future (2050) on dry deposition rates, with special interest for ozone (O3) and nitric acid vapor (HNO3), two compounds which are characterized by very different physico-chemical properties. The 3-D chemistry transport model LMDz-INCA is used, considering changes in vegetation distribution based on the three future projections RCPs 2.6, 4.5 and 8.5. The 2050 RCP 8.5 vegetation distribution leads to a rise up to 7 % (+0.02 cm s−1) in VdO3 and a decrease of −0.06 cm s−1 in VdHNO3 relative to the present day values in tropical Africa, and up to +18 and −15 % respectively in Australia. When taking into account the RCP 4.5 scenario, which shows dramatic land cover change in Eurasia, VdHNO3 increases by up to 20 % (annual-mean value) and reduces VdO3 by the same magnitude in this region. When analyzing the impact of dry deposition change on atmospheric chemical composition, our model calculates that the effect is lower than 1 ppb on annual mean surface ozone concentration, for both for the RCP8.5 and RCP2.6 scenarios. The impact on HNO3 surface concentrations is more disparate between the two scenarios, regarding the spatial repartition of effects. In the case of the RCP 4.5 scenario, a significant increase of the surface O3 concentration reaching locally up to 5 ppb (+5 %) is calculated on average during the June–August period. This scenario induces also an increase of HNO3 deposited flux exceeding locally 10 % for monthly values. Comparing the impact of land-cover change to the impact of climate change, considering a 0.93 °C increase of global temperature, on dry deposition velocities, we estimate that the strongest increase over lands occurs in the North Hemisphere during winter especially in Eurasia, by +50 % (+0.07 cm s−1) for VdO3 and +100 % (+0.9 cm s−1) for VdHNO3. However, different regions are affected by both changes, with climate change impact on deposition characterized by a latitudinal gradient, while the land-cover change impact is much more heterogeneous depending on vegetation distribution modification described in the future RCP scenarios. The impact of long-term land-cover changes on dry deposition is shown to be non-negligible and should be therefore considered in biosphere-atmospheric chemistry interaction studies in order to have a fully consistent picture.


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