Modeling and spatially distributing forest net primary production at the regional scale

Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that area's ability to sequester carbon in terrestrial ecosystems. As the ecosystems within a landscape change due to natural or anthropogenic processes, they may go from being a carbon sink to a carbon source or vice versa. Satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of terrestrial carbon. The coupling of Landsat Thematic Mapper (TM) data with a physiologically based forest productivity model (PnET-II) and historic climatic data provides an opportunity to enhance field plot-based forest inventory and monitoring methodologies. We use periodic forest inventory data from the U.S. Department of Agriculture (USDA) Forest Service's Forest Inventory and Analysis (FIA) Program to obtain estimates of forest area and type and to generate estimates of carbon storage for evergreen, deciduous, and mixed-forest classes. The area information is used in an accuracy assessment of remotely sensed forest cover at the regional scale. The map display of modeled net primary production (NPP) shows a range of forest carbon storage potentials and their spatial relationship to other landscape features across the southern United States. This methodology addresses the potential for measuring and projecting forest carbon sequestration in the terrestrial biosphere of the southern United States.     

Modeling and Spatially Distributing Forest Net Primary Production at the Regional Scale

Abstract

Forest, agricultural, rangeland, wetland, and urban landscapes have different rates of carbon sequestration and total carbon sequestration potential under alternative management options. Changes in the proportion and spatial distribution of land use could enhance or degrade that area’s ability to sequester carbon in terrestrial ecosystems. As the ecosystems within a landscape change due to natural or anthropogenic processes, they may go from being a carbon sink to a carbon source or vice versa. Satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of terrestrial carbon. The coupling of Landsat Thematic Mapper (TM) data with a physiologically based forest productivity model (PnET-II) and historic climatic data provides an opportunity to enhance field plot-based forest inventory and monitoring methodologies. We use periodic forest inventory data from the U.S. Department of Agriculture (USDA) Forest Service’s Forest Inventory and Analysis (FIA) Program to obtain estimates of forest area and type and to generate estimates of carbon storage for evergreen, deciduous, and mixed-forest classes. The area information is used in an accuracy assessment of remotely sensed forest cover at the regional scale. The map display of modeled net primary production (NPP) shows a range of forest carbon storage potentials and their spatial relationship to other landscape features across the southern United States. This methodology addresses the potential for measuring and projecting forest carbon sequestration in the terrestrial biosphere of the southern United States.     

Forest inventory and analysis: a national inventory and monitoring program

Forests provide significant commodity and noncommodity values to the citizens of the United States. An important and substantial role in ensuring the continued health, productivity, and sustainability of these resources is a reliable and credible inventory and monitoring program. The Forest Inventory and Analysis (FIA) program of the US Forest Service has been monitoring and reporting on status, condition, and trends in the nation's forests for over 70 years and the Forest Health Monitoring (FHM) program for the last 11 years. Recent legislation included in the 1998 Farm Bill, along with efforts to integrate inventory and monitoring networks to deliver Criteria and Indicators of Sustainable Forests, are redefining the role and operation of the recently integrated FIA and FHM programs. This paper provides a brief history and a look at new directions for the enhanced FIA Program.     

Regional estimation of current and future forest biomass

The 90,674 wildland fires that burned 2.9 million ha at an estimated suppression cost of $1.6 billion in the United States during the 2000 fire season demonstrated that forest fuel loading has become a hazard to life, property, and ecosystem health as a result of past fire exclusion policies and practices. The fire regime at any given location in these regions is a result of complex interactions between forest biomass, topography, ignitions, and weather. Forest structure and biomass are important aspects in determining current and future fire regimes. Efforts to quantify live and dead forest biomass at the local to regional scale has been hindered by the uncertainty surrounding the measurement and modeling of forest ecosystem processes and fluxes. The interaction of elevated CO2 with climate, soil nutrients, and other forest management factors that affect forest growth and fuel loading will play a major role in determining future forest stand growth and the distribution of species across the southern United States. The use of satellite image analysis has been tested for timely and accurate measurement of spatially explicit land use change and is well suited for use in inventory and monitoring of forest carbon. The incorporation of Landsat Thematic Mapper data coupled with a physiologically based productivity model (PnET), soil water holding capacity, and historic and projected climatic data provides an opportunity to enhance field plot based forest inventory and monitoring methodologies. We use periodic forest inventory data from the USDA Forest Service's Forest Inventory and Analysis (FIA) project to obtain estimates of forest area and type to generate estimates of carbon storage for evergreen, deciduous, and mixed forest classes for use in an assessment of remotely sensed forest cover at the regional scale for the southern United States. The displays of net primary productivity (NPP) generated from the PnET model show areas of high and low forest carbon storage potential and their spatial relationship to other landscape features for the southern United States. At the regional scale, predicted annual NPP in 1992 ranged from 836 to 2181 g/m2/year for evergreen forests and 769-2634 g/m2/year for deciduous forests with a regional mean for all forest land of 1448 g/m2/year. Prediction of annual NPP in 2050 ranged from 913 to 2076 g/m2/year for evergreen forest types to 1214-2376 g/m2/year for deciduous forest types with a regional mean for all forest land of 1659 g/m2/year. The changes in forest productivity from 1992 to 2050 are shown to display potential areas of increased or decreased forest biomass. This methodology addresses the need for spatially quantifying forest carbon in the terrestrial biosphere to assess forest productivity and wildland fire fuels.     

Forest reflectance modeling: theoretical aspects and applications

Forest reflectance models are able to contribute to the interpretation of satellite images over forested areas. A multipurpose forest reflectance model, its basic ideas, model input and output options are briefly described. The possibility to apply the model in forest remote sensing is demonstrated through the following simulation examples: the age dependence of forest reflectance, the seasonal course of forest reflectance, defoliation effects on forest reflectance, sensitivity of chlorophyll and water indices with respect to leaf chlorophyll and water content, respectively, and uncertainties in these indices introduced by the variation in stand parameters. When used together with the atmospheric radiative transfer and sensor calibration models, the forest reflectance model is applicable in satellite-imagery-aided forest ecology and health assessment, forest inventory and management.     

A simple empirical model to predict forest insecticide ground-level deposition from a compendium of field data

Deposit data from 205 aerial forest insecticide applications conducted in field trials by the Canadian Forest Service, Great Lakes Forestry Centre over a 15-year period are summarized. Deposit measurements were taken under "worst case" scenarios in the sense that direct applications were made over water bodies, and ground samplers were intentionally placed in open or cleared areas of forest. The median % deposit on shoreline collectors (32 separate applications) was 5.7%, on mid-stream collectors (44 separate applications) was 6.2%, and on forest floor collectors (129 separate applications) was 4.9%. Forest floor deposit was most closely associated with application rate and droplet size (r = 0.624, p < 0.001 and r = 0.662, p = 0.011, respectively) but these variables combined only explained 44% of the variation in deposit. Data from all three collector types were grouped by 10% deposit increments and combined to provide a data set from all deposition scenarios. A negative exponential model was fitted to the proportion of these combined sites regressed on % deposit in 10% increments and plotted as a deposit probability distribution curve (p < 0.001, r2 = 0.992). The probability distribution curve indicated that 5-10% deposit would be expected about 57-91% of the time, whereas 50% deposit or greater would be expected about 2% of the time or less. In a probabilistic risk assessment for aerially applied insecticides in a conifer-dominated forest environment, the probability distribution curve based on empirical data presented here can be used to refine the characterization of exposure scenarios from which effects estimates can be derived.     

Evidence-Based Knowledge Versus Negotiated Indicators for Assessment of Ecological Sustainability: The Swedish Forest Stewardship Council Standard as a Case Study

Assessing ecological sustainability involves monitoring of indicators and comparison of their states with performance targets that are deemed sustainable. First, a normative model was developed centered on evidence-based knowledge about (a) forest composition, structure, and function at multiple scales, and (b) performance targets derived by quantifying the habitat amount in naturally dynamic forests, and as required for presence of populations of specialized focal species. Second, we compared the Forest Stewardship Council (FSC) certification standards’ ecological indicators from 1998 and 2010 in Sweden to the normative model using a Specific, Measurable, Accurate, Realistic, and Timebound (SMART) indicator approach. Indicator variables and targets for riparian and aquatic ecosystems were clearly under-represented compared to terrestrial ones. FSC’s ecological indicators expanded over time from composition and structure towards function, and from finer to coarser spatial scales. However, SMART indicators were few. Moreover, they poorly reflected quantitative evidence-based knowledge, a consequence of the fact that forest certification mirrors the outcome of a complex social negotiation process.     

A simple empirical model to predict forest insecticide ground-level deposition from a compendium of field data

Deposit data from 205 aerial forest insecticide applications conducted in field trials by the Canadian Forest Service, Great Lakes Forestry Centre over a 15-year period are summarized. Deposit measurements were taken under “worst case” scenarios in the sense that direct applications were made over water bodies, and ground samplers were intentionally placed in open or cleared areas of forest. The median % deposit on shoreline collectors (32 separate applications) was 5.7%, on mid-stream collectors (44 separate applications) was 6.2%, and on forest floor collectors (129 separate applications) was 4.9%. Forest floor deposit was most closely associated with application rate and droplet size (r = 0.624, p < 0.001 and r = 0.662, p = 0.011, respectively) but these variables combined only explained 44% of the variation in deposit. Data from all three collector types were grouped by 10% deposit increments and combined to provide a data set from all deposition scenarios. A negative exponential model was fitted to the proportion of these combined sites regressed on % deposit in 10% increments and plotted as a deposit probability distribution curve (p < 0.001, r² = 0.992). The probability distribution curve indicated that 5–10% deposit would be expected about 57–91% of the time, whereas 50% deposit or greater would be expected about 2% of the time or less. In a probabilistic risk assessment for aerially applied insecticides in a conifer-dominated forest environment, the probability distribution curve based on empirical data presented here can be used to refine the characterization of exposure scenarios from which effects estimates can be derived.     

Projecting Climate Change Effects on Forest Net Primary Productivity in Subtropical Louisiana,USA

This study projected responses of forest net primary productivity (NPP) to three climate change scenarios at a resolution of 5 km × 5 km across the state of Louisiana, USA. In addition, we assessed uncertainties associated with the NPP projection at the grid and state levels. Climate data of the scenarios were derived from Community Climate System Model outputs. Changes in annual NPP between 2000 and 2050 were projected with the forest ecosystem model PnET-II. Results showed that forest productivity would increase under climate change scenarios A1B and A2, but with scenario B1, it would peak during 2011–2020 and then decline. The projected average NPP under B1 over the years from 2000 to 2050 was significantly different from those under A1B and A2. Forest NPP appeared to be primarily a function of temperature, not precipitation. Uncertainties of the NPP projection were due to large spatial resolution of the climate variables. Overall, this study suggested that in order to project effects of climate change on forest ecosystem at regional level, modeling uncertainties could be reduced by increasing the spatial resolution of the climate projections.     

Integrating Remote Sensing and Local Vegetation Information for a High-Resolution Biogenic Emissions Inventory— Application to an Urbanized,Semiarid Region

ABSTRACT

This paper presents a methodology for the development of a high-resolution (30-m), standardized biogenic volatile organic compound (BVOC) emissions inventory and a subsequent application of the methodology to Tucson, AZ. The region's heterogeneous vegetation cover cannot be modeled accurately with low-resolution (e.g., 1-km) land cover and vegetation information. Instead, local vegetation data are used in conjunction with multispectral satellite data to generate a detailed vegetation-based land-cover database of the region. A high-resolution emissions inventory is assembled by associating the vegetation data with appropriate emissions factors. The inventory reveals a substantial variation in BVOC emissions across the region, resulting from the region's diversity of both native and exotic vegetation.

The importance of BVOC emissions from forest lands, desert lands, and the urban forest changes according to regional, metropolitan, and urban scales. Within the entire Tucson region, the average isoprene, monoterpene, and     

Integrating remote sensing and local vegetation information for a high-resolution biogenic emissions inventory--application to an urbanized, semiarid region

This paper presents a methodology for the development of a high-resolution (30-m), standardized biogenic volatile organic compound (BVOC) emissions inventory and a subsequent application of the methodology to Tucson, AZ. The region's heterogeneous vegetation cover cannot be modeled accurately with low-resolution (e.g., 1-km) land cover and vegetation information. Instead, local vegetation data are used in conjunction with multispectral satellite data to generate a detailed vegetation-based land-cover database of the region. A high-resolution emissions inventory is assembled by associating the vegetation data with appropriate emissions factors. The inventory reveals a substantial variation in BVOC emissions across the region, resulting from the region's diversity of both native and exotic vegetation. The importance of BVOC emissions from forest lands, desert lands, and the urban forest changes according to regional, metropolitan, and urban scales. Within the entire Tucson region, the average isoprene, monoterpene, and OVOC fluxes observed were 454, 248, and 91 micrograms/m2/hr, respectively, with forest and desert lands emitting nearly all of the BVOCs. Within the metropolitan area, which does not include the forest lands, the average fluxes were 323, 181, and 70 micrograms/m2/hr, respectively. Within the urban area, the average fluxes were 801, 100, and 100 micrograms/m2/hr, respectively, with exotic trees such as eucalyptus, pine, and palm emitting most of the urban BVOCs. The methods presented in this paper can be modified to create detailed, standardized BVOC emissions inventories for other regions, especially those with spatially complex vegetation patterns.     

Using forest health monitoring data to integrate above and below ground carbon information

The national Forest Health Monitoring (FHM) program conducted a remeasurement study in 1999 to evaluate the usefulness and feasibility of collecting data needed for investigating carbon budgets in forests. This study indicated that FHM data are adequate for detecting a 20% change over 10 years (2% change per year) in percent total carbon and carbon content (MgC/ha) when sampling by horizon, with greater than 80% probability that a change in carbon content will be determined when a change has truly occurred (P < or = 0.33). The data were also useful in producing estimates of forest floor and soil carbon stocks by depth that were somewhat lower than literature values used for comparison. The scale at which the data were collected lends itself to producing standing stock estimates needed for carbon budget development and carbon cycle modeling. The availability of site-specific forest mensuration data enables the exploration of above ground and below ground linkages.     

Methodology for estimating soil carbon for the forest carbon budget model of the United States, 2001

The largest carbon (C) pool in United States forests is the soil C pool. We present methodology and soil C pool estimates used in the FORCARB model, which estimates and projects forest carbon budgets for the United States. The methodology balances knowledge, uncertainties, and ease of use. The estimates are calculated using the USDA Natural Resources Conservation Service STATSGO database, with soil dynamics following assumptions based on results of site-specific studies, and area estimates from the USDA Forest Service. Forest Inventory and Analysis data and national-level land cover data sets. Harvesting is assumed to have no effect on soil C. Land use change and forest type transitions affect soil C. We apply the methodology to the southeastern region of the United States as a case study.     

Forest cover of insular Southeast Asia mapped from recent satellite images of coarse spatial resolution

The study provides an example of mapping tropical forest cover from SPOT-Vegetation satellite images of coarse spatial resolution (1 km) for the subregion of insular Southeast Asia. A satellite image mosaic has been generated from satellite images acquired for the period 1998 to 2000. Forest cover has been mapped by unsupervised digital classification. The mapping result has then been compared to selected forest maps from the subregion, demonstrating the potential to provide basic information on forest area extent and distribution, but also on massive forest cover change in the subregional context. Forest area estimates derived from the map for the subregion have been found comparable to those compiled by FAO. The results indicate that many of the remaining tropical forests in Southeast Asia, rich in timber resources and biodiversity, may be lost in the near future if deforestation continues at present or previous rates.     

Inferred effects of cloud deposition on forest floor nutrient cycling and microbial properties along a short elevation gradient

Cloud water deposition often increases with elevation, and it is widely accepted that this cloud water increases acid loading to upland forest ecosystems. A study was undertaken in south-eastern Quebec to determine if a 250 m elevation gradient (i.e. 420-665 m), along a uniform sugar-maple stand on the slope of Mount Orford, corresponded to a pH gradient in the forest floor and to predictable changes in soil nutrient availability and microbial properties. Precipitation data from a nearby study, and a photographic survey, provided presumptive evidence that this elevation gradient corresponded to a strong gradient in cloud water deposition. Forest floor temperature did not differ significantly across elevations. Forest floor moisture content was significantly higher, whereas pH and exchangeable Ca and Mg were significantly lower, at the higher elevations. Average seasonal net nitrification rates, determined by long-term laboratory incubations, did not differ significantly across elevations, whereas average seasonal net ammonification rates were significantly higher at higher elevations. Basal respiration rates and microbial biomass did not differ significantly across elevations, but metabolic quotient was significantly higher at higher elevations indicating possible environmental stress on forest floor microbial communities due to cloud water deposition. Anaerobic N mineralisation rates were significantly higher at higher elevations suggesting that N-limited microbial communities frequently exposed to cloud cover can be important short-term sinks for atmospheric N, thereby contributing to increase the active-N fraction of forest floors. We conclude that, where no significant changes in vegetation or temperature occur, elevation gradients can still be used to understand the spatial variability of nutrient cycles and microbial properties.     

Nashville Sulfur Dioxide Emission Inventory and the Relationship of Emission to Measured Sulfur Dioxide

A detailed inventory of sulfur dioxide emissions was prepared as part of the Nashville Community Air Pollution Study conducted by the Public Health Service during 1958–59. The primary purpose of the inventory was to provide data for a study of the relationship between the emission of sulfur dioxide and measured ambient levels. The development of the inventory, data collection methods, and calculations are described. Ambient levels of sulfur dioxide were related to average emissions of sulfur dioxide in such a way (correlation coefficient = 0.81) that mean seasonal concentrations of atmospheric sulfur dioxide in square-mile areas could be predicted with fairly good confidence from a knowledge of sulfur dioxide emissions. For these long-period {average) predictions meteorological variables can be disregarded. On a square-mile basis, on the average, one ton of sulfur dioxide emitted per day produced a mean atmospheric sulfur dioxide concentration of 0.022 ppm, and 10 tons of sulfur dioxide per day produced a concentration of 0.067 ppm.     

Multifaceted Value Profiles of Forest Owner Categories in South Sweden: The River Helge å Catchment as a Case Study

Forest landscapes provide benefits from a wide range of goods, function and intangible values. But what are different forest owner categories’ profiles of economic use and non-use values? This study focuses on the complex forest ownership pattern of the River Helge å catchment including the Kristianstad Vattenrike Biosphere Reserve in southern Sweden. We made 89 telephone interviews with informants representing the four main forest owner categories. Our mapping included consumptive and non-consumptive direct use values, indirect use values, and non-use values such as natural and cultural heritage. While the value profiles of non-industrial forest land owners and municipalities included all value categories, the forest companies focused on wood production, and the Swedish Environmental Protection Agency on nature protection. We discuss the challenges of communicating different forest owners’ economic value profiles among stakeholders, the need for a broader suite of forest management systems, and fora for collaborative planning.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-012-0374-2) contains supplementary material, which is available to authorized users.     

Can’t See the (Bamboo) Forest for the Trees: Examining Bamboo’s Fit Within International Forestry Institutions

Over the centuries, governments and international agencies have developed a wide range of institutions to manage timber resources and conserve values provided by treed lands. Concerns regarding the sustainable supply of timber have provided opportunities for the development of substitute resources; however, bamboo and other non-timber forest resources have not been a part of the development of these institutions. Bamboo is a unique Non-Timber Forest Product, as it is often classified as forest or timber, and therefore must adhere to the same regulations as timber. Given the recent global expansion of bamboo, it is timely to examine the interplay between bamboo and the traditional institutions of forest governance. This paper aims to contribute to debates regarding cognitive institutional constraints on the development of substitute natural resources using bamboo as a case study, with specific focus on the applicability of Forest Stewardship Council certification, timber legality verification and Reducing Emissions from Deforestation and Forest Degradation to bamboos.     

High overlap between traditional ecological knowledge and forest conservation found in the Bolivian Amazon

It has been suggested that traditional ecological knowledge (TEK) may play a key role in forest conservation. However, empirical studies assessing to what extent TEK is associated with forest conservation compared with other variables are rare. Furthermore, to our knowledge, the spatial overlap of TEK and forest conservation has not been evaluated at fine scales. In this paper, we address both issues through a case study with Tsimane’ Amerindians in the Bolivian Amazon. We sampled 624 households across 59 villages to estimate TEK and used remote sensing data to assess forest conservation. We ran statistical and spatial analyses to evaluate whether TEK was associated and spatially overlapped with forest conservation at the village level. We find that Tsimane’ TEK is significantly and positively associated with forest conservation although acculturation variables bear stronger and negative associations with forest conservation. We also find a very significant spatial overlap between levels of Tsimane’ TEK and forest conservation. We discuss the potential reasons underpinning our results, which provide insights that may be useful for informing policies in the realms of development, conservation, and climate. We posit that the protection of indigenous cultural systems is vital and urgent to create more effective policies in such realms.