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Background: National forest resource assessments and monitoring, commonly known as National Forest Inventories (NFI’s), constitute an important national information infrastructure in many countries. Methods: This study presents details about developments of the NFI in China, including sampling and plot design, and the uses of alternative data sources, and specifically � reviews the evolution of the national forest inventory in China through the 20th and 21st centuries, with some reference to Europe and the US; � highlights the emergence of some common international themes: consistency of measurement; more efficient sampling designs; implementation of improved technology; expansion of the variables monitored; scientific transparency; � presents an example of how China’s expanding NFI exemplifies these global trends. Results: Main results and important changes in China’s NFI are documented, both to support continued trend analysis and to provide data users with historical perspective. Conclusions: New technologies and data needs ensure that the Chinese NFI, like the national inventories in other countries, will continue to evolve. Within the context of historical change and current conditions, likely directions for this evolution are suggested. Keywords: China; Europe; USA; National forest inventories; Forest inventory and analysis Background Additional demands, including information on forest National forest resource assessment and monitoring, ecosystem health, are constantly emerging and new tech- commonly known as National Forest Inventory (NFI), nology is applied to meet these challenges. Internationally, has become an important part of the national informa- there is great diversity regarding definitions, sampling tion infrastructure in many countries. NFI assessments designs, reporting protocols and error estimation. Defini- provide an essential service, reconciling available re- tions and specifications may also change over time in one sources with national priorities related to timeliness, country. Substantial efforts have been made to meet the precision, and forest values of interest. As a noun, the new challenges. Forest health monitoring has become an word ‘inventory’ refers to a detailed list of articles ac- essential part of the inventories in many countries. Proper- cording to their properties with a commercial origin. ties include symptom description, causal agent, and degree As a verb, the word refers to the process of construct- of damage. Inventories have also added measurements ing that list. In a forest inventory, the tabulated informa- and assessments of biodiversity indicators, such as dead tion generally includes estimates for trees, tree properties and decaying wood and key habitats (Tomppo et al. and forests, often on the basis of areal units (Loetsch and 2010a). Collaborative projects to reach agreement on Haller 1973; Davis et al. 2001; Tomppo et al. 2010b) and is common definitions and to make inventory results regarded as reliable and adequate for its intended purposes. comparable highlighted differences in FAO definitions (UNFCCC LULUCF COST Action E43 2015; Tomppo et al. 2010a; Lanz et al. 2010). The involvement of * Correspondence: zengweisheng@sohu.com experts from both organizations made it possible to make Academy of Forest Inventory and Planning, State Forestry Administration, good progress towards common definitions, e.g., in land Beijing 100714, China class and carbon pool definitions. The adoption of new Full list of author information is available at the end of the article © 2015 Zeng et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Zeng et al. Forest Ecosystems (2015) 2:23 Page 2 of 16 definitions takes time and needs to be coordinated with a in many countries, although new inventories are being initi- new inventory round. A constant awareness and work of ated all the time. the harmonisation of the concepts as well as the use of The sampling design in the first inventories in the three common definitions is therefore necessary. Before the new Nordic countries had some similarities and also some dif- definitions are really in use, some kind of intermediate tools ferences. All inventories used lines or strips passing through may be needed (Ståhl et al. 2012). countries or country regions (Ilvessalo 1927; Tomppo et al. The loss of forest cover and forest degradation, especially 2011). The intervals between the lines varied by regions de- in many developing countries, has become a problem of pending on the variability of forests and land use. Norway international concern, particularly in view of global warm- and Sweden employed strip surveys: all trees over a certain ing and high CO emissions (IPCC 2015). Inventories of diameter threshold were callipered on the strips with a land use and land use change, as well as biomass stock width of 10 m (Tomter et al. 2010; Axelsson et al. 2010). changes assessments, are integral tools in addressing these The first NFI in Finland employed lines and visual assess- problems. The objective of this study is to describe the ment on the lines as well sample plots with exact mesure- development of the national forest inventory in China, and ments and also with visual assessments on the plots, the to present the most recent estimates of the basic forest latter one to calibrate the visual assessments (Ilvessalo resource parameters, as well as the changes over time. Ref- 1927; Tomppo et al. 2011). All three countries changed erence to forest resource inventories in some European the sampling designs later to utilize clusters of plots: countries, the FIA in the United States as well as the Norway and Sweden in their inventories in 1957–1964 National Forest Assessment and Monitoring by FAO pro- and 1952–1964, respectively, and Finland in the fifth vides an international perspective. inventory in 1964–1970. All inventories used only tempor- ary plots first and later either a combination of permanent and temporary plots or only permanent plots. The Development of NFI’s in Europe Norwegian and Swedish NFIs have used fixed radius The history of forest inventories dates back to the end of plots while the Finnish NFI angle count plots from the Middle Ages when intensive use of forest resources 1964 until 2013. Concentric plots with two radii were first led to wood shortages which, in turn, forced users adopted in the Finnish NFI in 2014. to assess timber resources, particularly near towns and Lawrence et al. (2010) gives a concise summary of the mines (Loetsch and Haller 1973; Tomppo et al. 2010b). sampling designs in European countries and also in coun- The first information collected for these purposes con- tries contributing the European Cost Action E43 and the cerned forest area and crude estimates of growing stock. country book written in the Action (Tomppo et al. 2011). The first inventories were often local with the aim of Most of the countries use either detached field sample plots assessing the available timber resources for specific pur- or clusters of plots. The forest area represented by one plot poses and were often conducted by the timber users, e.g. varied from 50 ha in Walloon region in Belgium and plan- commercial companies (Loetsch and Haller 1973; Davis tations in Iceland to 2400 ha in USA and 267,700 ha in et al. 2001). It soon became obvious that such inventor- Canada. There is quite a high diversity also in estimation ies could not easily be used to compile national level methods, particularly in estimating the increment and the forest information for purposes of formulating national drain of trees. The country reports in the book by Tomppo forest policy; thus, NFIs were initiated. et al. (2010a) presents more detailed descriptions of the Sample-based national forest inventories were initiated inventory methods by countries and the changes in the in the Nordic countries in the late 1910s and early 1920s, designs. but were not introduced in other European countries until New demands for forest inventories require timely after World War II: in the late 1940s in the German and accurate spatially explicit information. Forest inven- Democratic Republic; in 1958 in France; in the 1960s in tory groups have employed remotely sensed data for Austria; and in the 1980s in Switzerland. The early national several decades to meet the requirements in a cost- inventories in the Nordic countries included not only in- effective way, first using aerial photographs and later formation about areas, volume and increment of growing also satellite images (Spurr 1960). The increasing avail- stock and the amount of timber, but also age, size and spe- ability of aerial photography in digital form and the cies structure of forests, silvicultural status of forests, ac- ease of integration with auxiliary and other georefer- complished and needed cutting and silvicultural regimes enced data (GIS data) has greatly facilitated the use of (Ilvessalo 1927). The purpose was to provide information aerial photographs (McRoberts and Tomppo 2007). for forest authorities, timber users, and planners who devel- NFI country reports (Tomppo et al. 2010a) show that oped national forest policies. Some European countries aerial photography is still widely used by European have only recently introduced sample-based inventories. At NFIs. Koch (2013) gives reasons for continued use the global level, national forest inventories are still lacking of aerial photography, suchas longtraditions, high Zeng et al. Forest Ecosystems (2015) 2:23 Page 3 of 16 spatial resolution, greater probability of acquiring computers were making it possible to automate the calcula- cloud free data within a specific time window as well tion and tabling of volume estimates. This technology also as smaller areas and fragmented land use in European supported compilation of data across many inventories, countries compared to, e.g., larger non-European and in 1965, the USDA published what, according to Labau countries such as the USA, Canada, or countries in et al. (1992)), was the first truly nationwide forest survey South America. report (U.S. Department of Agriculture 1965). The use of satellite images, based on NFI field data In addition to trends toward more efficient and more dates back to 1980, first for forest mapping in stand- nationally consistent sampling and compilation, there level inventories in an experimental way and later oper- were social and legislative developments that motivated ationally at the national level in Finland and Sweden, the inventory to move beyond its roots in timber to and increasingly for spatialisation and modeling in the assessment of a wider variety of forest resources. Public 1990s and 2000s (Reese et al. 2003; Tomppo et al. appreciation of non-timber forest resources such as water, 2008a), as well as for regional inventories in the USA habitat, and recreation use grew during the 1970s. The (McRoberts et al. 2002; McRoberts 2012). Forest and Rangeland Renewable Resources Planning Act The current trend is to use multi-resolution and multi- of 1974 (RPA) broadened the mandate of the Forest Sur- sensor data in the inventories. Statistically sound methods, vey to include monitoring of a range of non-timber the development of which requires resources and time, are resources (U.S. Department of Agriculture 1992). Non- a priority. Detailed and comprehensive field data remains timber resource data from the inventory, such as habitat always as the core information in the national forest inven- area estimates, informed several forest management de- tories. Another trend in Europe and elsewhere is to estab- bates, e.g., informed debates about management of public lish statistically sound sampling based inventories. For the land (Bolsinger and Waddell 1993). reasons, see Section Evolution of FIA in the United States. Several developments during the 1990s led to The tight connections among the inventory teams world- standardization of inventory techniques and analysis wide maintain the harmonization of the definitions and the methods across the country. Beginning in 1996, all methods. plots were required to use a four-point design that in- corporated sampling proportional to plot area instead Evolution of FIA in the United States of tree size (Labau et al. 1992). Over the subsequent A national forest inventory was established by the US Con- decade, all states migrated to a nationally consistent gress, through the McSweeney-McNary Act of 1928, to as- sample framework, in which one permanent plot was sess issues related to national and regional timber supply. situated randomly within each 2430-ha (6000-acre) For several decades, periodic forest assessments were com- cell of a hexagonal tessellation of the country. This pleted on a state-by-state basis with little effort to create or sample design is considered to be a “spatially balanced enforce methodological standardization (U.S. Department simple random sample,” ensuring good geographic of Agriculture 1992). Labau et al. (1992) provide an account distribution of points while retaining a stochastic of the changing techniques used by this inventory, which element (Reams et al. 2005). The sample can be inten- was called the country’s “Forest Survey” for most of its sified in areas of interest by further tesselating existing history and has been called the Forest Inventory and Ana- hexagons into finer spatial units, each with a randomly lysis program (FIA) since approximately 1990 (earlier in located sample. A national “core” set of variables is some quarters). measured at each plot, and there is flexibility to add Prior to World War II, strip sample methods adapted measurements to address regionally important moni- from European designs, such as that used in Finland’sgen- toring questions. Until approximately 2010, additional eral survey (Ilvessalo 1927), were common across the coun- measurements, focused primarily on forest health, were collected on 1/16 of all plots to allow broad-scale try. Timber measurements were taken at fixed distances along transects that were typically established along regular, assessment of covered variables. Since then, a few of parallel lines. Following the war, advances in aerial photo- these variables have been moved to “core” status (mea- sured on all plots), and the rest have been retired. grammetry made more efficient stratified designs feasible, and strip sampling became less common (Labau et al. Plots are measured on a rotating basis in such a way that 1992). Starting around 1950, plots began to be sampled an approximately equal number of plots per state is mea- sured each year. The re-measurement cycle is 5–10 years, using “variable radius” plot cruising, based upon sampling proportional to tree size. These techniques were adapted in depending upon the state, and because 10–20 % of the grid the US from work in Austria by Bitterlich (Grosenbaugh is visited each year, the system is known as an “annual in- ventory 1958). From approximately 1960 through the mid-1980s, ”, as opposed to the earlier practice of periodically most inventory units used a 10-point cluster design within measuring all plots in the same year. As a result, instead of a 0.405 ha (1 acre) area. At the same time, programmable a single-date snapshot of conditions that becomes more Zeng et al. Forest Ecosystems (2015) 2:23 Page 4 of 16 dated until the next re-measurement, FIA estimates reflect Participatory: the involvement of a wide range of a rolling average picture of conditions over a 5- to 10-year stakeholders is encouraged, including government period. institutions, the private sector and NGOs. A principle of the inventory of FIA (and other NFI’s) is Harmonized: the terms and definitions are the focus on supporting a wide range of academic, indus- consistent among national institutions and refer to trial, governmental, and environmental clients. Reports on internationally agreed terms and definitions. The forest status and trends are published at both the state and harmonization allows comparison between countries national levels every 5 years. The national report (Smith and facilitates reporting to international reporting et al. 2009) is considered the authoritative description of processes. theUSforestrysector. Beyond thosereports, thepublicac- cesses the database itself approximately 100,000 times per According to Saket et al. (2010), the objective of the year (U.S. Department of Agriculture 2015). While the NFMA is “to contribute to the sustainable management of exact coordinates of the plots are not publically available to forests and trees outside forests by providing national protect the integrity of the sample (Healey et al. 2011), the decision makers and stakeholders with the means of local neighborhood of each plot is provided, as are all other acquiring accurate, relevant and cost-effective information elements of the plot measurements. This policy of availabil- on the state, uses, management of the forestry resources ity is thought to maximize the return on the national in- and land use changes. Such information is particularly vestment in the inventory. NFIs vary in their willingness to relevant for national and international dialogue on forestry share data beyond aggregate statistics. Outside of the free related policy issues and socio-economic development”. data access model pursued by the US and other countries, For more detailed objectives, see Saket et al. (2010). Asses- many NFIs share plot information only with select collabo- sing trees outside forests may develop into one of the rators, while others, including China in the past, carefully most important challenges for the immediate future. restrict data access. By 2013, NFMA had been completed in 10 countries Today, sample-based inventories are conducted in most and was in progress or anticipated in another 20 countries European and North American countries, although the (FAO 2013). FAO’s NFMA had employed a standard tradition in Eastern Europe has been to aggregate data from approach regarding sampling design and data collection stand-level inventories originally designed for management until 2009. The major sampling unit was a 1 × 1 km planning purposes. Stand level data are often assessed in square. Each unit contained a cluster of four plots with a different years and error estimation of such national size of 250 × 20 m, placed in perpendicular orientations. aggregates are not possible. Consequently, many Eastern Small trees were measured on nested subplots. The details European countries have recently revised their systems in of the design are described by Saket et al. (2010) and FAO favour of statistical, sample-based NFIs. The main reason is (2013). Due to the high workload for each cluster, the to conduct and maintain forest inventories within a statis- sampling intensity of the plots had been low. Estimates tical framework presenting timely information and making could have been computed on the national level only it possible to estimate uncertainties of forest resource pa- (Tomppo et al. 2014). However, when necessary, the sam- rameters. The Country reports in Tomppo et al. (2010a) pling intensity was increased based on local information give an overview of these changes by countries. needs. FAO’s NFMA has also launched specific studies to analyse and further develop the design based on local in- FAO NFMA formation needs (Tomppo and Katila 2008b; Tomppo Since the early 2000s, the Forestry Department of the et al. 2014). One aspect regarding inventories in Tropical Food and Agriculture Organization of the United countries isaccessibility,–thetimeneeded to reach afield Nations (FAO) has invested substantial resources in plot. Specific statistical methods are used to address this developing a programme of support to national forest problem involving, for example, stratification. Consider- monitoring and assessment, commonly known as ations related especially to forest inventories in the Tro- NFMA (Saket et al. 2010; FAO 2013; Tomppo et al. pics are discussed by McRoberts et al. (2013). 2014). The NFMA operates mainly in developing countries, particularly in Tropical forests, and tech- Methods nical, financial, and institutional co-operation and Brief history of NFI in China support is often needed. Saket et al. (2010) character- In China a national forest inventory was started relatively ized the NFMA approach as follows: early. After the People’s Republic of China was established in 1949, some national institutions for forest survey were Demand driven: countries request FAO support and set up at first in the northeastern region, and forest sur- define the assessment scopes as well as information veys were conducted in the Changbai Mountain and requirements. Xiaoxinganling forest areas. Subsequently, forest surveys Zeng et al. Forest Ecosystems (2015) 2:23 Page 5 of 16 were gradually extended all over the country. In 1962, the based on two-dimensional grids, although the grid spacing 2 2 former Agriculture and Forestry Ministry (AFM) of China varies considerably, from 1 ∗ 2km in Shanghai, 2 ∗ 2km organized the provincial forestry departments to compile in Beijing and Tianjin to 6 ∗ 8km in Yunnan and 8 ∗ forest resource data from various inventories, such as 8km in Inner Mongolia (Table 2). A few provinces, such reconnaissance surveys and forest management inventor- as Heilongjiang, Gansu, Qinghai and Xinjiang, divide the ies conducted during the period 1950–1962 and prepared population into two or three strata according to eco- summaries for the whole country. For the first time in geographic regions. Each stratum is considered as an inde- China forest resource data were gathered and reported for pendent sub-population in which systematic sampling is the country as a whole. This nation-wide assessment pre- applied. The inventory has a 5-year cycle, and about 1/5 sented a general overview of forest resources in China. provinces conduct inventories each year. The sampling However, this first compilation of inventories only covered population of the NFI in China is the total land area, in- about 300 million ha, involving the main forest regions cluding inland water. Plots are established on non-forest and State Forest Bureaus (Xiao 2005). land for purposes of estimating the area of lands converted In 1973, the former AFM conducted two forest inven- from non-forest to forest uses and vice versa. tory pilot studies, one in northern China and another in For the estimation of inventory statistics, the estimators southern China. Based on the findings, technical specifi- and error estimators were based on an asummption of sim- cations on main methods in forestry surveys were issued. ple random sampling in most provinces. In provinces with During 1973–1976, the first national forest inventory sub-populations, the estimators and error estimators of (NFI1), which is usually called the “4th 5-year Plan” In- stratified sampling were used where each sub-population ventory, was implemented. Based on county-level inven- was considered as a stratum. Simple random sampling was tories, the sampling designs and survey methods were assumed within each stratum. The national statistics were not standardized for the whole country. In 1977, the obtained from the summation of all provincial statistics former AFM conducted a pilot study involving a con- completed in a 5-year cycle, and the errors were estimated tinuous forest inventory (CFI) in Jiangxi province. Based using stratified sampling where each province was consid- on findings of that pilot study, standard specifications ered as a stratum (SFA 2011). on continuous forest inventory in China were issued for execution (AFM 1978). Plot configuration During the period 1977–1981, the NFI2 was imple- The shape, size and number of sample plots vary greatly mented, based on CFI principles with permanent plots among provinces. Square plots are used in more than 90 % and statistical sampling. The provinces, municipalities or of the provinces. Circular plots are used only in Tibet, while autonomous regions, represented the target population. rectangular plots are used in Inner Mongolia and in one The basic sampling frame of the CFI system had become sub-population of Heilongjiang. Point sampling or angle a good foundation for national forest inventory in China. count sampling was used in Guangxi before the 6th NFI, Subsequently, a total of six NFIs (NFI3 to NFI8) were but square plots have been used since 2005 (Cen et al. continuously conducted during the periods 1984–1988, 2007). In the past, several provinces such as Henan and 1989–1993, 1994–1998, 1999–2003, 2004–2008, and Hubei used to apply cluster sampling in plateau areas, 2009–2013 (Xiao 2005; Lei et al. 2009; Lin et al. 2013). where a cluster was composed of 4 or 5 plots (Xiao 2005). The key characteristics of the eight NFI’s in China are Plot sizes vary between 0.06 and 0.10 ha, and most of listed in Table 1. them are 0.0667 ha (1 Chinese mu). Among the 31 prov- Following economic and technical advancement, the inces in China (not including Taiwan, Hongkong and NFI system in China has been continually improved re- Macao, the same hereafter), the smallest sample numbers garding sampling design, survey methods, and technical are less than 3000 (Jiangxi 2608, Tianjin 2818, and Hainan standards. 2829). The greatest number of samples exceeds 10,000 (Inner Mongolia 17,951, Hebei 11,709, Anhui 11,678, Sampling design Henan 10,358, and Sichuan 10,007). For most of the prov- Sample grid inces, the number of sample plots are between 3000 and The history of NFI in China shows a progressive evolution 10,000. Several provinces had more sample plots before. towards statistical sampling techniques. All the provinces For example, the number of sample plots in Guizhou was are now using a systematic sampling design and permanent 11,017 before 1995, about twice the present number, while field plots. For the purpose of efficiency, sampling designs the sample in Jiangxi was 10,455 before 1996, about four should accommodate variation in forest attributes and land times the current number of sample plots (Xiao 2005). use structure, which suggests that the idea of a single design Since the 6th NFI, the sampling design of each province for the whole country may not be suitable. The most com- did not change. The number, shape and size of sample plots mon NFI features include systematic sampling components for 31 provinces are summarized in the Table 2. Zeng et al. Forest Ecosystems (2015) 2:23 Page 6 of 16 Table 1 Key characteristics of the eight NFIs in China NFIs Period Key characteristics NFI1 1973–1976 Based on county-level inventory, in most regions the inventory was not unified for the whole country NFI2 1977–1981 The continuous forest inventory (CFI) method was applied, establishing an effective foundation for national monitoring NFI3 1984–1988 The 1st re-inventory based on the CFI system, providing the changes on both quantity and quality of forest resources NFI4 1989–1993 4 national forest monitoring centers were set up, which were responsible for quality check, statistical compilation, and output reporting for different regions NFI5 1994–1998 The UNDP CPR 91/151 project was executed, and new technologies such as “3S” (RS-remote sensing, GPS-global positioning system, GIS-geographic information system) were started NFI6 1999–2003 Remote sensing was widely applied, and full-coverage inventory for the mainland of China was achieved NFI7 2004–2008 Several ecological variables were added, and forest ecological services in the whole country were evaluated NFI8 2009–2013 Modeling of tree biomass equations for main tree species in China has been actively pursued It should be pointed out that some provinces in west- (tolerance) for dbh measurement is 3 mm or 1.5 % ern China base their inventories partially on interpret- (for trees with a dbh exceeding 20 cm). ation plots using satellite imagery, such as LandSat, The second most important quantitative tree attibute SPOT and RapidEye. For remote or inaccessible regions, is height, which is measured using a traditional clinom- interpretation of image plots represents the only infor- eter or ultrasonic hypsometer. The height of small trees mation obtained. For example, about 30 % of forest plots can be measured using a wooden or bamboo stick, or had to be assessed through interpretation of image plots even a fishing rod. The tolerance for tree height meas- in Tibet. urement is 3 % (for trees less than 10 m) or 5 % (for tree heights exceeding 10 m). In China’s NFI, height mea- surements are only required for 3–5 average trees on Field survey methods each forest plot (SFA 2014a). Field surveys represent the key activities of the NFI, re- Besides dbh and tree height, other quantitative atti- lating directly to the subsequent statistical analysis and butes, including azimuth and horizontal distance from inventory outputs. A field survey usually involves three the plot center to the sample tree, are measured usually aspects: survey items, survey procedures and survey using a box compass. In addition, crown cover (or crown methods. Survey items (also called “variables” here) are closure, canopy cover, canopy closure) of a forest stand defined by the technical specification. According to the need to be measured using transect sampling with two newest Technical Specifications on National Continuous diagonal lines or cover area estimation based on mean Forest Inventory issued for excution in 2014, the survey crown width. Sometimes, crown cover is measured using items include land use and cover, site and soil, forest visual estimation or subjective judgement, based on the stand characteristics, forest functions, ecological situa- experience of the cruising team. tions, species names and other items (SFA 2014a). Sur- vey procedures generally involve plot location and Qualitative assessments establishment, survey of tree attibutes and plot attri- Most of tree and plot attributes are assessed using quali- butes. In China’s NFI, all plots are located on the kilo- tative judgement. The qualitative attributes are usually meter grids of topographic maps 1:50,000 or 1:100,000, classified into several classess, groups, or grades. Land and should be permanently marked and periodically type and forest category are two of the most important revisited. The survey of tree and plot attributes involves plot attributes. Land is classified into two types: forest two different methods, measurement and judgement. land and non-forest land. Forest land and non-forest land are both divided into 5 classes (Table 3). Some of Quantitative measurement these can be divided further. The most important quantitative attibute is the diameter Forests are also classified into five categories related to at breast height (dbh) of sample trees, which is measured administrative use: protection forest, special use forest, tim- using a diameter tape. The breast height is defined as ber forest, fuel-wood forest, and economic forest. The first 1.3 m, and the minimum dbh is 5.0 cm measured over two categories are called “ecological forests”, while the bark. The maximum allowable measurement error remaining three categories are known as “commercial Zeng et al. Forest Ecosystems (2015) 2:23 Page 7 of 16 Table 2 Sampling designs for 31 provinces in China’s NFI Provinces Sub-pop. Area: km number of Plots Grid (Km) Plot shape Plot size (ha) Year of last inventory Beijing / 16,410 4074 2∗2 Square 0.0667 2011 Tianjin / 11,305 2818 2∗2 Square 0.0667 2012 Hebei / 187,693 11,709 4∗4 Square 0.06 2011 Shanxi / 156,623 9915 4∗4 Square 0.0667 2010 Inner Mongolia / 1,183,000 17,951 8∗8 Rectangular 0.06 2013 Liaoning / 145,739 4613 4∗8 Square 0.08 2010 Jilin / 189,193 8865 4∗16/3 Square 0.06 2009 Heilongjiang I 100,540 1571 8∗8 Square 0.06 2010 II 64,786 1013 8∗8 Rectangular 0.06 2010 III 289,282 9083 4∗8 Square 0.06 2010 Shanghai / 6341 3365 2∗1 Square 0.0667 2009 Jiangsu / 102,600 8536 4∗3 Square 0.0667 2010 Zhejiang / 101,800 4249 4∗6 Square 0.08 2009 Anhui / 138,165 11,678 4∗3 Square 0.0667 2009 Fujian / 121,501 5051 4∗6 Square 0.0667 2013 Jiangxi / 166,946 2608 8∗8 Square 0.0667 2011 Shandong / 152,221 9646 4∗4 Square 0.0667 2012 Henan / 167,000 10,358 4∗4 Square 0.08 2013 Hubei / 185,900 5820 4∗8 Square 0.0667 2009 Hunan / 211,835 6615 4∗8 Square 0.0667 2009 Guangdong / 176,769 3685 6∗8 Square 0.0667 2012 Guangxi / 237,600 4948 6∗8 Square 0.0667 2010 Hainan / 33,907 2829 4∗3 Square 0.0667 2013 Chongqing / 82,335 5133 4∗4 Square 0.0667 2012 Sichuan / 483,744 10,007 6∗8 Square 0.0667 2012 Guizhou / 176,167 5500 4∗8 Square 0.0667 2010 Yunnan / 382,644 7891 6∗8 Square 0.0667 2012 Tibet / 1,228,436 5855 6∗8 Circular 0.0667 2011 Shaanxi / 205,977 6440 4∗8 Square 0.08 2009 Gansu I 449,734 2817 2∗3 Square 0.08 2011 II 4038 3∗3 Square 0.08 2011 III 10,846 4∗8 Square 0.08 2011 Qinghai I 721,514 76,616 2∗2 Square 0.08 2013 II 51,620 4∗2 Square 0.08 2013 Ningxia / 51,955 12,936 2∗2 Square 0.06 2010 Xinjiang I 164,700 16,474 3∗4 Square 0.08 2011 II 59,917 6∗4 Square 0.08 2011 a 2 The permanent plots in Jilin province were established through intensifying the 4∗8 km grid by 50 %, that is, there are 3 plots for each 64 km square. The number of plots (5855) in Tibet only includes the ground plots in the 1st sub-population (30 forestry counties). The number of plots in Gansu, Qinghai, Ningxia and Xinjiang include some RS-interpretation plots, as supplement to ground plots. Taiwan, Hongkong and Macao are not included in this table forests”.The definition of forest in China’sNFI haschanged forests not only include arboreal forests and bamboo forests to some extent during different periods. Before 1994, the with a crown cover of more than 20 %, and economic minimum crown cover of a forest stand was 0.4 (or 35 %); shrubs with a crown cover of more than 30 % which pro- but since the 5th NFI in 1994–1998, the minimum crown vide mainly non-wood forest products and fruits, but also cover is defined as 20 %. In addition, since the 6th NFI, include other special shrubs, which are defined as shrub Zeng et al. Forest Ecosystems (2015) 2:23 Page 8 of 16 Table 3 Land Classification System Class name Description Forest land Arboreal forest Forest land with a minimum area of 667 m , a minimum width of 10 m, and a minimum crown cover of tree species of 20 % Bamboo forest Forest land composed of bamboos with a minimum dbh of 2 cm Open forest land Forest land with a crown cover of tree species of 10–19 % Shrub land Forest land with a minimum crown cover of shrub species of 30 %, including two sub-classes: special shrubs and general shrubs Other forest land Unclosed afforestation land, nursery land, clear-cut land, burned forest land, and planned forest land Non-forest land Cropland Cultivated land, farmland Grazing land Pasture, rangeland, grassland Inland water Lakes, rivers, and other water bodies Built-up land Industry and commerce, mining, traffic and transport, tourist facilities, dwellings and parking sites, gardens and parks Other land Unused and unproductive non-forest land lands located above the tree lines or in the area with less double sampling for stratification based on remote sens- than 400 mm precipitation, or located in the karst region ing interpretation and ground survey was tested in the or dry-hot valley areas (SFA 2014a). Jiangxi pilot in 1996, which settled a technical founda- Other forest characteristics include origin, dominant tion for wide application of remote sensing. In NFI6, species, age class/group, community structure, species remote sensing was widely used in all of the 31 prov- composition, naturalness, disaster class, health class and inces. Several provinces in western China, such as Tibet, so on. Forests are classified into two classes by origin: Xinjiang, Gansu, Qinghai and Sichuan, conducted natural forests and plantations. They are also classified firstly their full-coverage inventories based on remote into five classes by age category: young, middle-aged, sensing (Zeng 2004; Wang et al. 2005; Zhang and Wang near-mature, mature, and post-mature forests. The de- 2007). In the 7th and 8th NFIs, remote sensing contin- tails of definitions and specifications of all qualitative at- ued to be appllied as an effective supplement to ground tributes can be found in SFA (2014a). plots and an important information source for forest mapping. During this period, integrated application of New technology multi-scale remotely sensed data has been taken into Remote sensing consideration. The application of remote sensing (RS) in forest inven- tory can be traced back to early years of new China. The GPS and other technologies middle of the 1950s was the first time in China that aer- Global positioning systems (GPS) have been applied to ial forest surveys and comprehensive ground investiga- forest inventory for less than 20 years in China. In the tions were implemented. Then, a technical system for NFI5, combining with the implementation of UNDP forest inventory was established which was based on aer- CPR 91/151 project, the application of GPS in NFI was ial photography and visual measurement. In the NFI1, first tested in the Jiangxi pilot in 1996. In the NFI6, GPS remote sensing played an important role. At that time, was gradually applied to field survey in several provinces the remotely sensed data were aerial photos. In the (Luo et al. 2002). Since the 7th and 8th NFIs, GPS tech- NFI2, remote sensing was applied to forest inventory of niques have been widely used in field work of NFI in all Tibet in 1977. Black-and-white MSS images of 1:500,000 31 provinces. Using the functions of positioning and navi- scale and aerial photos of small scale were used to deter- gation decreases the time for locating plots, increases the mine forest area. In the NFI3, the application of remote ratio of re-measured plots, and provides assurance in some sensing was less important. In inaccessible regions in extent to increase the quality of inventory data (Luo et al. some provinces in western China, remotely sensed data 2002; Wu and Jiang 2006). was used as supplement of field survey. In the NFI4, re- Besides RS and GPS, additional new technologies in- mote sensing was applied to forest inventory of Tibet clude advanced database applications and modeling, and again in 1991, where Landsat TM images were used to the use of portable digital assistants (PDA/i-pad) and interpret forest area, and field plots were measured to geographical information systems (GIS). Statistics and obtain forest volume per hectare. In NFI5, combining calculations mainly depended on manual work, or were with the implementation of UNDP CPR 91/151 project, supported to some extent by calculator and simple Zeng et al. Forest Ecosystems (2015) 2:23 Page 9 of 16 computer before the NFI4. During the NFI4 in 1989– As mentioned before, the original definition of forest 1993, normative database files based on dBase and in China’s NFI has changed somewhat during different BASIC started to be applied in the office work. In the inventory periods. Thus, the values of the forest areas in NFI5, mini-type of database based on Foxplus was used. Table 4 are not completely comparable. Figure 1 shows Since theNFI6, large database based on Oracle has been the resulting differences of forest areas, using three inde- applied, which can ensure security and stability of NFI pendent time series and the published total. data, and increase the efficiency of data processing and In addition, there are other factors affecting the compar- information management. ability between different measurement occasions, such as Modeling techniques were only used for establishment improved sampling and progress in remote sensing. For of tree volume equations between NFI1 and NFI4. In example, during the three decades from NFI1 to NFI6, only NFI5 (1994–1998), the application of growth and yield three inventories were conducted in Tibet, and the results models was used in the Jiangxi pilot, with the implemen- were not completely comparable. Tibet is an autonomous tation of UNDP CPR 91/151 project. Since NFI6, model- region with extensive forest areas, the highest growing ing techniques have been widely used for estimation of stock volumes and a low population density. Thus, the for- growth and drain (including cut and dead volume) (SFA est area and growing stock volumes are relatively stable. 2011). During NFI8, specific modeling techniques were But during three inventories in 1977, 1991 and 2001, the been applied to develop biomass equations for the main forest area has increased from 6.32, 7.17 to 8.45 million ha, tree species in China (Zeng 2011, 2014, 2015). and the growing stock volume increased from 1.40 to 2.05 The first pilot of PDA application was made in Tianjin and 2.27 billion m . The increase of forest area and growing in 2002. Since NFI7, PDA techniques have been used in stock volume in Tibet amounts to 0.85 million ha and 0.65 several provinces, especially in north-eastern China billion m respectively from NFI3 to NFI4, representing 9 (Wang 2006). In recent years, data collection system based and 65 % of the total increase of forest area and volume in on i-pad has started to be applied in NFI (Xiao et al. thewhole country. Thespecificinventoryresults ofother 2013). Application of PDA/i-pad system in NFI can provinces, such as Sichuan, also influenced the comparabil- achieve paper-free data collection, increase the accuracy ity of national statistics between different inventory periods. of data, and strengthen the pertinence of quality control (Zhang and Zhang 2008). However, because of the disad- vantages of poor waterproof capability, less battery life, Forest types, origins and age classes small memory space, and limited CPU processing ability, Forest types PDA is still not applied to NFI in most provinces, espe- Forests include three types: arboreal forests, bamboo cially in southern China. forests, and special shrubs. Among the total forest The application of GIS (geographical information sys- area, arboreal forests are 175.34 million ha (not in- tem) in NFI was relatively late. In NFI5, combining with cluding 2.13 million ha forests in Taiwan, Hongkong the implementation of UNDP CPR 91/151 project, the and Macao), bamboo forests are 6.01 million ha, and application of GIS in was first tested in the Jiangxi pilot, special shrubs are 24.21 million ha. Forests are further which laid a foundation for wide application of GIS in classified into 5 categories, i.e., protective forest, NFI. Since NFI6, GIS techniques have been widely used special-use forest, timber forest, fuelwood forest, and in NFI, providing a technical platform for management economic forest, which are respectively 99.67, 16.31, of inventory data, querying and analysis of spatial data, 67.24, 20.57, 1.77 million ha (SFA 2014b). The areas and increasing the quality and efficiency of forest map- and proportions of different forest categories from ping (Wang and Li 2010; Shu 2014). NFI1 to NFI8 in China are listed in Table 5 (Lei 2005; SFA 2009, 2014b). Results and Discussion Table 5 shows that the proportions of protective forest Forest area and growing stock volumes and special-use forest are increasing gradually from According to the results of NFI8 in 2009–2013, the NFI1 to NFI8 while those of timber forest and fuel- total forest area in China is 207.69 million hectares, wood forest are decreasing. The changes from NFI5 to the relative forest cover is estimated at 21.63 %, and NFI7 are especially obvious, reflecting the strategic the total growing stock volume at 15.14 billion m shift in China’s forest policy from timber production (SFA 2014b). Estimates of forest area, forest cover per- to ecological conservation at the turn of the century. cent and growing stock volume from NFI1 to NFI8 are The proportion of econmic forest increases gradually listed in Table 4. Forest area, forest cover percent and from NFI1 to NFI5 but decreases slightly from NFI5 growing stock volume show continuous increase, ex- to NFI8 which is the result of the market share of cept from NFI1 to NFI2, due to large scale afforest- fruits and other non-timber forest products reaching ation and strict natural forest protection. close to saturation levels. Zeng et al. Forest Ecosystems (2015) 2:23 Page 10 of 16 Table 4 Forest area, forest cover percent and growing stock mature, and over-mature forests. According to the re- volume of the eight NFIs in China sults of NFI8, the area and volume of young forests are NFIs Forest area Forest cover Growing stock volume 53.32 million ha and 1.63 billion m respectively. Those (million ha) percent (%) (billion ha) of middle-aged forests are 53.11 million ha and 4.11 NFI1 121.86 12.69 8.66 billion m , and those of near-mature, mature, and over- NFI2 115.28 12.01 9.03 mature forests are respectively 58.17 million ha and 9.04 billion m (SFA 2014b). NFI3 124.65 12.98 9.14 The majority of the forests in China are young and NFI4 133.70 13.92 10.14 middle-aged, occupying 65 % of the total forest area. NFI5 158.94 16.55 11.27 The results of previous NFIs show that the proportions NFI6 174.91 18.21 12.46 of area and volume of forests in two age classes are rela- NFI7 195.45 20.36 13.72 tively constant (Table 7). The young and middle-aged NFI8 207.69 21.63 15.14 forests occupy about 2/3 of the area and less than 40 % of the total volume, and the mature forests occupy about Forest origins 1/3 of the area and more than 60 % of the volume. Forests are classified into two main types: natural forests and plantations. In the traditional concepts in China’s Increment and drain NFI, natural forests and plantations do not include other Theincrement estimatedbyChina’sNFI is definedas the special shrubs except economic shrubs. According to the volume increment of survivor trees between two inventory results of NFI8, the area and growing stock volume of periods plus half of the volume increment of harvested or natural forests amount to 121.84 million ha and 12.30 dead trees and the volume of ingrowth trees that exceed billion m respectively, while those of plantations are the dbh-threshold of 5.0 cm between the two inventories 69.33 million ha and 2.48 billion m (SFA 2014b). (SFA 2011). According to the results of NFI8, the annual Most of the forests in China are natural forests occupying increment of forests is 0.76 billion m where the increments 64 % of the total forest area and 83 % of the total growing of survivor trees, harvested or dead trees, and ingrowth stock volume respectively. Looking at the results of previ- trees are 0.52, 0.07, and 0.17 billion m , respectively. Look- ous NFIs, we find that the plantation area and volume pro- ing at the results of previous NFIs, we find that the annual portions gradually increase from 20 and 2 % in NFI1 to 36 increment has gradually increased from 0.19 billion m in and 17 % in NFI8 (Table 6). This increase is mainly due to NFI1 to 0.76 billion m in NFI8. The main reason for this the extensive afforestations during the past decades. increase is probably the rapid development of plantations in China. Forest age classes The drain estimated by China’s NFI is defined as the Forests, excepting bamboo and economic forests, are classi- volume of trees that were found to be harvested or dead fied into five age classes: young, middle-aged, near-mature, between two inventory periods. The volume of the FA4 FA1 FA2 FA3 Fig. 1 Development of Forest Areas of the eight NFIs in China. (FA1—Forest areas only inclcuding ≥0.4 (or 35 %) closed cover forests and economic shrubs; FA2—Forest areas also including 0.2–0.3 (or 20–35 %) cover forests and economic shrubs; FA3—Forest areas including both ≥0.2 (or 20 %) cover forests and all special shrubs (Wang and Hou 2014); FA4—Forest areas published in eight NFIs Zeng et al. Forest Ecosystems (2015) 2:23 Page 11 of 16 Table 5 The areas and proportions of forest categories from eight NFIs in China (Note: The forests in Taiwan, Hongkong and Macao are not included in this table) NFIs Total Protection Forest Special-use forest Timber forest Fuelwood forest Economic forest Area % Area % Area % Area % Area % Area % NFI1 119.78 100.00 7.85 6.55 0.67 0.56 99.07 82.71 3.67 3.07 8.52 7.11 NFI2 113.42 100.00 13.21 11.65 1.30 1.14 83.94 74.01 3.69 3.25 11.28 9.95 NFI3 122.80 100.00 17.76 14.47 3.12 2.54 83.73 68.18 4.44 3.62 13.74 11.19 NFI4 131.85 100.00 19.28 14.62 3.35 2.54 88.83 67.38 4.29 3.25 16.10 12.21 NFI5 156.84 100.00 24.59 15.68 3.97 2.53 103.61 66.06 4.45 2.84 20.22 12.89 NFI6 172.79 100.00 58.51 33.86 6.38 3.69 83.47 48.31 3.04 1.76 21.39 12.38 NFI7 193.33 100.00 93.79 48.51 13.22 6.84 64.16 33.19 1.75 0.90 20.41 10.56 NFI8 205.56 100.00 99.67 48.49 16.31 7.93 67.24 32.71 1.77 0.86 20.57 10.01 sample trees that have been cut or died between succes- North-Eastern, Eastern, South-Central, South-Western and sive measurement occasions is calculated by using the tree North-Western region. Table 8 presents the forest areas measurements at the first occasion and adding half of esti- and volumes of the six regions in eight NFIs. mated growth between measurements (SFA 2011). Ac- Table 8 shows that the proportions of forest areas in the cording to the results of NFI8, the annual drain is 0.51 six regions are not very different except the lower propor- billion m with the drains of harvested trees and dead tion in north-western region. The developments of forest trees being 0.39 and 0.12 billion m . Comparing the re- areas in the six regions are very similar corresponding to sults of previous NFIs, the annual drain gradually in- overall changes in the whole country, but the trends of for- creased from 0.34 billion m in NFI3 (having no data est area proportions are variable. The proportion of forest about drain in NFI1 and NFI2) to 0.51 billion m in NFI8. area in the north-eastern region decreased from 21 % in the NFI1 to 16 % in the NFI8, whereas the proportion in Geographical distribution the north-wesertn region increased in recent decades from The forests in China are mainly distributed in the 6.6%in theNFI5to9.5 %inthe NFI8. north-eastern, south-western and southern regions. Similarly, Table 8 shows that the proportions of forest About one half of the forest area is located in the 5 prov- volumes in the six regions differ greatly. More than 40 % inces Inner Mongolia, Heilongjiang, Yunnan, Sichuan, and of the total volume is found in the south-western region, Tibet (Fig. 2). with only about 1/3 in the northern, eastern, south- Less than 10 % of the forest areas are distributed in the central and north-western regions. The proportion of following 16 provinces (municipality, or autonomous forest volume in the north-eastern region decreased region): Beijing, Tianjin, Hebei, Shanxi, Shanghai, Jiangsu, continuously from 25 % in the NFI1 to 19 % in the Anhui, Shandong, Henan, Haihan, Chongqing, Gansu, NFI8. The development of volumes in south-western Qinghai, Ningxia, Honghong, and Macao. To simplify the region is similar to that in the north-eastern region. In analysis of change and distribution patterns, six regions contrast, the proportions of volumes in the eastern and have been identified for the whole country: the Northern, south-central regions increased from 6 and 7 % in the Table 6 Areas and growing stock volumes of natural forests and plantations from eight NFIs in China NFIs Natural forests Plantations 3 3 Area (million ha) % Volume (billion m ) % Area (million ha) % Volume (billion m)% NFI1 96.09 80.22 8.31 98.11 23.69 19.78 0.16 1.89 NFI2 91.12 80.42 8.53 96.93 22.19 19.58 0.27 3.07 NFI3 91.67 74.72 8.38 94.05 31.01 25.28 0.53 5.95 NFI4 97.48 74.00 9.20 92.84 34.25 26.00 0.71 7.16 NFI5 110.17 70.24 9.90 90.74 46.67 29.76 1.01 9.26 NFI6 115.76 68.49 10.59 87.52 53.26 31.51 1.51 12.48 NFI7 119.69 65.99 11.40 85.33 61.69 34.01 1.96 14.67 NFI8 121.84 63.73 12.30 83.20 69.33 36.37 2.48 16.80 Zeng et al. Forest Ecosystems (2015) 2:23 Page 12 of 16 Table 7 Areas and volumes of young and middle-aged forests and mature (including near-mature and over-mature) forests from eight NFIs in China NFIs Young and middle-aged forests Mature forests 3 3 Area (million ha) % Volume (billion m ) % Area (million ha) % Volume (billion m)% NFI1 70.68 64.14 2.49 28.75 39.51 35.86 6.17 71.25 NFI2 68.19 69.00 3.39 38.52 30.64 31.00 5.41 61.48 NFI3 72.17 68.48 3.36 37.71 33.22 31.52 5.55 62.29 NFI4 77.84 69.60 3.71 37.44 34.00 30.40 6.20 62.56 NFI5 92.27 69.69 4.20 38.50 40.14 30.31 6.71 61.50 NFI6 96.88 67.85 4.71 38.93 45.91 32.15 7.39 61.07 NFI7 104.63 67.25 5.35 40.04 50.96 32.75 8.01 59.96 NFI8 106.43 64.66 5.74 38.84 58.17 35.34 9.04 61.16 NFI1 to 11 and 12 % in the NFI8 respectively while the ment; more efficient sample designs; implementation of volume proportions in the northern and north-western improving technology; expansion of the variables moni- regions show little change. tored; and scientific transparency. Our focus below is how China’s expanding NFI exemplifies these global trends. Discussion In reviewing the evolution of forest inventories in China, Nationally consistent measurement Europe, and the US through the 20th and 21st centuries, Initial inventory efforts are almost necessarily local, common themes emerge. Each of these inventories has using methods appropriate for meeting specific informa- shown movement toward: nationally consistent measure- tion needs. As national-scale resource assessment has Fig. 2 Current Forest Map of China. Source: SFA (2014b) Zeng et al. Forest Ecosystems (2015) 2:23 Page 13 of 16 Table 8 Forest areas and volumes of the six regions in eight NFIs Regions NFI1 NFI2 NFI3 NFI4 NFI5 NFI6 NFI7 NFI8 Forest areas (million ha) Total 119.78 113.31 122.68 131.73 156.84 172.79 193.33 205.56 NO 15.43 16.40 17.12 18.17 20.37 23.29 27.61 29.74 NE 25.16 25.02 25.79 26.43 29.18 29.85 31.63 32.71 EA 19.39 16.42 19.29 21.56 26.99 28.65 30.51 32.07 SC 25.72 23.18 23.14 26.28 32.83 36.04 40.03 42.46 SW 25.90 24.64 28.74 30.71 37.14 42.39 46.31 49.06 NW 8.18 7.65 8.62 8.58 10.33 12.57 17.24 19.52 Forest volumes (billion m ) Total 84.70 88.01 89.14 99.10 109.08 120.98 133.63 147.79 NO 8.75 9.09 9.51 10.00 11.06 12.39 13.50 15.68 NE 21.33 21.94 21.48 22.41 23.59 23.66 25.68 28.18 EA 5.39 6.74 6.10 6.83 8.06 10.43 12.89 15.70 SC 5.94 7.15 6.78 7.52 9.24 12.24 15.31 17.44 SW 36.78 36.73 38.78 45.59 49.46 54.23 57.48 60.82 NW 6.51 6.36 6.49 6.75 7.67 8.03 8.77 9.97 NO northern region, including Beijing, Tianjin, Hebei, Shanxi, and Inner Mongolia, NE north-eastern region, including Liaoning, Jilin, and Heilongjiang, EA eastern region, including Shanghai, Jiangsu, Zhejiang, Anhui, Fujian, Jangxi, and Shandong, SC south-central region, including Henan, Hubei, Hunan, Guangdong, Guangxi, and Hainan, SW south-western region, including Chongqing, Sichuan, Guizhou, Yunan, and Tibet, NW north-western region, including Shaanxi, Gansu, Qinghai, Ningxia, and Xinjiang. The forests in Taiwan, Honghong and Macao are not included in this table become a priority in the countries we have surveyed, the More efficient sample designs need for consistent measurement standards has become National forest inventories are charged with monitoring apparent. Standards often originate from influential pilot large areas with limited budgets. Our survey of inter- studies or through lessons learned by sub-national or national inventories suggests that improvements to plot international inventories. In China, the continuous forest and sample designs are made in the interests of obtaining inventory (CFI) pilot in Jiangxi province strongly influ- better estimate precision without requiring additional field enced standards, beginning with the second NFI (1977– costs. Plot designs evolve as more efficient measurement 1981). Sampling strategies were tested and validated configurations are shown to adequately capture local condi- through the Jiangxi pilot application. Later, remote sens- tions, while new sample designs are developed to improve ing and GPS techniques now used in China’s NFI were variance estimates by controlling how plots are distributed also first applied in Jiangxi. International collaboration or analyzed. A “statistical” design based framework has affected the volution of forest inventory strategies. One been used in most inventories. Systematic or stratified sys- example is the use of permanent sample plots in a statis- tematic sampling designs are often used and three-stage tically sound way (e.g., Matérn 1984). design in US. Arranging plots into clusters is also common Regional differences in inventory methods still do particularly in Europe, a cluster aiming to be a one-day exist. For example, plot design varies widely within the workload on average. The FIA in USA uses detached plots. country. However, the NFI performs the central function A circular plot is the most common plot design, with either of integrating regional inventory methods by, for ex- one radius or a few radii. Angle count plot is used by some ample, developing standard classification methods that countries. are compatible with the measurements made in con- Through the 1950s and 60s, China’s developing capacity stituent regions. China’s capacity to coherently report to carry out forest inventory was dependent upon methods national forest resources across a wide range of ecosys- that were heterogeneous across counties. Pilot studies in tems has depended upon convergence toward consistent the 1970s led to establishment of continuous forest inven- methodologies, and this trend will likely continue. Note tory principles that have since influenced sample design also that a cost-efficient inventory may require different parameters nationally. While plot size, orientation, and re- sampling intensities in different ecozones. The most im- measurement cycle varies by province, permanent plots are portant aspect is that the estimates within a country and now standard across the country. The concept of unbiased between countries are comparable. plot distribution is standard, too, with simple random Zeng et al. Forest Ecosystems (2015) 2:23 Page 14 of 16 designs used in some provinces and stratified designs used other recent works (Yan et al. 2011; Zeng 2013) contrib- in others. With more and more application of high reso- ute to peer understanding of Chinese methods. FAO and lution remote sensing, it is possible to improve the sam- other projects, such COST Action E43 have done great pling design of the Chinese NFI, for example with reference work in adopting common definitions worldwide, a process to the annual inventory system in the US, allowing more which relies upon clear methodological description from immediate response of inventory results to broad-scale dis- cooperating countries (COST Action E43 2015). turbances or trends. Recent increases in Chinese forest area and growing stock have resulted from huge afforestation and reforestation Implementation of improving technology efforts. It is important both within and outside of the coun- New technology has affected how national forest inventor- try to understand methodological details used to verify ies get to, measure, store, and analyze plot information. Just these increases. It is also essential to see the extensive as basal area prisms enabled advances in decades past efforts, detailed here (Fig. 1), that have gone into reconciling to efficiency of plot data collection, new technologies changes to the inventory in the interests of making are influencing how China assembles its inventory estimates that are consistent over time. A next step in the estimates. Remote sensing has been used as the primary process of transparency might be the public access to the measurement of forest area in inaccessible regions, and is plot-level observations themselves. In addition to providing currently used to develop estimation strata in some prov- users more context about how estimates are made, public inces. Global positioning greatly facilitates the naviga- access would likely stimulate important ties to remotely tion needed to re-measure the permanent plots now sensed data as well as new analyses at more local levels. used throughout the country, and use of PDAs has Conclusions reduced time and human error associated with data This paper documents important changes in the Chinese input. NFI both to support continued trend analysis and to New modeling techniques have improved tree-level apprise data users of important changes to the inventory estimation of variables such as volume and biomass, and over the years. Critical details about sample design and plot have more recently been used to estimate growth, mor- design are likewise given, and uses of other data sources are tality, biomass and carbon storage (Ge et al. 2004; Li and described. New technologies and data needs ensure that Lei 2010). Finally, the use of GIS has improved how the Chinese inventory, like the inventories in other coun- inventory data are stored, queried, and applied to the tries, will continue to evolve. With historical changes and production of resource maps (Wang and Li 2010). current conditions as context, we have suggested likely directions for this evolution. Expansion of variables studied China’s early inventory efforts, like those throughout the Competing interests The authors declare that they have no competing interests. world at the time, focused on the timber supply. In China, as elsewhere, a growing appreciation of the eco- Authors’ contributions system services and non-timber forest products provided WeiSheng Zeng carried out the second and third sections about the NFI in China and the results. Erkki Tomppo carried out the first section National by forests has created a need for broader assessment Forest Inventories and participated in the fourth section Discussion. Sean capacities. Beginning with NFI7 (2004–2008), a suite of Healty carried out the Discussion and participated in the first section. Klaus environmental variables has been added to the inventory Gadow drafted the outline of the manuscript, and participated in the first and Discussion sections. All authors read and approved the final manuscript. to support assessment of ecosystem services (Table 1). This has enabled new assessments of both ecological Acknowledgements services (Dai et al. 2009) and forest health (Yang et al. The authors thank Ms Yang XueYun of the Academy of Forest Inventory and Planning, State Forestry Administration (Beijing), for compiling the main 2015). Like the rest of the world, China continues to de- results of previous NFIs in China. velop better biomass equations so that climate change mitigation function of forest carbon storage may be bet- Author details Academy of Forest Inventory and Planning, State Forestry Administration, ter understood (Zeng 2014). 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China Forestry Press, Beijing, p 170 Zhang HJ, Zhang J (2008) Using PDA and “3S” tecnniques to achieve paper-free data collection in forest inventory. Forestry Engineering 24(3):39–40 Submit your manuscript to a journal and benefi t from: 7 Convenient online submission 7 Rigorous peer review 7 Immediate publication on acceptance 7 Open access: articles freely available online 7 High visibility within the fi eld 7 Retaining the copyright to your article Submit your next manuscript at 7 springeropen.com
"Forest Ecosystems" – Springer Journals
Published: Dec 1, 2015
Keywords: Ecology; Ecosystems; Forestry
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