Provincial Inventory Research Articles

Impacts of spruce budworm defoliation on the habitat of woodland caribou, moose, and their main predators.

Forest logging has contributed to the decline of several woodland caribou populations by causing the fragmentation of mature coniferous stands. Such habitat alterations could be worsened by spruce budworm (SBW) outbreaks. Using 6201 vegetation plots from provincial inventories conducted after the last SBW outbreak (1968–1992) in boreal forests of Québec (Canada), we investigated the influence of SBW‐caused tree defoliation and mortality on understory vegetation layers relevant to woodland caribou and its main predators. We found a positive association between severe outbreaks and the cover of most groups of understory plant species, especially in stands that were dominated by balsam fir before the outbreak, where a high canopy openness particularly benefited relatively fast‐growing deciduous plants. Such increases in early successional vegetation could provide high‐quality forage for moose, which is likely to promote higher wolf densities and increase predation pressure on caribou. SBW outbreaks may thus negatively affect woodland caribou by increasing predation risk, the main factor limiting caribou populations in managed forests. For the near future, we recommend updating the criteria used to define critical caribou habitat to consider the potential impacts of spruce budworm defoliation.

Province-level fossil fuel CO2 emission estimates for China based on seven inventories

China pledges to reach a peak in CO2 emissions by 2030 and to make its best efforts to reach this peak earlier. Previous studies have paid much attention to the total amount of China’s CO2 emissions, but usually only one dataset is used in each evaluation. The pledged national reduction target is administratively divided into provincial targets. Accurate interpretation of province-level carbon emissions is essential for making policies and achieving the reduction target. However, the spatiotemporal pattern of provincial emissions and the associated uncertainty are still poorly understood. Thus, an assessment of province-level CO2 emissions considering local statistical data and emission factors is urgently needed. Here, we collected and analyzed 7 published emission datasets to comprehensively evaluate the spatiotemporal distribution of provincial CO2 emissions. We found that the provincial emissions ranged from 20 to 649 Mt CO2 and that the standard deviations (SDs) ranged from 8 to 159 Mt. Furthermore, the emissions estimated from provincial-data-based inventories were more consistent than those from the spatial disaggregation of national energy statistics, with mean SDs of 26 and 65 Mt CO2 in 2012, respectively. Temporally, emissions in most provinces increased from 2000 to approximately 2012 and leveled off afterwards. The interannual variation in provincial CO2 emissions was captured by provincial-data-based inventories but generally missed by national-data-based inventories. When compared with referenced inventories, the discrepancy for provincial estimates could reach −57%–162% for national-data-based inventories but were less than 45% for provincial-data-based inventories. Using comprehensive data sets, the range presented here incorporated more factors and showed potential systematic biases. Our results indicate that it is more suitable to use provincial inventories when making policies for subnational CO2 reductions or when performing atmospheric CO2 simulations. To reduce uncertainties in provincial emission estimates, we suggest the use of local optimized coal emission factors and validations of inventories by direct measurement data and remote sensing results.

Autoregressive Modeling of Forest Dynamics

In this work, we employ autoregressive models developed in financial engineering for modeling of forest dynamics. Autoregressive models have some theoretical advantage over currently employed forest modeling approaches such as Markov chains and individual-based models, as autoregressive models are both analytically tractable and operate with continuous state space. We performed a time series statistical analysis of forest biomass and basal areas recorded in Quebec provincial forest inventories from 1970 to 2007. The geometric random walk model adequately describes the yearly average dynamics. For individual patches, we fit an autoregressive process (AR) of order 1 capable to model negative feedback (mean-reversion). Overall, the best fit also turned out to be geometric random walk; however, the normality tests for residuals failed. In contrast, yearly means were adequately described by normal fluctuations, with annual growth on average of 2.3%, but with a standard deviation of order of 40%. We used a Bayesian analysis to account for the uneven number of observations per year. This work demonstrates that autoregressive models represent a valuable tool for the modeling of forest dynamics. In particular, they quantify the stochastic effects of environmental disturbances and develop predictive empirical models on short and intermediate temporal scales.

Occurrence and leaching of silver in municipal sewage sludge in China.

Sewage treatment plants effectively remove silver (Ag) from sewage. Sewage sludge can therefore be important Ag sinks, polluting the environment with this element. In this work, we report a nation-wide survey on the Ag content of sewage sludge in China (0.23-19.02 mg kg-1, average 2.72 mg kg-1). Furthermore, we identify that sludge disposal represents an important Ag pollution source (84.48 tons in 2016) for the environment by estimating the national and provincial inventories of sludge-borne Ag in China. Also the positive correlations between the per capita gross domestic product (GDP)/provincial GDP and the content/mass loadings of Ag highlighted the impact of human activities on Ag pollution. In different samples, strong complexation of thiosulfate contributed to the highest leaching concentration (95.00-438.15 μg kg-1) and ratio (1.9-8.8%) of Ag, emphasizing the necessity of a long-term risk assessment for landfill and land application of sludge.

Assessment of a high-resolution NOX emission inventory using satellite observations: A case study of southern Jiangsu, China

To evaluate the bottom-up NOX emission inventories with different data sources and spatial scales, an updated product of tropospheric NO2 vertical column densities (VCDs) from Ozone Monitoring Instrument (OMI), POMINO, was applied in chemistry transport modeling (CTM) and Gaussian function model for southern Jiangsu, a typical developed and polluted region in eastern China. Compared to the national emission inventory (MEIC), better correlation was found between spatial distributions of the high-resolution provincial inventory (JS) and POMINO VCDs. When applied in CTM, the simulated VCDs using JS were closer to POMINO data than those using MEIC, indicating the advantage of the provincial inventory that incorporated detailed information of individual plants. The simulated VCDs, however, were generally larger than observed ones, particularly for regions with high NO2 levels, partly because the improved NOX control measures for power sector were not fully considered in both national and provincial inventories. The “top-down” NOX emissions were estimated for four cities/city combinations in southern Jiangsu, using a Gaussian function model based on POMINO NO2 VCDs. The results were found to be most consistent with the estimates in JS among bottom-up inventories with different data sources. To further harmonize emissions and satellite observations at relatively small spatial scale, the on-line emission measurement data for individual plants are recommended for emission inventory development, and the products of satellite observation data with finer horizontal resolution are encouraged.

Emissions and low-carbon development in Guangdong-Hong Kong-Macao Greater Bay Area cities and their surroundings

Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

Improved provincial emission inventory and speciation profiles of anthropogenic non-methane volatile organic compounds: a case study for Jiangsu, China

Abstract. Non-methane volatile organic compounds (NMVOCs) are the key precursors of ozone (O3) and secondary organic aerosol (SOA) formation. Accurate estimation of their emissions plays a crucial role in air quality simulation and policy making. We developed a high-resolution anthropogenic NMVOC emission inventory for Jiangsu in eastern China from 2005 to 2014, based on detailed information of individual local sources and field measurements of source profiles of the chemical industry. A total of 56 NMVOCs samples were collected in nine chemical plants and were then analyzed with a gas chromatography – mass spectrometry system (GC-MS). Source profiles of stack emissions from synthetic rubber, acetate fiber, polyether, vinyl acetate and ethylene production, and those of fugitive emissions from ethylene, butanol and octanol, propylene epoxide, polyethylene and glycol production were obtained. Various manufacturing technologies and raw materials led to discrepancies in source profiles between our domestic field tests and foreign results for synthetic rubber and ethylene production. The provincial NMVOC emissions were calculated to increase from 1774 Gg in 2005 to 2507 Gg in 2014, and relatively large emission densities were found in cities along the Yangtze River with developed economies and industries. The estimates were larger than those from most other available inventories, due mainly to the complete inclusion of emission sources and to the elevated activity levels from plant-by-plant investigation in this work. Industrial processes and solvent use were the largest contributing sectors, and their emissions were estimated to increase, respectively, from 461 to 958 and from 38 to 966 Gg. Alkanes, aromatics and oxygenated VOCs (OVOCs) were the most important species, accounting for 25.9–29.9, 20.8–23.2 and 18.2–21.0 % to annual total emissions, respectively. Quantified with a Monte Carlo simulation, the uncertainties of annual NMVOC emissions vary slightly through the years, and the result for 2014 was −41 to +93 %, expressed as 95 % confidence intervals (CI). Reduced uncertainty was achieved compared to previous national and regional inventories, attributed partly to the detailed classification of emission sources and to the use of information at plant level in this work. Discrepancies in emission estimation were explored for the chemical and refinery sectors with various data sources and methods. Compared with the Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of emissions in this work were more influenced by the locations of large point sources, and smaller emissions were found in urban area for developed cities in southern Jiangsu. In addition, discrepancies were found between this work and MEIC in the speciation of NMVOC emissions under the atmospheric chemistry mechanisms CB05 and SAPRC99. The difference in species OLE1 resulted mainly from the updated source profile of building paint use and the differences in other species from the varied sector contributions to emissions in the two inventories. The Community Multi-scale Air Quality (CMAQ) model simulation was applied to evaluate the two inventories, and better performance (indicated by daily 1 h maximum O3 concentrations in Nanjing) were found for January, April and October 2012 when the provincial inventory was used.

Object-Based Classification of Wetlands in Newfoundland and Labrador Using Multi-Temporal PolSAR Data

ABSTRACTDespite the fact that vast portions of Newfoundland and Labrador (NL) are covered by wetlands, currently there is no provincial inventory of wetlands in the province. In this study, we analyzed multi-temporal synthetic aperture radar (SAR) data for wetland classification at 4 pilot sites across NL. Object-based image analysis (OBIA) using a segmentation method based on optical data (RapidEye image in this study), and well-adjusted to SAR images, was first compared to pixel-based classification. Next, multi-date object-based wetland maps using the Random Forest classifier were compared to single-date classification. Finally, ratio and textural features were evaluated for wetland classification. The OBIA method demonstrated superior results, and the multi-date classification performed better than single-date classification with accuracies ranging from 75% to 95%. The multi-date results showed that the images acquired in August are the most appropriate for classifying wetlands, while the October images are of less value. Also, covariance matrix is a valuable feature set for wetland mapping. Moreover, ratio and textural features slightly increase the overall accuracy when the initial overall accuracy is relatively low. It can be concluded that multi-date SAR classification, with the proposed segmentation method, shows great potential for mapping wetlands and can be applied throughout the province.

Methodology and applications of city level CO2 emission accounts in China

China is the world's largest energy consumer and CO2 emitter. Cities contribute 85% of the total CO2 emissions in China and thus are considered as the key areas for implementing policies designed for climate change adaption and CO2 emission mitigation. However, the emission inventory construction of Chinese cities has not been well researched, mainly owing to the lack of systematic statistics and poor data quality. Focusing on this research gap, we developed a set of methods for constructing CO2 emissions inventories for Chinese cities based on energy balance table. The newly constructed emission inventory is compiled in terms of the definition provided by the IPCC territorial emission accounting approach and covers 47 socioeconomic sectors, 17 fossil fuels and 9 primary industry products, which is corresponding with the national and provincial inventory. In the study, we applied the methods to compile CO2 emissions inventories for 24 common Chinese cities and examined uncertainties of the inventories. Understanding the emissions sources in Chinese cities is the basis for many climate policy and goal research in the future.

Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu Province, China

Abstract. Improved emission inventories combining detailed source information are crucial for better understanding of the atmospheric chemistry and effectively making emission control policies using air quality simulation, particularly at regional or local scales. With the downscaled inventories directly applied, chemical transport models might not be able to reproduce the authentic evolution of atmospheric pollution processes at small spatial scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China, including SO2, NOx, CO, NH3, volatile organic compounds (VOCs), total suspended particulates (TSP), PM10, PM2.5, black carbon (BC), organic carbon (OC), and CO2. The key parameters relevant to emission estimation for over 6000 industrial sources were investigated, compiled, and revised at plant level based on various data sources and on-site surveys. As a result, the emission fractions of point sources were significantly elevated for most species. The improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Compared to the downscaled Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of NOx emissions in our provincial inventory was more consistent with summer tropospheric NO2 VCDs observed from OMI, particularly for the grids with moderate emission levels, implying the improved emission estimation for small and medium industrial plants by this work. Three inventories (national, regional, and provincial by this work) were applied in the Models-3 Community Multi-scale Air Quality (CMAQ) system for southern Jiangsu October 2012, to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO2, NO2, O3, and PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high-resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO2 concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than those observed, implying that the urban emissions were overestimated when economy or population densities were applied to downscale or allocate the emissions. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. Sensitivity analysis of PM2.5 and O3 formation was conducted using the improved provincial inventory through the brute force method. Iron and steel plants and cement plants were identified as important contributors to the PM2.5 concentrations in Nanjing. The O3 formation was VOC-limited in southern Jiangsu, and the concentrations were negatively correlated with NOx emissions in urban areas owing to the accumulated NOx from transportation. More evaluations are further suggested for the impacts of speciation and temporal and vertical distribution of emissions on air quality modeling at regional or local scales in China.

A high-resolution regional emission inventory of atmospheric mercury and its comparison with multi-scale inventories: a case study of Jiangsu, China

Abstract. A better understanding of the discrepancies in multi-scale inventories could give an insight into their approaches and limitations as well as provide indications for further improvements; international, national, and plant-by-plant data are primarily obtained to compile those inventories. In this study we develop a high-resolution inventory of Hg emissions at 0.05° × 0.05° for Jiangsu, China, using a bottom-up approach and then compare the results with available global/national inventories. With detailed information on individual sources and the updated emission factors from field measurements applied, the annual Hg emissions of anthropogenic origin in Jiangsu in 2010 are estimated at 39 105 kg, of which 51, 47, and 2 % were Hg0, Hg2+, and Hgp, respectively. This provincial inventory is thoroughly compared to three downscaled national inventories (NJU, THU, and BNU) and two global ones (AMAP/UNEP and EDGARv4.tox2). Attributed to varied methods and data sources, clear information gaps exist in multi-scale inventories, leading to differences in the emission levels, speciation, and spatial distributions of atmospheric Hg. The total emissions in the provincial inventory are 28, 7, 19, 22, and 70 % larger than NJU, THU, BNU, AMAP/UNEP, and EDGARv4.tox2, respectively. For major sectors, including power generation, cement, iron and steel, and other coal combustion, the Hg contents (HgC) in coals/raw materials, abatement rates of air pollution control devices (APCDs) and activity levels are identified as the crucial parameters responsible for the differences in estimated emissions between inventories. Regarding speciated emissions, a larger fraction of Hg2+ is found in the provincial inventory than national and global inventories, resulting mainly from the results by the most recent domestic studies in which enhanced Hg2+ were measured for cement and iron and steel plants. Inconsistent information on large power and industrial plants is the main source of differences in spatial distribution of emissions between the provincial and other inventories, particularly in southern and northwestern Jiangsu, where intensive coal combustion and industry are located. Quantified with Monte Carlo simulation, uncertainties in the provincial inventory are smaller than those of the NJU national inventory, resulting mainly from the more accurate activity data of individual plants and the reduced uncertainties in HgC in coals/raw materials.

Changes to dam safety management in British Columbia triggered by failure of a small earth dam

ABSTRACTThe Testalinden earth dam in southern British Columbia failed in June 2010 and created a huge debris flow. Homes were destroyed and property was damaged. The failure of this small dam resulted in a comprehensive review of over 1000 dams in the province, evaluation of dam safety management practices, changes to the Water Act and improvements in how data on dams are collected, archived and communicated. The provincial dam inventory was re-evaluated to ensure that appropriate consequence classification, and therefore attention, is assigned to dams. Increased scrutiny was placed on dam owners to ensure they complied with dam safety policies and to ensure they submitted annual inspection reports and formal dam safety reviews in a timely manner. Dam owners and professionals engaged in dam safety activities have received new guidelines and better education and training.

Ecosystem classification and inventory maps as surrogates for ground beetle assemblages in boreal forest

AIMS: We compare performance of ecosystem classification maps and provincial forest inventory data derived from air photography in reflecting ground beetle (Coleoptera: Carabidae) biodiversity patterns that are related to the forest canopy mosaic. Our biodiversity surrogacy model based on remotely sensed tree canopy cover is validated against field-collected ground data. METHODS: We used a systematic sampling grid of 198 sites, covering 84 km2 of boreal mixedwood forest in northwestern Alberta, Canada. For every site, we determined tree basal area, characterized the ground beetle assemblage and obtained corresponding provincial forest inventory and ecosystem classification information. We used variation partitioning, ordination and misclassification matrices to compare beetle biodiversity patterns explained by alternative databases and to determine model biases originating from air photo-interpretation. IMPORTANT FINDINGS: Ecosystem classification data performed better than canopy cover derived from forest inventory maps in describing ground beetle biodiversity patterns. The biodiversity surrogacy models based on provincial forest inventory maps and field survey generally detected similar patterns but inaccuracies in air photo-interpretation of relative canopy cover led to differences between the two models. Compared to field survey data, air photo-interpretation tended to confuse two Picea species and two Populus species present and homogenize stand mixtures. This generated divergence in models of ecological association used to predict the relationship between ground beetle assemblages and tree canopy cover. Combination of relative canopy cover from provincial inventory with other geo-referenced land variables to produce the ecosystem classification maps improved biodiversity predictive power. The association observed between uncommon surrogates and uncommon ground beetle species emphasizes the benefits of detecting these surrogates as a part of landscape management. In order to complement conservation efforts established in protected areas, accurate, high resolution, wide ranging and spatially explicit knowledge of landscapes under management is primordial in order to apply effective biodiversity conservation strategies at the stand level as required in the extensively harvested portion of the boreal forest. In development of these strategies, an in-depth understanding of vegetation is key.

Forest attribute estimation of northeastern Canadian forests using QuickBird imagery and a shadow fraction method

This study demonstrates a method to map forest stand polygons based on four forest attributes (volume, basal area, height, and crown closure) using shadow fraction values estimated from high spatial resolution QuickBird panchromatic images. The method was tested over three test sites in northeastern Canada that were largely dominated by black spruce ( Picea mariana (Mill.) BSP.). The method involved four sets of procedures: (i) estimating shadow fraction from the panchromatic band of QuickBird images, (ii) generating site-specific and global regression models linking shadow fraction with each of the four forest attributes, (iii) mapping the forest attributes as a grid layer (30 × 30 m) for each test site using the global regression models, and (iv) generating stand polygons from the raster layers. Each test site was covered by a QuickBird satellite image with 0.6 × 0.6 m of spatial resolution. Between 2002 and 2004, 108 ground sample plots were acquired to develop local regression models. Goodness of fit ( R 2) of the linear regression models between shadow fraction and stand attributes ranged from 0.55 to 0.79. Relative root mean square error and bias estimates were, respectively, 0.32 and 0.15 for volume; 0.29 and 0.14 for basal area; 0.32 and −0.04 for crown closure; and 0.17 and 0.05 for height. Stand volume maps were produced from both the shadow fraction method and conventional forest stand maps (derived from aerial photo-interpretation) for a test site. Volume patterns were similar, and total volume for the test site differed by only 5.6% between the two maps. Lastly, the raster images derived from the shadow fraction method were used to produce a stand map following guidelines similar to those used by provincial inventory. In all cases, our results suggest that the shadow fraction method is a reliable and convenient way to map forest stand polygons and related attributes of black spruce stands of northeastern forests of Canada.

A simple Bayesian Belief Network for estimating the proportion of old-forest stands in the Clay Belt of Ontario using the provincial forest inventory

The differences between boreal forest landscapes produced by natural disturbance regimes and landscapes produced by harvesting are important and increasingly well documented. To continue harvesting operations while maintaining biodiversity and other ecosystem services, government policies and certification processes are pushing for practices that preserve landscape features within their range of natural variability. One major shortcoming in the implementation of such a strategy is the lack of complete spatial or temporal information about these landscape features, such as the proportion of old stands, which are believed to act as a coarse filter for conservation if they remain representative enough of natural conditions. The objective of this study was to quantify the proportion of old stands in a very large landscape by combining fragmentary knowledge from two different sources, i.e., a provincial forest inventory and existing fire history reconstructions using a Bayesian Belief Network. This study was conducted over a 6.5 Mha landscape located within the Clay Belt of the province of Ontario, Canada, and suggests that more than 72.4% of this area is occupied by stands where no fire occurred during the last 150 years. The implications for management and potential for future research are discussed.

Ocupación y uso del territorio en el sector centromeridional de la cuenca del Duero entre la Antigüedad y la alta Edad Media (siglos I-XI d.C.)

The authors propose an overview of the dynamics of settlement and land use in the region between the Central System and the territory south of the Duero River. The time span is the period between the Roman establishment and the Early Middle Ages. In order to study the settlement patterns, data from a field survey contained in the provincial inventories have been used. In addition, information from recent excavations in rural and urban sites has also been taken into account. Based on this data, a quantitative evaluation of land use in the Ambles Valley (Avila) has been attempted. To do so, Geographical Information Systems have been applied in order to measure land exploitation. As a complement, palaeopalynological data both from peat bogs and from samples from archaeological sites have been added. The paper focuses on the agropastoral transformations that took place from the Flavian colonization up to the Early Middle Ages. The main aspects discussed following a diachronic point of view are: the spread of the rural habitat, the increasing agrarian intensification and the growing specialization of production.

The distribution and morphometry of lakes and reservoirs in British Columbia: a provincial inventory

An inventory of provincial lakes and reservoirs has been developed to characterise and assess the distribution and morphometry of standing water bodies in British Columbia. In the province, there are over 241,500 lakes and reservoirs greater than 1,000 m 2 in size. These water bodies cover 2.37 percent of the province area and contain an estimated 521 km 3 of water (312 km 3 in natural lakes and 209 km 3 in reservoirs). A hypsometric relation suitable for order‐of‐magnitude estimates of lake volume from lake area is presented. Based on the distribution and morphometric attributes of lakes, several distinctive limnologic regions were identified, including the northeastern Alberta Plateau (highest proportion of circular lakes), the southwestern Alberta Plateau (lowest lake density/coverage and highest proportion of irregularly shaped lakes) and the Milbanke Strandflat (highest density of lakes). Observed regional and scale‐related patterns in lake distribution/morphometry appear to be largely related to geomorphic controls, particularly tectonic and glacial history. Large‐scale hydrologic implications of these standing water bodies and potential ecosystem/water resource management applications of the provincial inventory are also discussed.

Mapping aboveground tree biomass at the stand level from inventory information: test cases in Newfoundland and Quebec

A method of estimating and mapping aboveground tree biomass (AGTB) was developed using provincially available forest inventory databases. More specifically, AGTB conversion tables were devised to estimate biomass for stand attributes that are commonly mapped in provincial inventories over the Canadian landscape, i.e., species composition, projected crown density, and dominant tree height. AGTB is first estimated at the tree level using allometric relationships and measured stem distributions that are subsequently summed to estimate plot-level biomass. AGTB conversion tables are then computed from regression models that relate the plot-level biomass values to stand attributes. AGTB can then be mapped over the landscape by assigning the plot-level biomass values to the mapped stands. The method was developed using two provinces, Newfoundland and Labrador (N.L.) and Quebec, as test cases to assess the adaptation required between different management units. Models used to develop conversion tables from the test areas provided estimates of biomass with R2 ranging from 0.22 to 0.35 and from 0.31 to 0.64 and root mean square errors of 38 to 47 t/ha and 21 to 41 t/ha for N.L. and Quebec, respectively, based on an independent validation data set not used in the development of the models. Mapping errors and potential improvements to the models are discussed. To extend the methods developed in this study to a national map of forest AGTB will require significant adjustments to account for differences in regional inventory specifications. While the method for AGTB mapping can fulfil an important monitoring requirement in forestry, applying it to all provinces, as well as including alternate data sources for areas where inventories do not exist, such as satellite remotely sensed images, requires further research, some of which is currently in progress.

Status of woodland caribou in Saskatchewan

Recent research has shown that woodland caribou in Saskatchewan exist as relatively separate populations within a metapopulation. Preliminary analyses show that individuals within all populations are selecting peatland habitat types (i.e., fens and bogs) throughout the year. Despite an absence of hunting, populations south of the Precambrian shield appear to be declining slowly, while those on the southern margin of the shield may be declining more rapidly. The apparent population decline is likely due to high rates of predation, especially on neonates. To maintain viable caribou populations in the region, forestry operations must be managed to maintain adequate amounts of preferred habitat types and connections among populations. At a coarse scale, preferred habitat is that which acts as a refuge from predators. Additional information is required to categorize specific peatland types, as data in the existing provincial forest inventory are inadequate for both selection analysis and management purposes. Ongoing research into revisions to the forest inventory and analyses of bog and fen types selected by caribou are needed to focus future management strategies.

Operational forest inventory applications using Landsat TM data: The British Columbia experience

Abstract The Inventory Branch, B.C. Ministry of Forests has the mandate to annually update the provincial forest inventory database which consists of over 6,600, 1:20,000 scale mapsheets. Updating a database of this size using conventional photointerpretation and manual drafting is time consuming and costly. Digital satellite remote sensing techniques using Landsat TM data integrated with CAM/GIS technology have provided an efficient and cost effective method of streamlining the update procedure. In the future, updating may be further enhanced by incorporating digital change detection methods, classification, raster to vector conversion techniques and digital terrain correction. This paper describes how such technology is currently being used operationally in British Columbia.