Towards an Integrated Approach to Natural Hazards Risk Assessment Using GIS: With Reference to Bushfires

This paper develops a GIS-based integrated approach to risk assessment in natural hazards, with reference to bushfires. The challenges for undertaking this approach have three components: data integration, risk assessment tasks, and risk decision-making. First, data integration in GIS is a fundamental step for subsequent risk assessment tasks and risk decision-making. A series of spatial data integration issues within GIS such as geographical scales and data models are addressed. Particularly, the integration of both physical environmental data and socioeconomic data is examined with an example linking remotely sensed data and areal census data in GIS. Second, specific risk assessment tasks, such as hazard behavior simulation and vulnerability assessment, should be undertaken in order to understand complex hazard risks and provide support for risk decision-making. For risk assessment tasks involving heterogeneous data sources, the selection of spatial analysis units is important. Third, risk decision-making concerns spatial preferences and/or patterns, and a multicriteria evaluation (MCE)-GIS typology for risk decision-making is presented that incorporates three perspectives: spatial data types, data models, and methods development. Both conventional MCE methods and artificial intelligence-based methods with GIS are identified to facilitate spatial risk decision-making in a rational and interpretable way. Finally, the paper concludes that the integrated approach can be used to assist risk management of natural hazards, in theory and in practice.     

A GIS model-based screening of potential contamination of soil and water by pyrethroids in Europe

The paper presents a geographic information system (GIS) model-based approach for analysis of potential contamination of soil and water by pyrethroids for the European continent. Pyrethroids are widely used pesticides and their chemical and toxicological characteristics suggest there may be concerns about human health and ecosystems, although so far there is no strong evidence indicating actual risk. However, little monitoring has been conducted and limited experimental information is available. We perform an assessment exercise that demonstrates how accessible information and GIS-based modeling allow to estimate the spatial distribution of chemical concentrations and fluxes at a screening level. The assessment highlights potential hot spots and the main environmental transport pathways, in a quick and simple way. By combining information on pesticide use, crop distribution and landscape and climate parameters we identify potential problem areas to help focusing monitoring campaigns. The approach presented here is simple and fast, and can be applied to virtually all pesticide classes used over a large domain, and is therefore suitable for the screening of large quantities of chemicals, of which the majority has not undergone any systematic environmental monitoring program. The method has been tested through benchmarking with other well-established models. However, further research is needed to evaluate it against experimental observations.     

A GIS-based approach for assessing the regional conservation status of genetic diversity: an example from the southern Appalachians

Conserving genetic diversity requires an assessment of the distribution of genetic variants in relation to patterns of land use and environmental variation at a regional scale. This assessment requires a novel approach to integrating and analyzing the genetic and environmental data across spatial scales. To explore the integration of genetic data with other geospatial data sets, we developed a GIS-based approach for examining patterns of genetic diversity for several species of salamanders in southern Appalachians. The genetic data, from allozyme surveys in the genetics literature, were integrated into a GIS database along with related attributes including population identifications and spatial locations. Using existing geospatial data, we classified sample locations as being either protected from anthropogenic disturbance (e.g., National Parks, Wilderness Areas) or as unprotected (e.g., private lands, multiple-use lands in National Forests). We used multidimensional scaling of allelic frequencies and contributions of populations to interpopulation differences in allelic richness to determine which populations had genetic characteristics most different from other populations in the sample. Measures of genetic differentiation were integrated into the GIS database to facilitate spatial analysis and visualization of the indices in relation to land use. This approach was useful for both identification of populations with components of genetic variation that were not well represented at protected sites and for identifying areas of species distributions where more genetic sampling would be necessary to make informed management decisions. Our approach could be readily adapted for use by managers and geneticists working with other species and types of genetic markers.     

Effects of tree size and spatial distribution on growth of ponderosa pine forests under alternative management scenarios

Forest ecosystems may be actively managed toward heterogeneous stand structures to provide both economic (e.g., wood production and carbon credits) and environmental benefits (e.g., invasive pest resistance). In order to facilitate wider adoption of possibly more sustainable forest stand structures, defining growth expectations among alternative management scenarios is crucial. To estimate the effect of tree size and spatial distributions on growth for forest structures commonly considered in uneven-aged forest stand management, large (0.2 ha+) plots were established in 14 uneven-aged ponderosa pine stands in eastern Montana. All study trees were stem-mapped and measured for diameter and 10-year sapwood and basal area increment. A generalized growth model was developed to predict both total and merchantable 10-year basal area increment for nine hypothetical stand structures [three diameter distributions (reverse-J, irregular, flat) × three spatial distributions (clumpy, partial clumpy, uniform)]. Results indicate that the size and spatial distributions of individual trees have a considerable effect on overall stand growth. The greatest total stand growth was in stands with reverse “J” shaped tree size distributions, while the greatest merchantable stand growth was in stands with “flat” diameter distributions and uniform spatial distributions. Through better comprehension of generalized uneven-aged stand growth dynamics, forest managers may better assess the effects of alternative stand structures on stand growth while providing forest stand structures that may be more resilient in a changing climate.     

Predictors of Ips confusus Outbreaks During a Record Drought in Southwestern USA: Implications for Monitoring and Management

In many ecosystems the effects of disturbance can be cryptic and disturbance may vary in subtle spatiotemporal ways. For instance, we know that bark beetle outbreaks are more frequent in temperate forests during droughts; however, we have little idea about why they occur in some locations and not others. Understanding biotic and abiotic factors promoting bark beetle outbreaks can be critical to predicting and responding to pest outbreaks. Here we address the environmental factors which are associated with Ips confusus outbreaks during the 2002 widespread drought within the distribution range of pinyon pine woodlands in Arizona. We used univariate statistics to test if whether tree characteristics, other herbivores, stand properties, soil type, wind, and topography were associated with I. confusus outbreak, and logistic regression to create a predictive model for the outbreaks. We found that I. confusus attacks occur in low elevation stands on steeper slopes, where favorable winds for I. confusus dispersion occur. I. confusus select larger trees, in high density stands with understory shrubs that exhibit phenotypic traits characteristic of resistance to stem-boring moths. The model was highly accurate, and explained 95% of the variability in occurrence (98% of the absences and 95% of the presences). Accurate prediction of the impacts of disturbance allow us to anticipate, minimize or mitigate for and eventually counteract its effects, especially those affecting diversity and ecosystem function. Identification of outbreak risk areas can guide regional and national management towards the reduction of infestation risk and enhancing conservation of pinyon-juniper woodlands.     

Remote Assessment of Forest Health in Southern Arizona, USA: Evidence for Ozone-Induced Foliar Injury

This paper examines possible ozone-induced foliar injury to ponderosa pine areas in the Rincon Mountains of southern Arizona from 1972 to 1992. Spatiotemporal differences in a satellite-derived vegetation index (VI) are examined with respect to antecedent moisture conditions, temporal variations in ozone exposure levels, and measured foliar injury values from 1985. Seasonal ozone exposure levels (SUM60 and W126) increased from 1982 to 1998 and were significantly correlated (r = 0.49 and 0.53, α= 0.05) with annual population totals in the Tucson area. Extensive masking of satellite images from 1972, 1986, and 1992 resulted in two optimal change detection areas, with one site, TVWMica, exposed mostly to the Tucson air pollution plume, while the other site, EMica, was more protected from Tucson-derived pollution. An overall increase in VI from 1972 to 1992 at both sites appears to have been caused by an increase in moisture availability. Larger foliar injury values in 1985 were associated with a smaller increase in VI (i.e., a smaller increase in green leaf biomass) from 1972 to 1986. From 1972 to 1986 and from 1986 to 1992, VI values at TV/WMica increased at a slower rate compared to those at EMica. The reduced increase in “green-up” may have been caused partially by ozone-induced foliar injury and resulting decreases in green leaf biomass. However, these spatial differences in VI values may have also been caused by a number of other factors. Results nevertheless reveal the strong possibility of distinct, topographically based, spatial variations in ozone-induced foliar injury within the Rincons.     

A Hierarchical Approach to Forest Landscape Pattern Characterization

Landscape spatial patterns have increasingly been considered to be essential for environmental planning and resources management. In this study, we proposed a hierarchical approach for landscape classification and evaluation by characterizing landscape spatial patterns across different hierarchical levels. The case study site is the Red Hills region of northern Florida and southwestern Georgia, well known for its biodiversity, historic resources, and scenic beauty. We used one Landsat Enhanced Thematic Mapper image to extract land-use/-cover information. Then, we employed principal-component analysis to help identify key class-level landscape metrics for forests at different hierarchical levels, namely, open pine, upland pine, and forest as a whole. We found that the key class-level landscape metrics varied across different hierarchical levels. Compared with forest as a whole, open pine forest is much more fragmented. The landscape metric, such as CONTIG_MN, which measures whether pine patches are contiguous or not, is more important to characterize the spatial pattern of pine forest than to forest as a whole. This suggests that different metric sets should be used to characterize landscape patterns at different hierarchical levels. We further used these key metrics, along with the total class area, to classify and evaluate subwatersheds through cluster analysis. This study demonstrates a promising approach that can be used to integrate spatial patterns and processes for hierarchical forest landscape planning and management.     

A GIS-Based Multicriteria Evaluation for Aiding Risk Management <Emphasis Type="Italic">Pinus pinaster</Emphasis> Ait. Forests: A Case Study in Corsican Island,Western Mediterranean Region

Forest management can benefit from decision support tools, including GIS-based multicriteria decision-aiding approach. In the Mediterranean region, Pinus pinaster forests play a very important role in biodiversity conservation and offer many socioeconomic benefits. However, the conservation of this species is affected by the increase in forest fires and the expansion of Matsucoccus feytaudi. This paper proposes a methodology based on commonly available data for assessing the values and risks of P. pinaster forests and to generating maps to aid in decisions pertaining to fire and phytosanitary risk management. The criteria for assessing the values (land cover type, legislative tools for biodiversity conservation, environmental tourist sites and access routes, and timber yield) and the risks (fire and phytosanitation) of P. pinaster forests were obtained directly or by considering specific indicators, and they were subsequently aggregated by means of GIS-based multicriteria analysis. This approach was tested on the island of Corsica (France), and maps to aid in decisions pertaining to fire risk and phytosanitary risk (M. feytaudi) were obtained for P. pinaster forest management. Study results are used by the technical offices of the local administration—Corsican Agricultural and Rural Development Agency (ODARC)—for planning the conservation of P. pinaster forests with regard to fire prevention and safety and phytosanitary risks. The decision maker took part in the evaluation criteria study (weight, normalization, and classification of the values). Most suitable locations are given to target the public intervention. The methodology presented in this paper could be applied to other species and in other Mediterranean regions.     

High-Biomass Forests of the Pacific Northwest: Who Manages Them and How Much is Protected?

To examine ownership and protection status of forests with high-biomass stores (>200 Mg/ha) in the Pacific Northwest (PNW) region of the United States, we used the latest versions of publicly available datasets. Overlay, aggregation, and GIS-based computation of forest area in broad biomass classes in the PNW showed that the National Forests contained the largest area of high-biomass forests (48.4 % of regional total), but the area of high-biomass forest on private lands was important as well (22.8 %). Between 2000 and 2008, the loss of high-biomass forests to fire on the National Forests was 7.6 % (236,000 ha), while the loss of high-biomass forest to logging on private lands (364,000 ha) exceeded the losses to fire across all ownerships. Many remaining high-biomass forest stands are vulnerable to future harvest as only 20 % are strictly protected from logging, while 26 % are not protected at all. The level of protection for high-biomass forests varies by state, for example, 31 % of all high-biomass federal forests in Washington are in high-protection status compared to only 9 % in Oregon. Across the conterminous US, high-biomass forest covers <3 % of all forest land and the PNW region holds 56.8 % of this area or 5.87 million ha. Forests with high-biomass stores are important to document and monitor as they are scarce, often threatened by harvest and development, and their disturbance including timber harvest results in net C losses to the atmosphere that can take a new generation of trees many decades or centuries to offset.     

Gaining forests but losing ground: A GIS evaluation in a Himalayan watershed

GIS overlay techniques were used to provide a quantitative historic documentation of deforestation and land-use dynamics in the Middle Mountains of Nepal between 1947 and 1990. Deforestation was most critical in the 1960s, but active afforestation programs in the 1980s have reversed the process. In spite of these trends, the degradation problem is more complex. The GIS evaluation showed that 86% of the recently afforested land is now under pine plantations located primarily at lower elevations and moderately steep slopes. In contrast, rainfed agricultural expansion is most pronounced on acidic soils and steeper, upper elevation sites, suggesting marginalization of agriculture. Agricultural expansion coupled with major losses of grazing land to pine forests are the key processes pointing towards major animal feed deficits. An alternative animal feed source is suggested through GIS using a topographically based microclimatic classification to generate a tree-planting map where the optimum ecological conditions for selective native fodder tree species are identified.     

Support of sustainable management of nitrogen contamination due to septic systems using numerical modeling methods

Nitrogen contamination is a serious concern to sustainable environmental management, and one important source of nitrogen contaminant is due to wastewater treatment using onsite sewage treatment and disposal systems (OSTDS, a.k.a., septic systems). This paper presents a study in which numerical modeling is used to support sustainable decision-making and management of nitrogen contamination by utilizing a recently developed GIS-based software, VZMOD, a Vadose Zone MODel for simulating nitrogen transformation and transport in vadose zone between drainfield of septic systems and water table. VZMOD is based on a physical model of unsaturated flow and nitrogen transformation and transport, and the model is solved numerically using the finite element methods. This is the major difference between VZMOD and other GIS-based software of nitrogen modeling. Using GIS techniques, VZMOD considers spatial variability of a number of hydrogeologic parameters such as hydraulic conductivity and porosity. A unique feature of VZMOD is that VZMOD addresses spatial variability of water table by using VZMOD together with ArcNLET, an ArcGIS-based software developed to simulate groundwater flow and nitrate load from septic systems to surface water bodies. VZMOD is designed to execute in different modes to be compatible with different levels of data availability in various management projects of nitrogen contamination. This paper presents an application of VZMOD at a neighborhood with hundreds of septic systems and heterogeneous hydraulic conductivity, porosity, and water table depth. The modeling results indicate that using septic systems at the considered neighborhood is unsustainable and more management means are necessary.     

A river water quality model integrated with a web-based geographic information system

Scientists often use mathematical models to assess river water quality. However, the application of the models in environmental management and risk assessment is quite limited because of the difficulty of preparing input data and interpreting model output. This paper presents a study that links ArcIMS, a Web-based Geographic Information System (GIS) software to ROUT, a national and regional scale river model which evolved from the US Environmental Protection Agency's Water Use Improvement and Impairment Model, to create a WWW-GIS-based river simulation model called GIS-ROUT. GIS-ROUT is used to predict chemical concentrations in perennially flowing rivers throughout the continental United States that receive discharges from more than 10,000 publicly owned wastewater treatment plants (WWTPs). The WWTP chemical loadings are calculated from per capita per day disposal of product ingredients and the population served by each plant. Each WWTP, containing data on treatment type and influent and effluent flows, is spatially associated with a specific receiving river segment. Based on user defined treatment-type removal rates for a particular chemical, an effluent concentration for each WWTP is calculated and used as input to the river model. Over 360,000 km of rivers are modeled, incorporating dilution and first order loss of the chemical in each river segment. The integration of spatial data, GIS, the WWW, and modeling in GIS-ROUT makes it possible to organize and analyze data spatially, and view results on interactive maps as well as tables and distribution charts. The integration allows scientists and managers in different locations to coordinate and share their estimations for environmental exposure and risk assessments.     

Spatial Patterns of Macrobenthic Communities in Shallow-Water Tidal Embayments and Their Association with Environmental Factors

This study examines the distribution, composition, and structure of benthic communities in nine shallow-water semienclosed embayments on Cape Cod, southeastern Massachusetts. The spatial patterns were used to associate benthic characteristics with local environmental factors. Field data from multiple years were collected to measure macrofaunal abundance, community composition, and environmental characteristics. Multivariate statistics were used to analyze the spatial variations of species composition and the abundance of benthic macrofauna. Canonical ordination, specifically redundancy analysis, was used to determine the relative importance of the environmental factors (nutrients and habitat factors) being studied. The analyses demonstrate that the benthic communities in the shallow tidal embayments are clearly clustered in association with the local environments. Species composition and community structure of the benthic macrofauna are significantly correlated with water column parameters, especially with phytoplankton biomass, total nitrogen, and dissolved oxygen.     

Combining remote sensing imagery and forest age inventory for biomass mapping

Aboveground biomass (AGB) of forests is an important component of the global carbon cycle. In this study, Landsat ETM(+) images and field forest inventory data were used to estimate AGB of forests in Liping County, Guizhou Province, China. Three different vegetation indices, including simple ratio (SR), reduced simple ratio (RSR), and normalized difference vegetation index (NDVI), were calculated from atmospherically corrected ETM(+) reflectance images. A leaf area index (LAI) map was produced from the RSR map using a regression model based on measured LAI and RSR. The LAI map was then used to develop an initial AGB map, from which forest stand age was deduced. Vegetation indices, LAI, and forest stand age were together used to develop AGB estimation models for different forest types through a stepwise regression analysis. Significant predictors of AGB changed with forest types. LAI and NDVI were significant predictors of AGB for Chinese fir (R(2)=0.93). The model using LAI and stand age as predictors explained 94% of the AGB variance for coniferous forests. Stand age captured 79% of the AGB variance for broadleaved forests (R(2)=0.792). AGB of mixed forests was predicted well by LAI and SR (R(2)=0.931). Without differentiating among forest types, the model with SR and LAI as predictors was able to explain 90% of AGB variances of all forests. In Liping County, AGB shows a strong gradient that increases from northeast to southwest. About 64% of the forests have AGB in the range from 90 to 180 t ha(-1).     

Variation in Vegetation Structure and Soil Properties, and the Relation Between Understory Plants and Environmental Variables Under Different Phyllostachys pubescens Forests in Southeastern China

Biodiversity maintenance and soil improvement are key sustainable forestry objectives. Research on the effects of bamboo forest management on plant diversity and soil properties are therefore necessary in bamboo-growing regions, such as southeastern China’s Shunchang County, that have not been studied from this perspective. We analyzed the effects of different Phyllostachys pubescens proportions in managed forests on vegetation structure and soil properties using pure Cunninghamia lanceolata forests as a contrast, and analyzed the relation between understory plants and environmental variables (i.e., topography, stand and soil characteristics) by canonical correspondence analysis (CCA). The forest with 80% P. pubescens and 20% hardwoods (such as Phoebe bournei, Jatropha curcas, Schima superba) maintained the highest plant diversity and best soil properties, with significantly higher plant diversity than the C. lanceolata forest, and better soil physicochemical and biological properties. The distribution of understory plants is highly related to environmental factors. Silvicultural disturbance strongly influenced the ability of different bamboo forests to maintain biodiversity and soil quality under extensive management, and the forest responses to management were consistent with the intermediate-disturbance hypothesis (i.e., diversity and soil properties were best at intermediate disturbance levels). Our results suggest that biodiversity maintenance and soil improvement are important management goals for sustainable bamboo management. To achieve those objectives, managers should balance the inputs and outputs of nutrients and protect understory plants by using appropriate fertilizer (e.g., organic fertilizer), adjusting stand structure, modifying utilization model and the harvest time, and controlling the intensity of culms and shoots harvests.     

COMPARATIVE EVALUATION OF LAND COVER DATA SOURCES FOR EROSION PREDICTION1

ABSTRACT: A fundamental problem in protecting surface drinking water supplies is the identification of sites highly susceptible to soil erosion and other forms of nonpoint source (NPS) pollution. The New York City Department of Environmental Protection is trying to identify erodible sites as part of a program aimed at avoiding costly filtration. New York City's 2,000 square mile watershed system is well suited for analysis with geographic information systems (GIS); an increasingly important tool to determine the spatial distribution of sensitive NPS pollution areas. This study used a GIS to compare three land cover sources for input into the Modified Universal Soil Loss Equation (MUSLE), a model estimating soil loss from rangeland and forests, for a tributary watershed within New York City's water supply system. Sources included both conventional data (aerial photography) and Landsat data (MSS and TM images). Although land cover classifications varied significantly across these sources, location-specific and aggregate watershed predictions of the MUSLE were very similar. We conclude that using Landsat TM imagery with a hybrid classification algorithm provides a rapid, objective means of developing large area land cover databases for use in the MUSLE, thus presenting an attractive alternative to photo interpretation.     

Comparison of Two Spatial Optimization Techniques: A Framework to Solve Multiobjective Land Use Distribution Problems

Two spatial optimization approaches, developed from the opposing perspectives of ecological economics and landscape planning and aimed at the definition of new distributions of farming systems and of land use elements, are compared and integrated into a general framework. The first approach, applied to a small river catchment in southwestern France, uses SWAT (Soil and Water Assessment Tool) and a weighted goal programming model in combination with a geographical information system (GIS) for the determination of optimal farming system patterns, based on selected objective functions to minimize deviations from the goals of reducing nitrogen and maintaining income. The second approach, demonstrated in a suburban landscape near Leipzig, Germany, defines a GIS-based predictive habitat model for the search of unfragmented regions suitable for hare populations (Lepus europaeus), followed by compromise optimization with the aim of planning a new habitat structure distribution for the hare. The multifunctional problem is solved by the integration of the three landscape functions (“production of cereals,” “resistance to soil erosion by water,” and “landscape water retention”). Through the comparison, we propose a framework for the definition of optimal land use patterns based on optimization techniques. The framework includes the main aspects to solve land use distribution problems with the aim of finding the optimal or best land use decisions. It integrates indicators, goals of spatial developments and stakeholders, including weighting, and model tools for the prediction of objective functions and risk assessments. Methodological limits of the uncertainty of data and model outcomes are stressed. The framework clarifies the use of optimization techniques in spatial planning.     

Integrating social preference in GIS-aided planning for forestry and conservation activities: a case study from rural SE Asia

Land-use planning using geographic information systems (GIS) commonly emphasizes biophysical spatial data; however planning can be improved by integrating spatial sets of socioeconomic data into the GIS. As an example, we compared a traditional GIS-aided forestry planning protocol that considered only biophysical suitability, with an integrated GIS-aided approach that incorporated both biophysical and socioeconomic suitability. The analyses were conducted for the planning of plantation investments in the Kyaukpadaung Township in the dry zone of central Myanmar. The traditional approach used three biophysical layers for suitability: land use, slope, and accessibility. In contrast, the integrated GIS approach included biophysical suitability data, perceptions and preferences of local villagers towards forestry (social suitability), and quantitative socioeconomic data. The results indicated that the integrated approach provided two principal benefits over the traditional method. First, the integrated method resulted in a more precise idea of suitable sites for plantation investment that could benefit more rural people and also lead to greater investment efficiency. Second, incorporating social preference into the GIS takes into account the crucial element of social capital (viz., social preference), which should lead to higher levels of community acceptance of plantation projects because those plantations would be established on socially suitable land. A second GIS exercise showed how conservation investment decisions could be informed using the integrated method. The results of this study support the idea that GIS-aided planning activities can be enhanced through the incorporation of social data into the analysis. When applicable, spatial data collection efforts for GIS-based planning exercises should incorporate spatial socioeconomic data.     

Silvicultural management in maintaining biodiversity and resistance of forests in Europe-temperate zone

In Europe temperate forests play a prominent role in timber production, nature protection, water conservation, erosion control and recreation. For centuries temperate forests in Europe have been affected by forest devastation and soil degradation. Applying great efforts to eliminate the severe wood shortage of those days, countermeasures were taken during the last 150 years by regenerating and tending highly productive forests. High growth rates and an increasing growing stock of these forests indicate that formerly stated goals have been successfully achieved. Coniferous species were often favoured because they were easy to establish and manage, and gave reason for high volume growth expectations. Today coniferous forests expand far beyond the limits of their natural ranges.These changes have been accompanied by a loss of biodiversity, a shift to nonsite adapted tree species and reduce the resistance against storms, snow, ice, droughts, insects and fungi. Some of these hazards were further intensified by the increasing average stand age, as well as in some areas by severe air pollution. Climatic fluctuations, especially changes in the frequency and intensity of extreme warm and dry climatic conditions and of heavy storms, had considerable impact on forest ecosystems.The changing demands of today require a widened scope of forest management. Society is asking for sustainable forestry emphasizing biodiversity and naturalistic forest management. It is of great economic and ecological relevance to know on which sites today's forests are most susceptible to climatic and other environmental changes and hazards. In those areas adjustments of management through a conversion the prevailing forests towards more site adapted mixed forests needs to be considered with priority. The high diversity in site conditions, ownership, economic and socio-cultural conditions require strategies adapted to the local and regional needs. Higher resistance of forests will increase economic and social benefits of forests and reduce the risks by maintaining sustainable forestry.     

Long-term depletion of calcium and other nutrients in eastern US forests

Both harvest removal and leaching losses can deplete nutrient capital in forests, but their combined long-term effects have not been assessed previously. We estimated changes in total soil and biomass N, Ca, K, Mg, and P over 120 years from published data for a spruce-fir site in Maine, two northern hardwood sites in New Hampshire, central hardwood sites in Connecticut and Tennessee, and a loblolly pine site in Tennessee. For N, atmospheric inputs counterbalance the outputs, and there is little long-term change on most sites. For K, Mg, and P, the total pool may decrease by 2%–10% in 120 years depending on site and harvest intensity. For Ca, net leaching loss is 4–16 kg/ha/yr in mature forests, and whole-tree harvest removes 200–1100 kg/ha. Such leaching loss and harvest removal could reduce total soil and biomass Ca by 20%–60% in only 120 years. We estimated unmeasured Ca inputs from rock breakdown, root-zone deepening, and dry deposition; these should not be expected to make up the Ca deficit. Acid precipitation may be the cause of current high leaching of Ca. Although Ca deficiency does not generally occur now in acid forest soils, it seems likely if anthropogenic leaching and intensive harvest removal continue.