Regional impact analysis of climate change on natural and managed forests in the Federal State of Brandenburg, Germany

A methodology for regional application of forest simulation models has been developed as part of an assessment of possible climate change impacts in the Federal state of Brandenburg (Germany). Here we report on the application of a forest gap model to analyse the impacts of climate change on species composition and productivity of natural and managed forests in Brandenburg using a statistical method for the development of climate scenarios. The forest model was linked to a GIS that includes soil and groundwater table maps, as well as gridded climate data with a resolution of 10 × 10 km and simulated a steady-state species composition which was classified into forest types based on the biomass distribution between species. Different climate scenarios were used to assess the sensitivity of species composition to climate change. The simulated forest distribution patterns for current climate were compared with a map of Potential Natural Vegetation (PNV) of Brandenburg.In order to analyse the possible consequences of climate change on forest management, we used forest inventory data to initialize the model with representative forest stands. Simulation experiments with two different management strategies indicated how forest management could respond to the projected impacts of climate change. The combination of regional analysis of natural forest dynamics under climate change with simulation experiments for managed forests outlines possible trends for the forest resources. The implications of the results are discussed, emphasizing the regional differences in environmental risks and the adaptation potentials of forestry in Brandenburg.     

Analysis of the spatio-temporal and semantic aspects of land-cover/use change dynamics 1991–2001 in Albania at national and district levels

In the turmoil of a rapidly changing economy the Albanian government needs accurate and timely information for management of their natural resources and formulation of land-use policies. The transformation of the forestry sector has required major changes in the legal, regulatory and management framework. The World Bank financed Albanian National Forest Inventory project provides an analysis of spatially explicit land-cover/use change dynamics in the period 1991–2001 using the FAO/UNEP Land Cover Classification System for codification of classes, satellite remote sensing and field survey for data collection and elements of the object-oriented geo-database approach to handle changes as an evolution of land-cover/use objects, i.e. polygons, over time to facilitate change dynamics analysis.Analysis results at national level show the trend of natural resources depletion in the form of modifications and conversions that lead to a gradual shift from land-cover/use types with a tree cover to less dense tree covers or even a complete removal of trees. Policy failure (e.g., corruption, lack of law enforcement) is seen as the underlying cause. Another major trend is urbanisation of areas near large urban centres that change urban-rural linkages. Furthermore, after privatisation agricultural areas increased in the hills where environmental effects may be detrimental, while prime agricultural land in the plains is lost to urbanisation.At district level, the local variability of spatially explicit land-cover/use changes shows different types of natural resources depletion. The distribution of changes indicates a regional prevalence, thus a decentralised approach to the natural resources management could be advocated.     

A necessary distinction between spatial representativeness of an air quality monitoring station and the delimitation of exceedance areas

The European legislation on ambient air quality introduces the concepts of spatial representativeness of a monitoring station and spatial extent of an exceedance zone. Spatial representativeness is an essential macro-scale siting criterion which should be evaluated before the setting-up and during the life of a monitoring point. As for the exceedance area, it has to be defined each time an environmental objective is exceeded in an assessment zone. No specific approach is prescribed to delimit such areas. A probabilistic methodology is presented, based on a preliminary kriging estimation of atmospheric concentrations at each point of the domain. It is applied to NO₂ pollution on the urban scale. In the proposed approach, a point belongs to the area of representativeness of a station if its concentration differs from the station measurement by less than a given threshold. To take the estimation uncertainty into account, the standard deviation of the kriging error is used in a probabilistic framework. The choice of the criteria used to deal with overlapping areas is first tested on NO₂ annual mean concentration maps of France, built by combining surface monitoring observations and outputs from the CHIMERE chemistry transport model. At the local scale, data from passive sampling surveys and high -resolution auxiliary variables are used to provide a more precise estimation of the background pollution in different French cities. The traffic-related pollution can also be accounted for in the map by additional predictors such as distance to the road, and traffic-related NO_x emissions. Similarly, the proposed approach is implemented to identify the points, at a given statistical risk, where the NO₂ concentration is above the annual limit value.     

Monitoring of Biodiversity Indicators in Boreal Forests: a Need for Improved Focus

The general principles of scale and coarse and fine filters have been widely accepted, but management agencies and industry are still grappling with the question of what to monitor to detect changes in forest biodiversity following forest management. Part of this problem can be attributed to the lack of focused questions for monitoring including absence of null models and predicted effects, a certain level of disconnect between research and management, and recognition that monitoring can be designed as a research question. Considerable research from the past decade has not been adequately synthesized to answer important questions, such as which species or forest attributes might be the best indicators of change. A disproportionate research emphasis has been placed on community ecology, and mostly on a few groups of organisms including arthropods, amphibians, migratory songbirds, and small mammals, while other species, including soil organisms, lichens, bats, raptors, some carnivores, and larger mammals remain less well-known. In most studies of community ecology, the question of what is the importance, if any, of the regularly observed subtle changes in community structures, and causes of observed changes is usually not answered. Hence, our ability to deal with questions of persistence is limited, and demographic research on regionally--defined key species (such as species linked to processes, species whose persistence may be affected, species with large home ranges, species already selected as indicators, and rare and threatened species) is urgently needed. Monitoring programs need to be designed to enable managers to respond to unexpected changes caused by forest management. To do this, management agencies need to articulate null models for monitoring that predict effects, focus fine--scale monitoring on key species (defined by local and regional research) in key habitats (rare, declining, important) across landscapes, and have a protocol in place to adapt management strategies to changes observed. Finally, agencies must have some way to determine and define when a significant change has occurred and to predict the persistence of species; this too should flow from a well--designed null model.     

Application of a Life Cycle Simulation Model to Evaluate Impacts of Water Management and Conservation Actions on an Endangered Population of Chinook Salmon

Fisheries and water resource managers are challenged to maintain stable or increasing populations of Chinook salmon in the face of increasing demand on the water resources and habitats that salmon depend on to complete their life cycle. Alternative management plans are often selected using professional opinion or piecemeal observations in place of integrated quantitative information that could reduce uncertainty in the effects of management plans on population dynamics. We developed a stochastic life cycle simulation model for an endangered population of winter-run Chinook salmon in the Sacramento River, California, USA with the goal of providing managers a tool for more effective decision making and demonstrating the utility of life cycle models for resource management. Sensitivity analysis revealed that the input parameters that influenced variation in salmon escapement were dependent on which age class was examined and their interactions with other inputs (egg mortality, Delta survival, ocean survival). Certain parameters (river migration survival, harvest) that were hypothesized to be important drivers of population dynamics were not identified in sensitivity analysis; however, there was a large amount of uncertainty in the value of these inputs and their error distributions. Thus, the model also was useful in identifying future research directions. Simulation of variation in environmental inputs indicated that escapement was significantly influenced by a 10% change in temperature whereas larger changes in other inputs would be required to influence escapement. The model presented provides an effective demonstration of the utility of life cycle simulation models for decision making and provides fisheries and water managers in the Sacramento system with a quantitative tool to compare the impact of different resource use scenarios.     

Compositing climate change vulnerability of a Mediterranean region using spatiotemporally dynamic proxies for ecological and socioeconomic impacts and stabilities

The study presents a new methodology to quantify spatiotemporal dynamics of climate change vulnerability at a regional scale adopting a new conceptual model of vulnerability as a function of climate change impacts, ecological stability, and socioeconomic stability. Spatiotemporal trends of equally weighted proxy variables for the three vulnerability components were generated to develop a composite climate change vulnerability index (CCVI) for a Mediterranean region of Turkey combining Landsat time series data, digital elevation model (DEM)-derived data, ordinary kriging, and geographical information system. Climate change impact was based on spatiotemporal trends of August land surface temperature (LST) between 1987 and 2016. Ecological stability was based on DEM, slope, aspect, and spatiotemporal trends of normalized difference vegetation index (NDVI), while socioeconomic stability was quantified as a function of spatiotemporal trends of land cover, population density, per capita gross domestic product, and illiteracy. The zones ranked on the five classes of no-to-extreme vulnerability were identified where highly and moderately vulnerable lands covered 0.02% (12 km²) and 11.8% (6374 km²) of the study region, respectively, mostly occurring in the interior central part. The adoption of this composite CCVI approach is expected to lead to spatiotemporally dynamic policy recommendations towards sustainability and tailor preventive and mitigative measures to locally specific characteristics of coupled ecological–socioeconomic systems.     

Changes in water level,land use,and hydrological budget in a semi-permanent playa lake,Southwest Spain

Medina playa lake, a Ramsar site in western Andalusia, is a brackish lowland lake of 120 ha with an average depth of 1 m. Water flows into Medina from its 1,748-ha watershed, but the hydrology of the lake has not previously been studied. This paper describes the application of a water budget model on a monthly scale over a 6-year period, based on a conceptual hydrological model, and considers different future scenarios after calibration to improve the understanding of the lake’s hydrological functioning. Climatic variables from a nearby weather station and observational data (water-level evolution) were used to develop the model. Comparison of measured and predicted values demonstrated that each model component provided a reasonable output with a realistic interaction among the components. The model was then used to explore the potential consequences of land-use changes. Irrigation of olive groves would significantly reduce both the hydroperiod (becoming dry 15% of the time) and the average depth of the lake (water level <0.5 m 40% of the time). On the other hand, removal of an artificial overflow would double the average flooded surface area during high-water periods. The simulated water balance demonstrates that the catchment outputs are dominated by lake evaporation and surface outflow from the lake system to a creek. Discrepancies between predicted and observed water levels identify key areas of uncertainty for future empirical research. The study provides an improved basis for future hydrological management of the catchment and demonstrates the wider utility of this methodology in simulating this kind of system. This methodology provides a realistic appraisal of potential land-use management practices on a catchment-wide scale and allows predictions of the consequences of climate change.     

Holling's Figure-Eight Model: A Technical Reevaluation in Relation to Climate Change and Biodiversity

Holling proposed a four-phase conceptual model of ecosystem dynamics that includes exploitation, conservation, and destructive and renewal components to explain the failure of many natural resource management schemes. The model is drawn as a sideways figure-eight i.e. . There are two dimensions in this model, connectivity (abscissa) and the amount of capital stored in the system (ordinate). This conceptual model has been suggested as a guide to thinking about the impact of climate change on biodiversity, but the two dimensions are insufficient and the alignment of the figure-eight model is problematic when compared with actual data. Kay has adjusted the dimensions of the figure-eight model and renamed the abscissa as exergy stored and the ordinate as exergy consumed. We realign the original figure-eight model, labeling the abscissa as carbon stored and the ordinate as nutrients, such that the relative values of both axes are in qualitative agreement with data from four different studies. This new alignment is then shown to fit relatively well with Holling's original labels. This revision of the figure-eight model brings Holling's model into agreement with observations and provides insight into the linkages between biodiversity and climate change.     

Urban water resource management for sustainable environment planning using artificial intelligence techniques

In the current era, water is a significant resource for socio-economic growth and the protection of healthy environments. Properly controlled water resources are considered a vital part of development, which reduces poverty and equity. Conventional Water system Management maximizes the existing water flows available to satisfy all competing demands, including on-site water and groundwater. Therefore, Climatic change would intensify the specific challenges in water resource management by contributing to uncertainty. Sustainable water resources management is an essential process for ensuring the earth's life and the future. Nonlinear effects, stochastic dynamics, and hydraulic constraints are challenging in ecological planning for sustainable water development. In this paper, Adaptive Intelligent Dynamic Water Resource Planning (AIDWRP) has been proposed to sustain the urban areas' water environment. Here, an adaptive intelligent approach is a subset of the Artificial Intelligence (AI) technique in which environmental planning for sustainable water development has been modeled effectively. Artificial intelligence modeling improves water efficiency by transforming information into a leaner process, improving decision-making based on data-driven by combining numeric AI tools and human intellectual skills. In AIDWRP, Markov Decision Process (MDP) discusses the dynamic water resource management issue with annual use and released locational constraints that develop sensitivity-driven methods to optimize several efficient environmental planning and management policies. Consequently, there is a specific relief from the engagement of supply and demand for water resources, and substantial improvements in local economic efficiency have been simulated with numerical outcomes.     

Brazilian LTER: Ecosystem and Biodiversity Information in Support of Decision-Making

Brazil officially joined the International Long Term Ecological Research (ILTER) network in January 2000, when nine research sites were created and funded by the Brazilian Council for Science and Technology (CNPq). Two-years later some positive signs already emerge of the scientific, social and political achievements of the Brazilian LTER program. We discuss examples of how ecosystem and biodiversity information gathered within a long-term research approach are currently subsidizing decision-making as regards biodiversity conservation and watershed management at local and regional scales. Success in this respect has often been related to satisfactory communication between scientists, private companies, government and local citizens. Environmental education programs in the LTER sites are playing an important role in social and political integration. Most examples of integration of ecological research to decision-making in Brazil derive from case studies at local or regional scale. Despite the predominance of a bottom-up integrative pathway (from case studies to models; from local to national scale), some top-down initiatives are also in order, such as the construction of a model to estimate the inpact of different macroeconomic policies and growth trajectories on land use. We believe science and society in Brazil will benefit of the coexistence of bottom-up and top-down integrative approaches.     

Agricultural land-use change and ash (<Emphasis Type="Italic">Fraxinus excelsior</Emphasis> L.) colonization in Pyrenean landscapes: an interdisciplinary case study

Changes in agricultural land use are responsible for significant modifications in mountain landscapes. This study is part of an interdisciplinary research on the processes and consequences of spontaneous afforestation of Pyrenean landscapes by ash, and the possibilities for its management. We address the relationships between vegetation dynamics and land-use change from the combination of an agricultural study of change in farm management and an ecological study of grassland colonization by ash. In the framework of a village case study, we characterized parcels management and land-use histories, and analyzed the dynamics of the composition of grassland vegetation communities. From a joint analysis of the results obtained in each discipline, we discuss the limitations and complementarities of the two approaches for the interdisciplinary assessment of the afforestation process.     

The relative role of climate change and human activities in the desertification process in Yulin region of northwest China

To overcome the shortcoming of existing studies, this paper put forward a statistical vegetation–climate relationship model with integrated temporal and spatial characteristics. Based on this model, we quantitatively discriminated on the grid scale the relative role of climate change and human activities in the desertification dynamics from 1986 to 2000 in Yulin region. Yulin region’s desertification development occurred mainly in the southern hilly and gully area and its reverse in the northwest sand and marsh area. This spatial pattern was especially evident and has never changed thoroughly. From the first time section (1986–1990) to the second (1991–1995), the desertification was developing as a whole, and either in the desertification development district or in the reverse district human activities’ role was always occupying an overwhelmingly dominant position (they were 98.7% and 101.4%, respectively), the role of climate change was extremely slight. From the second time section (1991–1995) to the third (1996–2000), the desertification process was reaching a state of stability, in the desertification development district the role of climate change was nearly equivalent to that of human activities (they were 46.2% and 53.8% separately), and yet in the desertification reverse district, the role of human activities came up to 119.0%, the role of climate change amounted to ?19.0%. In addition, the relative role of climate change and human activities possessed great spatial heterogeneity. The above conclusion rather coincides with the qualitative analysis in many literatures, which indicates that this method has certain rationality and can be utilized as a reference for the monitoring and studying of desertification in other areas.     

Waste management modeling by MARKAL model: A case study for Basilicata Region

Air pollution is one of the most pressing environmental problems which affects likewise urban, industrial and rural areas. Environmental planners, regulators and decision makers need reliable, scientifically based tools to find out strategies for controlling air pollution in a cost-effective way, taking into account the whole productive system. In this framework the basic elements of energy-environmental planning have to be extended to include also waste processing technologies amongst the usually considered pollution sources. Bottom-up optimizing models, based on linear programming techniques and customized for specific cases, represent a powerful tool in energy-environmental management. This paper focuses on the integrated modeling of material flows and energy system performed on a local scale case study (Basilicata Region, Southern Italy) using the linear programming model IEA-MARKAL. We have evaluated the feasibility of the model in representing the waste management system to estimate the environmental impact of the waste processing technologies in the context of the whole productive system. A sensitivity analysis has been carried out to emphasize the connections between tariffs, waste disposal technologies assessment and atmospheric emissions. This revised version was published online in July 2006 with corrections to the Cover Date.     

Design to monitor trend in abundance and presence of American beaver (Castor canadensis) at the national forest scale

Wildlife conservationists design monitoring programs to assess population dynamics, project future population states, and evaluate the impacts of management actions on populations. Because agency mandates and conservation laws call for monitoring data to elicit management responses, it is imperative to design programs that match the administrative scale for which management decisions are made. We describe a program to monitor population trends in American beaver (Castor canadensis) on the US Department of Agriculture, Black Hills National Forest (BHNF) in southwestern South Dakota and northeastern Wyoming, USA. Beaver have been designated as a management indicator species on the BHNF because of their association with riparian and aquatic habitats and its status as a keystone species. We designed our program to monitor the density of beaver food caches (abundance) within sampling units with beaver and the proportion of sampling units with beavers present at the scale of a national forest. We designated watersheds as sampling units in a stratified random sampling design that we developed based on habitat modeling results. Habitat modeling indicated that the most suitable beaver habitat was near perennial water, near aspen (Populus tremuloides) and willow (Salix spp.), and in low gradient streams at lower elevations. Results from the initial monitoring period in October 2007 allowed us to assess costs and logistical considerations, validate our habitat model, and conduct power analyses to assess whether our sampling design could detect the level of declines in beaver stated in the monitoring objectives. Beaver food caches were located in 20 of 52 sampled watersheds. Monitoring 20 to 25 watersheds with beaver should provide sufficient power to detect 15–40% declines in the beaver food cache index as well as a twofold decline in the odds of beaver being present in watersheds. Indices of abundance, such as the beaver food cache index, provide a practical measure of population status to conduct long-term monitoring across broad landscapes such as national forests.     

Application of QUAL2Kw for water quality modeling and dissolved oxygen control in the river Bagmati

A stream water quality model, QUAL2Kw, was calibrated and validated for the river Bagmati of Nepal. The model represented the field data quite well with some exceptions. The influences of various water quality management strategies have on DO concentrations were examined considering: (i) pollution loads modification; (ii) flow augmentation; (iii) local oxygenation. The study showed the local oxygenation is effective in raising DO levels. The combination of wastewater modification, flow augmentation and local oxygenation is necessary to ensure minimum DO concentrations. This reasonable modeling guarantees the use of QUAL2Kw for future river water quality policy options.     

Estimation of Vegetation Coverage in Semi-arid Sandy Land Based on Multivariate Statistical Modeling Using Remote Sensing Data

The estimation of vegetation coverage is essential in the monitoring and management of arid and semi-arid sandy lands. But how to estimate vegetation coverage and monitor the environmental change at global and regional scales still remains to be further studied. Here, combined with field vegetation survey, multispectral remote sensing data were used to estimate coverage based on theoretical statistical modeling. First, the remote sensing data were processed and several groups of spectral variables were selected/proposed and calculated, and then statistically correlated to measured vegetation coverage. Both the single- and multiple-variable-based models were established and further analyzed. Among all single-variable-based models, that is based on Normalized Difference Vegetation Index showed the highest R (0.900) and R ² (0.810) as well as lowest standard estimate error (0.128024). Since the multiple-variable-based model using multiple stepwise regression analysis behaved much better, it was determined as the optimal model for local coverage estimation. Finally, the estimation was conducted based on the optimal model and the result was cross-validated. The coefficient of determination used for validation was 0.867 with a root-mean-squared error (RMSE) of 0.101. The large-scale estimation of vegetation coverage using statistical modeling based on remote sensing data can be helpful for the monitoring and controlling of desertification in arid and semi-arid regions. It could serve for regional ecological management which is of great significance.     

A multi-scale metrics approach to forest fragmentation for Strategic Environmental Impact Assessment

Forests are becoming severely fragmented as a result of land development. South Korea has responded to changing community concerns about environmental issues. The nation has developed and is extending a broad range of tools for use in environmental management. Although legally mandated environmental compliance requirements in South Korea have been implemented to predict and evaluate the impacts of land-development projects, these legal instruments are often insufficient to assess the subsequent impact of development on the surrounding forests. It is especially difficult to examine impacts on multiple (e.g., regional and local) scales in detail. Forest configuration and size, including forest fragmentation by land development, are considered on a regional scale. Moreover, forest structure and composition, including biodiversity, are considered on a local scale in the Environmental Impact Assessment process. Recently, the government amended the Environmental Impact Assessment Act, including the SEA, EIA, and small-scale EIA, to require an integrated approach. Therefore, the purpose of this study was to establish an impact assessment system that minimizes the impacts of land development using an approach that is integrated across multiple scales.This study focused on forest fragmentation due to residential development and road construction sites in selected Congestion Restraint Zones (CRZs) in the Greater Seoul Area of South Korea. Based on a review of multiple-scale impacts, this paper integrates models that assess the impacts of land development on forest ecosystems. The applicability of the integrated model for assessing impacts on forest ecosystems through the SEIA process is considered.On a regional scale, it is possible to evaluate the location and size of a land-development project by considering aspects of forest fragmentation, such as the stability of the forest structure and the degree of fragmentation. On a local scale, land-development projects should consider the distances at which impacts occur in the vicinity of the forest ecosystem, and these considerations should include the impacts on forest vegetation and bird species. Impacts can be mitigated by considering the distances at which these influences occur. In particular, this paper presents an integrated environmental impact assessment system to be applied in the SEIA process. The integrated assessment system permits the assessment of the cumulative impacts of land development on multiple scales.     

Effects of Forest Management Practices on Mid-Atlantic Streams

Agricultural and urban land use activities have affected stream ecosystems throughout the mid-Atlantic region. However, over 60% of the mid-Atlantic region is forested. A study was conducted to investigate the effects of management practices on forested stream ecosystems throughout the mid-Atlantic region. The study consisted of two phases: Phase 1 was a literature synthesis of information available on the effects of forest management practices on stream hydrology, erosion and sedimentation, riparian habitat alteration, chemical addition, and change in biotic diversity in the mid-Atlantic region. In Phase 2, data from mid-Atlantic streams were analyzed to assess the effects of forest land use on stream quality at the regional scale. Typically, it is the larger order streams in which monitoring and assessment occurs—3^rd order or higher streams. The impacts of forest management practices, particularly hydrologic modifications and riparian buffer zone alteration, occur predominantly in first and second order streams with cumulative impacts translating to higher order streams. Based on the literature review and mid-Atlantic Highland streams analysis, there are short-term (e.g., 2 to 5 years) effects of forest management practices on stream quality at local scales. However, signatures of cumulative effects from forest management practices are not apparent at regional scales in the Highlands. In general, forested land use is associated with good stream quality in the region compared with other land use practices.     

Trends in land use and land cover change in the protected and communal areas of the Zambezi Region,Namibia

Land management decisions have extensively modified land use and land cover in the Zambezi Region. These decisions are influenced by land tenure classifications, legislation, and livelihoods. Land use and land cover change is an important indicator for quantifying the effectiveness of different land management strategies. However, there has been no evidence on whether protected or communal land tenure is more affected by land use and land cover changes in southern Africa and particularly Namibia. Our study attempted to fill this gap by analyzing the relationship between land use and land cover change and land tenure regimes stratified according to protected and communal area in the Zambezi Region. Multi-temporal Landsat TM and ETM+ imagery were used to determine the temporal dynamics of land use and land cover change from 1984 to 2010. The landscape showed distinctive modifications over the study period; broad trends include the increase in forest land after 1991. However, changes were not uniform across the study areas. Two landscape development stages were deduced: (1) 1984–1991 represented high deforestation and gradual increase in shrub land; (2) 1991–2000 and 2000–2010 represented lower deforestation and slower agropastoral expansion. The results further show clear patterns of the dynamics, magnitude, and direction of land use and land cover change by tenure regime. The study concluded that land tenure has a direct impact on land use and land cover, since it may restrict some activities carried out on the land in the Zambezi Region.