Land2014, 3(3), 850-873; doi:10.3390/land3030850 (doi registration under processing) - published online 23 July 2014 Show/Hide Abstract
Abstract: Land use patterns are the consequence of dynamic processes that often include important legacy issues. Evaluation of past trends can be used to investigate the role of path dependence in influencing future land use through a reference “business as usual” (BAU) scenario. These issues are explored with regard to objectives for woodland expansion in Scotland as a major pillar of climate change policy. Land use changes based upon recent trends and future transient scenarios to 2050 are used to assess viability of targets for reducing greenhouse gas emissions using analysis based on net emission change factors. The BAU scenario is compared with alternative future scenarios incorporating policy targets and stronger spatial targeting of land use change. Analysis highlights recent trends in new woodland planting on lower quality agricultural land due to socioeconomic and cultural factors. This land is mainly in the wetter uplands and often on carbon-rich soils. Woodland planting following this path dependence can therefore result in net carbon emissions for many years into the future due to soil disturbance during establishment. In contrast, alternative scenarios with more lowland woodland planting have net sequestration potential, with greatest benefits when carbon-rich soils are excluded from afforestation. Spatial targeting can also enhance other co-benefits such as habitat networks and climate change adaptation.
Land2014, 3(3), 834-849; doi:10.3390/land3030834 (doi registration under processing) - published online 23 July 2014 Show/Hide Abstract
Abstract: Conservation thinking will benefit from the incorporation of a resilience perspective of landscapes as social-ecological systems that are continually changing due to both internal dynamics and in response to external factors such as a changing climate. The examination of two valley oak stands in Southern California provides an example of the necessity of this systems perspective where each stand is responding differently as a result of interactions with other parts of the landscape. One stand is experiencing regeneration failure similar to other stands across the state, and is exhibiting shifts in spatial pattern as a response to changing conditions. A nearby stand is regenerating well and maintaining spatial and structural patterns, likely due to the availability of imported water associated with upstream urban development. Valley oak stands have a capacity for reorganization as a response to changes in the landscape and environmental conditions. This reorganization can benefit conservation efforts; however, we must ask what limits there are to valley oak’s capacity to reorganize and still maintain its ecological function in face of increasing changes in climate and land cover. The usefulness of resilience as a concept in conservation is discussed at several scales from the stand to the landscape.
Land2014, 3(3), 793-833; doi:10.3390/land3030793 - published online 22 July 2014 Show/Hide Abstract
Abstract: International agreements on climate change have highlighted the role of land in climate and human dynamics, making it an issue of global importance. The modelling of land-related processes, sectors, and activities has recently become a central topic in economic and policy theory, as well as within environmental sciences. Modelling strategies have been improved and new datasets have come into light for land-cover and land-use change analysis. However, unexpected human behavior and natural constraints challenge the modelling of interdependences and feedback mechanisms amongst economies, societies, and the environment, resulting from land-use and cover change. This paper provides a detailed overview of the most representative and advanced methods and models developed to represent climate–human–land interactions. It offers a critical discussion about relevant methodological aspects, missing knowledge, and areas for future research.
Land2014, 3(3), 770-792; doi:10.3390/land3030770 - published online 18 July 2014 Show/Hide Abstract
Abstract: Climatic stress and anthropogenic disturbances have caused significant environmental changes in the Sahel. In this context, the importance of soil is often underrepresented. Thus, we analyze and discuss the interdependency of soil and vegetation by classifying soil types and its woody cover for a region in the Senegalese Ferlo. Clustering of 28 soil parameters led to four soil types which correspond with local Wolof denotations: Dek, Bowel, Dior and Bardial. The soil types were confirmed by a Non-metric Multidimensional-Scaling (NMDS) ordination and extrapolated via a Random Forest classifier using six significant variables derived from Landsat imagery and a digital elevation model (out-of-bag error rate: 7.3%). In addition, canopy cover was modeled using Landsat and a Reduced-Major-Axis (RMA) regression (R2 = 0.81). A woody vegetation survey showed that every soil type has its own species composition. However, 29% of Bowel regions are deforested (i.e., degraded) and interviews revealed extensive environmental changes and a strong decline and local extinction of woody species. The differences between the soil types are significant, showing that vegetation changes (i.e., degradation and greening), resilience to climatic stress and human activities largely depend on soil properties. We highlight that spatial heterogeneity is an important aspect when dealing with environmental changes in the Sahel, and local knowledge can be well used to classify spatial units by means of public Earth observation data.
Land2014, 3(3), 739-769; doi:10.3390/land3030739 - published online 18 July 2014 Show/Hide Abstract
Abstract: Agroecology and landscape ecology are two land-use sciences based on ecological principles, but have historically focused on fine and broad spatial scales, respectively. As global demand for food strains current resources and threatens biodiversity conservation, concepts such as multifunctional landscapes and ecologically-analogous agroecosystems integrate ecological concepts across multiple spatial scales. This paper reviews ecological principles behind several concepts crucial to the reconciliation of food production and biodiversity conservation, including relationships between biodiversity and ecosystem functions such as productivity and stability; insect pest and pollinator management; integrated crop and livestock systems; countryside biogeography and heterogeneity-based rangeland management. Ecological principles are integrated across three spatial scales: fields, farms, and landscapes.
Land2014, 3(3), 719-738; doi:10.3390/land3030719 - published online 18 July 2014 Show/Hide Abstract
Abstract: This paper presents a method to optimise the calibration of parameters and land use transition rules of a cellular automata (CA) urban growth model using a self-adaptive genetic algorithm (SAGA). Optimal calibration is achieved through an algorithm that minimises the difference between the simulated and observed urban growth. The model was applied to simulate land use change from non-urban to urban in South East Queensland’s Logan City, Australia, from 1991 to 2001. The performance of the calibrated model was evaluated by comparing the empirical land use change maps from the Landsat imagery to the simulated land use change produced by the calibrated model. The simulation accuracies of the model show that the calibrated model generated 86.3% correctness, mostly due to observed persistence being simulated as persistence and some due to observed change being simulated as change. The 13.7% simulation error was due to nearly equal amounts of observed persistence being simulated as change (7.5%) and observed change being simulated as persistence (6.2%). Both the SAGA-CA model and a logistic-based CA model without SAGA optimisation have simulated more change than the amount of observed change over the simulation period; however, the overestimation is slightly more severe for the logistic-CA model. The SAGA-CA model also outperforms the logistic-CA model with fewer quantity and allocation errors and slightly more hits. For Logan City, the most important factors driving urban growth are the spatial proximity to existing urban centres, roads and railway stations. However, the probability of a place being urbanised is lower when people are attracted to work in other regions.