scholarly journals Changing Landscapes Forest: Implications for its Conservation

2018 ◽  
Vol 8 (3) ◽  
pp. 44
Author(s):  
James Rodríguez-Echeverry ◽  
Rodrigo Fuentes ◽  
Margareth Leiton ◽  
Edilia Jaque
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Spatial Pattern ◽  
Exotic Species ◽  
Land Use Planning ◽  
Forest Ecosystem ◽  
Conservation Strategies ◽  
Native Forest ◽  
Forest Landscape ◽  
The Impact

AbstractThe forest landscape of southern Chile, which includes Chilean temperate forest ecosystem, has been designated as a hotspot for biodiversity conservation. However, this landscape has been transformed by land-use change. A proper knowledge about how land-use change impact this ecosystem would provide crucial information for planning conservation strategies. At the commune of Arauco – Chile, the impact of the land-use change on the spatial pattern of native forest ecosystem from 1990 to 2010 was evaluated at the landscape level. This evaluation was carried out using satellite images, landscape metrics and spatially explicit models. The loss of native forest ecosystem was of 40.7% (loss rate of 4.39% per year). Conversely, the exotic species plantations increased more than 150%. The number patches of native forest ecosystem increased more than 130%. The size distribution of patches (<100 ha) increased more than 22%. The aggregation index of native forest ecosystem decreased from 62.5 to 40.1. The loss of native forest ecosystem was caused by the expansion of exotic species plantations, which was associated with substantial changes in the spatial pattern of the forest landscape. As a strategy for conservation of the native forest ecosystem we suggest a landscape approach, using the corridor–patch–matrix model. We recommend that this strategy be complemented with land-use planning. Moreover, this strategy must be supported by a framework of environmental policies. We also recommend strengthening the existing ecological restoration programmes and developing new programmes to restore the native forest ecosystem.

scholarly journals The Impact of Anthropogenic Land-Use Change on Soil Organic Carbon, Oporae Valley, Lake Tutira, New Zealand

2021 ◽  
Author(s):  
◽  
Roderick Charles James Boys
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Sedimentation Rate ◽  
Large Scale ◽  
Slope Angle ◽  
Carbon Accounting ◽  
Native Forest ◽  
The Impact

<p>During the anthropocene land use change has exacerbated erosion of the Soil Organic Carbon (SOC) rich topsoil in the Oporae Valley. As well as reducing the SOC content of the contemporary topsoil, the large scale redistribution of sediment has created a quantifiable long-term SOC sink in paleosols. Using contemporary native forest soils as a proxy, pasture covered topsoils contain ~40% less SOC (a loss of 5,338 T/[square kilometer] SOC). The pre-human paleosol at ~200 cm, an average 32 cm thickness, contains 9180 T/[square kilometer]. Significantly more SOC buried at depth than what currently exists in the contemporary topsoil indicates the relative importance of paleosols as C stores and the role of land use change on SOC. The preservation characteristics of a paleosol in the Oporae Valley are determined by slope angle and the relative position they hold in relation to the inter-fingering of the alluvial toeslope with the colluvial footslope. Groupings of [radioisotope carbon-14] ages in and above the pre-human paleosol allow for calculation of terrestrial sedimentation rates. At ~0.9 mm yr^-1 the terrestrial pre-human sedimentation rate averaged over the valley floor is approximately half (0.53) of the corresponding pre-human lake rate of ~1.7 mm yr^-1. As a proportion of the lake's anthropogenic sedimentation rate at ~4.8 mm yr^-1, the terrestrial anthropogenic sedimentation rate has slightly increased to ~2.8 mm yr^-1 (0.58 of the lake sedimentation rate). These initial findings demonstrate the potential for further research in this area, so that ongoing land-use change can be accurately incorporated into terrestrial carbon accounting.</p>

scholarly journals 3D soil void space lacunarity as an index of degradation after land use change

2020 ◽  
Vol 42 ◽  
pp. e42491
Author(s):  
Carlos Renato dos Santos ◽  
Antônio Celso Dantas Antonino ◽  
Richard John Heck ◽  
Leandro Ricardo Rodrigues de Lucena ◽  
Alex Cristóvão Holanda de Oliveira ◽  
...  
Keyword(s):  
Land Use ◽  
Spatial Distribution ◽  
Land Use Change ◽  
Native Forest ◽  
Void Space ◽  
Lower Porosity ◽  
Porous Soil ◽  
The Impact ◽  
Soil Pores ◽  
Lacunarity Analysis

In this work, lacunarity analysis is performed on soil pores segmented by the pure voxel extraction method from soil tomography images. The conversion of forest to sugarcane plantation was found to result in higher sugarcane soil pore lacunarity than that of native forest soil, while the porosity was found to be lower. More precisely, this study shows that native forest has more porous soil with a more uniform spatial distribution of pores, while sugarcane soil has lower porosity and a more heterogeneous pore distribution. Moreover, validation through multivariate statistics demonstrates that lacunarity can be considered a relevant index of clustering and can explain the variability among soils under different land use systems. While porosity by itself represents a fundamental concept for quantification of the impact of land use change, the current findings demonstrate that the spatial distribution of pores also plays an important role and that pore lacunarity can be adopted as a complementary tool in studies directed at quantifying the effect of human intervention on soils.

scholarly journals Land Use Change Ontology and Traffic Prediction through Recurrent Neural Networks: A Case Study in Calgary, Canada

2021 ◽  
Vol 10 (6) ◽  
pp. 358
Author(s):  
Abul Azad ◽  
Xin Wang
Keyword(s):  
Neural Network ◽  
Land Use ◽  
Deep Learning ◽  
Land Use Change ◽  
Traffic Flow ◽  
Land Use Planning ◽  
Transportation Planning ◽  
Traffic Prediction ◽  
Modeling Approach ◽  
The Impact

Land use and transportation planning have a significant impact on the performance of cities’ traffic conditions and the quality of people’s lives. The changing characteristics of land use will affect and challenge how a city is able to manage, organize, and plan for new developments and transportation. These challenges can be better addressed with effective methods of monitoring and predicting, which can enable optimal efficiency in how a growing city like Calgary, Canada, can perform. Using ontology in land use planning is a new initiative currently being researched and explored. In this regard, ontology incorporates relationships between the various entities of land use. The aim of this study is to present Land Use Change Ontology (LUCO) with a deep neural network for traffic prediction. We present a Land Use Change Ontology (LUCO) approach, using expressions of how the semantics of land use changes relate to the integration of temporal land use information. This study examines the City of Calgary’s land use data from the years 2001, 2010, and 2015. In applying the LUCO approach to test data, experimental outcomes indicated that from 2001 to 2015 residential land use increased by 30% and open space decreased by 40%. Forecasting traffic is increasingly essential for successful traffic modelling, operations, and management. However, traditional means for predicting traffic flow have largely assumed restrictive model architectures that have not controlled for the amounts of land use change. Inspired by deep learning methods and effective data mining computing capabilities, this paper introduces the deep learning Recurrent Neural Network (RNN) to predict traffic while considering the impact of land use change. The RNN was successful in learning the features of traffic flow under various land use change situations. Experimental results indicated that, with the consideration of LUCO, the deep learning predictors had better accuracy when compared with other existing models. Success of our modeling approach indicates that cities could apply this modeling approach to make land use transportation planning more efficient.

scholarly journals The Impact of Anthropogenic Land-Use Change on Soil Organic Carbon, Oporae Valley, Lake Tutira, New Zealand

2021 ◽  
Author(s):  
◽  
Roderick Charles James Boys
Keyword(s):  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Sedimentation Rate ◽  
Large Scale ◽  
Slope Angle ◽  
Carbon Accounting ◽  
Native Forest ◽  
The Impact

<p>During the anthropocene land use change has exacerbated erosion of the Soil Organic Carbon (SOC) rich topsoil in the Oporae Valley. As well as reducing the SOC content of the contemporary topsoil, the large scale redistribution of sediment has created a quantifiable long-term SOC sink in paleosols. Using contemporary native forest soils as a proxy, pasture covered topsoils contain ~40% less SOC (a loss of 5,338 T/[square kilometer] SOC). The pre-human paleosol at ~200 cm, an average 32 cm thickness, contains 9180 T/[square kilometer]. Significantly more SOC buried at depth than what currently exists in the contemporary topsoil indicates the relative importance of paleosols as C stores and the role of land use change on SOC. The preservation characteristics of a paleosol in the Oporae Valley are determined by slope angle and the relative position they hold in relation to the inter-fingering of the alluvial toeslope with the colluvial footslope. Groupings of [radioisotope carbon-14] ages in and above the pre-human paleosol allow for calculation of terrestrial sedimentation rates. At ~0.9 mm yr^-1 the terrestrial pre-human sedimentation rate averaged over the valley floor is approximately half (0.53) of the corresponding pre-human lake rate of ~1.7 mm yr^-1. As a proportion of the lake's anthropogenic sedimentation rate at ~4.8 mm yr^-1, the terrestrial anthropogenic sedimentation rate has slightly increased to ~2.8 mm yr^-1 (0.58 of the lake sedimentation rate). These initial findings demonstrate the potential for further research in this area, so that ongoing land-use change can be accurately incorporated into terrestrial carbon accounting.</p>

scholarly journals Dynamics of soil organic carbon in the steppes of Russia and Kazakhstan under past and future climate and land use

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Susanne Rolinski ◽  
Alexander V. Prishchepov ◽  
Georg Guggenberger ◽  
Norbert Bischoff ◽  
Irina Kurganova ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Organic Carbon ◽  
Land Use Change ◽  
Soil Organic Carbon ◽  
Arable Land ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Scenarios ◽  
The Impact

AbstractChanges in land use and climate are the main drivers of change in soil organic matter contents. We investigated the impact of the largest policy-induced land conversion to arable land, the Virgin Lands Campaign (VLC), from 1954 to 1963, of the massive cropland abandonment after 1990 and of climate change on soil organic carbon (SOC) stocks in steppes of Russia and Kazakhstan. We simulated carbon budgets from the pre-VLC period (1900) until 2100 using a dynamic vegetation model to assess the impacts of observed land-use change as well as future climate and land-use change scenarios. The simulations suggest for the entire VLC region (266 million hectares) that the historic cropland expansion resulted in emissions of 1.6⋅ 1015 g (= 1.6 Pg) carbon between 1950 and 1965 compared to 0.6 Pg in a scenario without the expansion. From 1990 to 2100, climate change alone is projected to cause emissions of about 1.8 (± 1.1) Pg carbon. Hypothetical recultivation of the cropland that has been abandoned after the fall of the Soviet Union until 2050 may cause emissions of 3.5 (± 0.9) Pg carbon until 2100, whereas the abandonment of all cropland until 2050 would lead to sequestration of 1.8 (± 1.2) Pg carbon. For the climate scenarios based on SRES (Special Report on Emission Scenarios) emission pathways, SOC declined only moderately for constant land use but substantially with further cropland expansion. The variation of SOC in response to the climate scenarios was smaller than that in response to the land-use scenarios. This suggests that the effects of land-use change on SOC dynamics may become as relevant as those of future climate change in the Eurasian steppes.

scholarly journals Multi-Temporal Built-Up Grids of Brazilian Cities: How Trends and Dynamic Modelling Could Help on Resilience Challenges?

2021 ◽  
Vol 13 (2) ◽  
pp. 748
Author(s):  
Iana Rufino ◽  
Slobodan Djordjević ◽  
Higor Costa de Brito ◽  
Priscila Barros Ramalho Alves
Keyword(s):  
Land Use ◽  
Urban Planning ◽  
Cellular Automata ◽  
Land Use Change ◽  
Spatial Pattern ◽  
Urban Growth ◽  
Spatial Information ◽  
Dynamic Modelling ◽  
Urban Models ◽  
Extreme Hazards

The northeastern Brazilian region has been vulnerable to hydrometeorological extremes, especially droughts, for centuries. A combination of natural climate variability (most of the area is semi-arid) and water governance problems increases extreme events’ impacts, especially in urban areas. Spatial analysis and visualisation of possible land-use change (LUC) zones and trends (urban growth vectors) can be useful for planning actions or decision-making policies for sustainable development. The Global Human Settlement Layer (GHSL) produces global spatial information, evidence-based analytics, and knowledge describing Earth’s human presence. In this work, the GHSL built-up grids for selected Brazilian cities were used to generate urban models using GIS (geographic information system) technologies and cellular automata for spatial pattern simulations of urban growth. In this work, six Brazilian cities were selected to generate urban models using GIS technologies and cellular automata for spatial pattern simulations of urban sprawl. The main goal was to provide predictive scenarios for water management (including simulations) and urban planning in a region highly susceptible to extreme hazards, such as floods and droughts. The northeastern Brazilian cities’ analysis raises more significant challenges because of the lack of land-use change field data. Findings and conclusions show the potential of dynamic modelling to predict scenarios and support water sensitive urban planning, increasing cities’ coping capacity for extreme hazards.

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