Environmental Management DOI 10.1007/s00267-014-0278-y

Wetland Degradation: Its Driving Forces and Environmental Impacts in the Sanjiang Plain, China Kaishan Song • Zongming Wang • Jia Du Lei Liu • Lihong Zeng • Chunying Ren

•

Received: 2 April 2013 / Accepted: 8 April 2014 Ó Springer Science+Business Media New York 2014

Abstract This study investigated human-induced longterm wetland degradation that occurred in the Sanjiang Plain. Results from analyzing land-use/land-cover data sets derived from remotely sensed Landsat Multispectral Scanner/Thematic Mapper imagery for four time points showed that wetlands in the Sanjiang Plain have been severely transformed, and the area of wetlands decreased by 38 % from 1976 to 1986, by 16 % from 1986 to 1995, and by 31 % from 1995 to 2005. This study showed that transition to agricultural cultivation accounted for 91 % of wetland losses, whereas transition to grassland and forest accounted for 7 % of the wetlands losses. Institutional strategies and market policies probably exerted great impacts on agricultural practice that directly or indirectly influenced the decrease in wetlands. This study also indicated that an increased population likely led to wetland conversion to cropland by showing a high correlation between population and cropland (R2 = 0.92, P \ 0.001). Wetland loss occurred during later time intervals at a low rate. This study suggests that the existing wetland-protection measures in the Sanjiang Plain should be reinforced further because of possible environmental consequences of wetland loss, such as enhanced soil carbon emission,

Electronic supplementary material The online version of this article (doi:10.1007/s00267-014-0278-y) contains supplementary material, which is available to authorized users. K. Song (&)  Z. Wang (&)  J. Du  L. Liu  L. Zeng  C. Ren Northeast Institute of Geography and Agricultural Ecology, Chinese Academy of Sciences, No. 4888, Shengbei Street, North-zone of High-tech District, Changchun 130102, China e-mail: [email protected] Z. Wang e-mail: [email protected]

changed hydrological cycling, and regional temperature increase. Keywords GIS  Land-use/land-cover change  Remote sensing  Sanjiang Plain  Wetlands

Introduction Wetland ecosystems are associated with a diverse and complex array of direct and indirect uses (Mitsch and Gosselink 2007). Direct uses include the use of wetlands for water supply and harvesting of wetland products such as fish and plant resources. Indirect benefits from wetlands come from their environmental functions such as flooding retention, groundwater recharge/discharge, and nutrientcontamination abatement (Lewis 1995). Changes in land use/land cover (LULC) can have important consequences to natural resources (Houghton 1994; Houghton et al. 1999; Turner II et al. 1995; Pontius et al. 2004; Liu et al. 2005) and can substantially affect some key aspects of earth system functioning (Mather 2006; Soler and Verburg 2010). Likewise, areal changes of wetlands can substantially affect ecosystem processes (Mitsch and Gosselink 2007; Zhang et al. 2010; Wang et al. 2011). Numerous studies have shown that the areal change of wetlands directly impacts worldwide biotic diversity (Sahagian and Melack 1998; Seidl and Moraes 2000), contributes to local and regional climate change (Chase et al. 1999; Foley et al. 2005; Lin et al. 2009; Huang et al. 2010a), and even contributes to global climate warming (Houghton et al. 1999; Intergovernmental Panel on Climate Change [IPCC] 2007). One of the most typical examples for the areal change of wetlands in China is the Sanjiang Plain, which used to be the largest concentrated freshwater wetland but currently is

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second to the Qinghai–Tibet Highland marsh (Liu and Ma 2002; Gong et al. 2010). The wetlands in the Sanjiang Plain harbor hundreds of species of birds and other living creatures (Zhao 1999a; Liu and Ma 2002). From the late 1950s to the early 1990s, a number of large farms were developed in the plain resulting in an 80 % loss of wetlands (Liu and Ma 2002; Song et al. 2008). Because the Sanjiang Plain has gone through the most dramatic LULC change in China (Liu and Ma 2002; Liu et al. 2005), the LULC change of this area is a hot research topic (Liu et al. 2005; Gong et al. 2010). According to Zhao’s (1999a) investigation, all of the natural wetlands in the Sanjiang Plain would disappear within 20 years if the rate of wetland loss remained the same as that observed before 1995 (Zhao 1999b). The wetland landscapes in this area have changed and fragmented severely (Song et al. 2008; Gong et al. 2010; Qiu 2011) due to intensive human activities, and this wetland degradation has led to increasingly frequent droughts, decreased river runoff, and decreased groundwater levels (He 2000; Zhang et al. 2010; Yu 2011). With a growing awareness of the importance of wetland ecological and environmental functions and a rapid decline of wetlands in this region, eight wetland nature reserves have been established (Wang et al. 2006; Qiu 2011; Zhang et al. 2011). Three of these reserves are of international importance with Ramsar site numbers (see Fig. 1b): (1) Sanjiang National Nature Reserve [47.330 0.3600 N and 134.120 0.0000 E (Ramsar site no. 1152)] covers approximately 164,400 ha; (2) Honghe National Nature Reserve [47°290 2400 N and 133°0.240 0000 E (Ramsar site no. 1149)] covers approximately 21,800 ha; and (3) Xingkai Lake National Nature Reserve [45.100 0.1200 N and 132.190 0.1200 E (Ramsar site no. 1155)] covers approximately 222,500 ha (The Ramsar Convention on Wetlands 2002). Overuse of groundwater and intensive agricultural activities are considered to be the major threats, and hunting and fisheries also used to be threats to waterfowl and protective birds in these nature reserves (Liu and Ma 2002; Wang et al. 2011). Given the ever-increasing pressure of food security in China, more croplands will be developed in the plain, and thus wetlands are subjected to being cultivated for food production (Cyrannoski 2009; Zhang et al. 2010; Qiu 2011). Basic information on wetland-resource status and trends is critical for evaluating the effectiveness of wetland management (Megan et al. 2001). Government and wetland experts have been paying increasing attention to the areal change of regional wetlands (Mitsch and Gosselink 2007; Qiu 2011; Song et al. 2012). Liu (1995) examined the influence of a large-scale agricultural development on the wetlands of the Sanjiang Plain and investigated the change of main LULC types using remote sensing in the subregion of the Sanjiang Plain (Song et al. 2008). Liu and Ma (2002)

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concluded that the natural land covers in the Sanjiang Plain, wetlands, and forestry land have mostly decreased and argued for the conservation of wetland structure to promote wetland functionality. All of these qualitative studies to some extent described the dynamic characteristics of wetlands in part of the Sanjiang Plain (Liu and Ma 2002; Zhang et al. 2010, 2011), but they did not give detailed information about how wetlands changed at regional scale and over a long time period (Liu et al. 2005; Song et al. 2008). A lack of accurate temporal and spatial dynamic data sets for the whole area has prevented conducting quantitative assessments about wetland dynamics and their relationship with other LULC (Cyrannoski 2009; Gong et al. 2010). A compromise between environmental conservation and arable land demands for food and urbanization will continue to be a primary challenge for China in the future (Liu et al. 2005; Gong et al. 2010; Qiu 2011) and can threaten to decrease wetland sustainability in the Sanjiang Plain. Reaching such a compromise relies on the assessment of wetland areas within a large spatial and temporal scope. This study investigated the dynamics of wetlands in the Sanjiang Plain through the analysis of LULC changes that occurred between 1976 and 2005 using spatial data sets derived from remotely sensed imagery by way of global information system technology. The objectives of this study were as follows: (1) document changes in LULC in the Sanjiang Plain during three temporal intervals extending from 1976 to 2005 using Landsat images; (2) identify the forcing agents driving these changes by association with historical records and socioeconomic data, in particular, the changes in wetland area; and (3) examine the potential environmental consequences of these changes at a regional scale. Study Area The Sanjiang Plain lies in the far northeast part of Heilongjiang Province, China (Fig. 1a), with latitude 43°490 5500 – 48°270 4000 N and longitude 129°110 2000 –135°050 2600 E covering an area of 108,900 km2. In 2005, the population was 8.71 million with 53.2 % directly or indirectly being engaged in farming practice (Heilongjiang Province Statistical Year book [HPSY] 2006). The plain is a low alluvial plain formed by three rivers: the Heilongjiang River, the Songhua River, and the Wusuli River (Fig. 1b). The climate ranges from temperate humid to subhumid continental monsoon. The mean annual temperature is 3.2 °C with the coldest month in January (mean temperature 20.5 °C) and hottest month in July (mean temperature 21.7 °C). The annual precipitation is approximately 500–650 mm and mainly concentrates from May to September (80 %). Most of the rivers in the area exhibit typical alluvial plain characteristics with low gradient

Environmental Management Fig. 1 a Location of the Sanjiang Plain in China. b Topographic map with main geographic features. The three squares filled with yellow color indicate the location of three Rsamsar sites that have been listed internationally important wetlands. c LULC for the same area in 1954 (Color figure online)

resulting in a large channel curve coefficient. A small part of wetlands is distributed along these rivers in the mountainous area, but most wetlands are situated in the alluvial plain formed by these major rivers flowing along the plain. The main soils, constituting approximately 96 % of the whole study area, include the following: meadow soil (Eutric Vertisol, FAO), levee, swamp soil (Histosol, FAO), alluvial soil (Fluvisols, FAO), dark brown soil (Haplic Luvisol, FAO), and Albic soil (Albic Luvisol, FAO). For all of the soil types, the meadow soil occupies[37 % of the plain. The main types of vegetation in the Sanjiang Plain include the following: Phragmites communis, Carex lasiacarpa, C. pseudocuraica, C. meyeriana, Alnus sibirica, Betula fruticosa, Salix brachypoda, Lythrum salicaria, Calamagrostis anagustifolia, and

Pedicularis gvandiflora. Carex marsh is the main wetland plant and is distributed widely with Phragmites marsh scattered in some places (Zhao 1999a; Liu and Ma 2002). According to the thematic map-derived LULC, before the 1950s the Sanjiang Plain was still pristine (Fig. 1c): the cropland area was 15.9 % (1.7 million ha) of the region, the forest was 38.2 % (4.1 million ha), and the wetlands occupied 32.7 % (approximately 3.5 million ha). Since the end of the 1950s, a great number of farming units were developed converting large areas of wetlands, forest, and grassland into croplands. Today, the Sanjiang Plain is one of the main commodity grain-production bases of the nation with total annual yield of grain and bean of 1.67 9 107 tons (HPSY 2006). With national food security

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I. a

I. b

II. a

II. b

Forest

Cropland

Water-body

Built-up

Wetlands

Fig. 2 Landsat MSS/TM images showing typical LULC change in the Sanjiang Plain in 1976 and 2004. In region I, forest was converted to cropland. (Ia) Landsat MSS image from June 7, 1976. (Ib) LANDSAT-5 TM image from June 23, 2004. In region II, wetlands were converted to cropland. (IIa) Landsat MSS image from August 19, 1976. (IIb) LANDSAT-5 TM image from September 28, 2004.

These color-composite images were generated with band 4 (red), band 3 (green), and band 2 (blue, and white and cyan indicate urban land and built-up land, respectively; blue indicates water body; and red indicates vegetated surface. Yellow polygons are the interpreted LULC types (Color figure online)

being an increasing concern, more dry cropland will be converted to paddy field, and more wetlands will be cultivated for agricultural production (Cyrannoski 2009; Qi et al. 2009; Zhu and Yan 2011; Yu 2011).

MSS images data during 1975–1976; Landsat TM data during 1985–1986, 1995–1996, and 2004–2005). Cloudfree satellite images from July to September were acquired when vegetation cover is at a maximum for each studied time point. Radiometric calibration was performed for all of the images before delivered by China Remote Sensing Satellite Ground Station (http://www.rsgs.ac.cn). The ArcGIS 9.1 software package (ESRI, Redland, CA, USA) function ‘‘Fishnet’’ is used to generate a map frame with transverse Mercator projection and nets of 2 km to which scanned topographic maps were then registered. After creation of the map frame, Landsat TM data acquired in 1995–1996 were registered to topographic maps by collecting ground control points (GCPs) and used as the master images to georectify the remotely sensed data acquired in 1975–1976, 1985–1986, and 2004–2005. ERDAS Imagine 9.0 software package (ERDAS, Norcross, GA, USA) was used in the georectification of these Landsat

Materials and Methods Landsat Images and Preprocessing The spatial–temporal LULC data sets derived from Landsat images for the Sanjiang Plain form the basis for assessing the wetland dynamics of the study area. To cover the study region, 11 scenes of Landsat Multispectral Scanner (MSS) or Thematic Mapper (TM) data were acquired for each studied time point, which generally took 1 or 2 years to acquire good quality-images for one time point (Landsat

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images, and the Landsat-MSS data were resampled to a pixel resolution of 30 9 30 m with the nearest neighbor resampling method. The root mean squared error of the geometric rectifications was always \1.0 pixels (or 30 m). LULC Classification In this study, LULC data sets for 1986 and 1995 were derived from the National Land Cover Data set (hereafter called NLCD-85/86 and NLCD-95/96) with reference to the data set NLCD-99/00. All of these LULC data sets were developed through visual interpretation and digitization of TM images (Liu et al. 2002, 2005; Xiao et al. 2005) because a standard computer-assisted image classification algorithm to classify LULC is unpractical due to the extreme complexity of landscape patterns in China (Liu et al. 2005; Gong et al. 2010). A classification system of 25 land-cover types was used in the generation of these LULC data sets (Liu et al. 2005), and postprocessing of all of the digitized data resulted in the China LULC map. The NLCD-developed LULC-mapping protocol was followed to create the LULC data sets for 1976 and 2005 (Song et al. 2008), and the major points of the two LULC data sets are described as follows. The interpreter used the ArcGIS 9.1 software to identify the LULC types on the computer screen. Boundaries of LULC objects were then drawn and the attributes labeled to produce the digital map (Liu et al. 2002, 2005; Gong et al. 2010). Landsat TM images for 04/05 and Landsat MSS images for 75/76 were interpreted by making reference to NLCD-99/00 and NLCD-85/86 data sets, respectively. Using ArcGIS 9.1 software, LULC change patches were drawn on MSS or TM images (shown as a combination of band 432 RGB) for 1976, and then compared with NLCD-1985/1986, and for 2005 from NLCD-99/00 (e.g. Fig. 2a, b). The LULC maps from 85/86 to 99/00 were also used as the supporting information to identify LULC changes for each patch. Other ancillary data were also used in the process of interpretation, e.g. the vegetation map at a scale of 1:250,000, the topographic map at 1: 50, 000, the DEM at 1:100, 000 and the soil map at 1:500, 000. It is worth noting that a similar method was applied by Gong et al. (2010) for national wetlands mapping for 1990 and 2000. In the last point of generating LULC data sets, the 25 LULC types were grouped into seven LULC categories— forest, grassland, cropland, water body, wetlands, built-up land, and unused land—as referenced by the Chinese National Technical Standard for Land-Use Survey in China (Liu et al. 2002, 2005). Considering the need for accuracy and data comparability, we processed the data sets of the four time points at the smallest scale by merging small polygons \1 hectare.

Fig. 3 Ground points of the Sanjiang Plain visited in 2006 field surveys

Accuracy Assessment All NLCD data sets were assessed by field surveys (Liu et al. 2005; Xiao et al. 2005). Assessments of classification accuracy in 2005 were made using the methods proposed by Liu et al. (2002, 2005). Confusion matrix was used to assess the accuracy of the 2005 LULC map (Pontius and Millones 2011). Various representative routes with an accumulated survey length of 3,648 km across the Sanjiang Plain were investigated in July 2006, and a total of 1332 site-evaluation points were recorded with Global Positioning System along these routes (Fig. 3). The longitude and latitude of where these routes crossed each of the LULC type boundaries were recorded. The errors of classification and routes were registered into the spatial data set in 2005 and then transferred to grids having equally sized Landsat TM image pixels. By comparing the pixels in error with those of the routes, the errors in the classification of the images in 2005 were calculated. For the 1976 LULC data set, some auxiliary data, such as the vegetation maps (1: 250,000) and land-use maps of some counties [produced by air-photo and detailed land survey (1:100,000)] around 1976, were collected for accuracy assessment. Spatial Data Analysis Methods LULC changes were acquired by cross-tabulation detection method using ArcGIS 9.1, and change matrices were then produced. Quantitative information of the overall LULC changes, i.e. gains and losses in each category, was compiled and extracted. The change matrix gives an indication of the main types of changes (directions) in the study area

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(Jia et al. 2004; Liu et al. 2005; Shalaby and Tateishi 2007; Pontius et al. 2013). The average annual change rate (Kti) was calculated by the following formula (Eq. 1 Aldwaik and Pontius 2012): hP i J j¼1 ðCtji  Ctij Þ  100 % Kti ¼ ; ð1Þ P ðYtþ1  Yt Þ  Jj¼1 Ctij where J is number of LULC categories; i is index for category at the initial time point for a particular time interval; j is index for category at the final time point for a particular time interval; t is index for the initial time point of interval)Yt, Yt?1) where t ranges from 1 to T - 1; Yt is year at time point t; and Ctij is area of LULC that transitions from category i at time Yt to category j at time Yt?1. To analyze the overall LULC change characteristics in the Sanjiang Plain, annual percentage of change on the LULC for each time interval, meaning one rate per time interval, was calculated using Eq. (2), and the details can be found in Aldwaik and Pontius (2012).

impact of climatic change on wetland dynamics. Statistical analyses (analysis of variance [ANOVA]) were performed using SPSS 16.0 software package (Statistical Program for Social Sciences), and significance levels (P value) were calculated. Regression analysis was performed between cropland area and farming population to track the driving forces for wetland conversions in the study region, which was combined with institutional and historical records to support the driving-force analyses.

Results and Discussion Data Set Accuracy The mapping accuracies for 7 major LULC categories in 2005 are listed in Table 1. The producer’s accuracy ranges from 0.78 to 0.97 for the seven major LULC categories, whereas the user’s accuracies range from 0.89 to 0.97. An overall accuracy of 93 % was achieved for 2005 data set.

area of change during interval ½Yt ; Ytþ1 =area of study region  100 % duration of interval [Yt ; Ytþ1  nP P  hPJ PJ io J J  J¼1 i¼1 Ctjj j¼1 i¼1 Ctjj ¼  100 % Ytþ1  Yt

LC ¼

where LC is the annual change expressed as a percent of the study area.

Driving-Forces Analysis Socioeconomic data from HPSY (1990, 2000, 2006) were collected. To determine institutional factors and anthropogenic interventions that influence LULC changes, a series of participatory workshops and interviews were performed with the local residents. Historical information about natural resource, agricultural policies of the region in the past 30 years, and institutional policies in the past 50 years were obtained, which facilitated the analysis of their impacts on LULC change in this region. Information about the environmental impacts on large area wetland reclamations was obtained by collecting soil samples and analyzing nutrients of meadow soil and by analyzing water table dynamics data because paddy field was widely developed (Liu and Ma 2002). Furthermore, climatic data were obtained from the Chinese Meteorological Information Center to analyze the

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ð2Þ

We also collected 132 slices (a thin transect along two categories of LULC to evaluate LULC-mapping accuracy at various locations during the mapping process (Liu et al. 2005). Results indicate that 99.85 % of the polygon boundaries show \1.0 pixel (30 m) shift from the real boundary. The overall agreement was 91 % of the study area for 1976 and 93 % for 1986 and 1995 data sets (Liu et al. 2005; Xiao et al. 2005). LULC Dynamics Natural-resource management is a complex undertaking and is influenced by environmental, economic, social, and political factors (Meyer and Turner 1994; Rao and Rekha 2001; Weng 2002; Lambin and Geist 2006; Song et al. 2012). When broad LULC classes are examined between 1976 and 2005, LULC in the Sanjiang Plain was drastically modified, and these changes are shown in Fig. 4. As listed in Tables 2 and 3, cropland and forest were the two major LULC categories of the study region during the investigated temporal extent (from 1976 to 2005). Cropland

Environmental Management Table 1 Confusion matrices of LULC classification result for 2005 Ground surveys Map result

Pixels Cropland

Patches Forest

Grassland

Water

Built-up

Wetland

Unused

Total

User’s accuracy

Cropland

15,257

313

411

0

12

137

0

16,130

0.95

310

Forest

187

11,347

347

5

87

311

21

12,305

0.92

225

Grassland Water

157 0

107 0

4,174 14

0 3,422

8 0

262 83

0 0

4,708 3,519

0.89 0.97

85 70

Built-up

79

53

33

0

5,478

0

32

5,675

0.96

130

Wetland

247

325

247

211

18

13,457

187

14,692

0.92

345

Unused

0

0

107

0

21

43

1,347

1,518

0.89

35

Total

15,927

12,145

5,333

3,638

5,624

14,293

1,587

58,547

–

1,200

Producer’s accuracy

0.96

0.93

0.78

0.94

0.97

0.94

0.85

–

–

–

Overall accuracy

(54,482/58,547) = 0.93

Identified patches were digitized and measured with pixels in the calculation of the confusion matrices

accounted for 33 % (1976) and 51 % (2005) of the total area, whereas forest accounted for 33 % (1976) and 32 % (2005). Table 2 shows that the areas of cropland and builtup kept increasing from 1976 to 2005. In contrast, the areas of forest, grassland, water body, unused land, and wetlands decreased in the same study temporal extent. The most noticeable LULC change in the Sanjiang Plain is a rapid decrease in wetlands, and this is coincident with a rapid increase in cropland. In 1976, wetlands covered approximately 21 % of the Sanjiang Plain (2.2 million ha) but then decreased to 13, 11 and 9 %, respectively, in 1986, 1995, and 2005 with the remaining wetlands being approximately 958,700 ha. Between 1976 and 2005, the average annual decrease in wetland area was 42,400 ha. However, the decreasing rate was not steady but rather slowed down over time. The average annual decrease in wetland area was approximately 84,100 ha in the time interval between 1976 and 1986, approximately 24,000 between 1986 and 1995, and approximately 19,500 ha between 1995 and 2005. In terms of percentage, the areal change of wetland was -1.90 % for the whole study temporal extent, but this had a decreased decreasing magnitude, i.e. -3.77 % during 1976–1986, -1.73 % during 1986–1996, and -1.66 % during 1995–2005, respectively (Table 3). Meanwhile, cropland increased by 55.3 %, from 3.6 million ha in 1976 to 5.6 million ha in 2005, and had an average annual increase rate of 2.3 % during 1976–1986, 1.0 % during 1986–1995, and 1.2 % during 1995–2005. The considerable decrease in wetlands and the associated increase in cropland were likely caused by the rapidly increasing demand for commercial agricultural product and inadequate legal and institutional regulations for wetland protection (Liu and Ma 2002; Qiu 2011).

Built-up land area increased from approximately 174,000 ha in 1976–214,400 ha in 2005, whereas forest decreased slightly from 3.6 to 3.4 million ha in the same time interval (Table 2). Grassland decreased from approximately 833,400 ha in 1976 to 420,000 ha in 2005, in total 413,500 ha over the past three decades. The average annual decrease in grassland area is approximately 13,800 ha or 1.7 % in the plain. This average decrease rate varied over different stages, being 1.5, 5.0 and 0.2 % during 1976–1986, 1986–1995, and 1995–2005, respectively (Table 3). Table 2 shows that unused land and water bodies did not experience a large change, i.e. respectively, approximately 320,100 and 2,600 ha in 1976, and approximately 280,200 and 1,800 ha in 2005. Table 3 shows that LULC changes in the Sanjiang Plain varied during different time intervals. Most LULC types changed much more dramatically during 1976–1986 and then slowed down from 1985 to 1995 and from 1995 to 2005. The LC values also confirmed this trend, which was 1.4 % during 1976–1986, 1.2 % during 1986–1995, and 1.2 % during 1995–2005, and 1.3 % during the whole study temporal extent (Table 3). Tables 2 and 3 show that cropland, grassland, and wetlands are the main LULC categories showing the greatest changes during the past three decades. Because the interchange between wetlands and cropland is the major concern in this study, the discussion below will be focused on these two land-cover types. Wetlands Versus Other LULC Table 4 shows that wetlands were mainly converted to cropland accounting for 70 % of wetland loss; 17 % of wetlands became grassland; and a similar area of

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Fig. 4 LULC distributions across the Sanjiang Plain in 1976 (a), 1986 (b), 1995 (c), and 2005 (d)

wetlands turned to forest and water bodies during 1976–1986. However, only a very small portion of wetlands turned to built-up land and barren during the same interval. Similarly, 70 % of the wetlands were converted to cropland during 1986–1995. The amount of wetlands converted into cropland increased to 91 % between 1995 and 2005. Overall, approximately 91 % of wetlands were converted to cropland during 1976–2005, which is equivalent to approximately 1.5 million ha (Table 4). Conversion to cropland was the main reason for wetland loss during 1976–2005. The remaining wetlands were turned to forest or grassland as an indirect result of conversion to cropland (Fig. 5), and minimal

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wetlands were converted to built-up land through drainage systems for wetland reclamation and overuse of groundwaters (Liu and Ma 2002; Yu 2011; Gong et al. 2011). Contrarily, approximately 253,000 ha of other LULC types were reverted to wetlands from 1976 to 2005 (Table 5), which is approximately 17 % of total wetlands lost during the same temporal extent. The contrast between wetlands and other LULC interchange is shown in Fig. 5. Cropland accounted for 18 %, grassland contributed to 45 %, and water bodies and forest contributed to 36 % of the wetland increase. Because LULC data sets derived from satellite images are only a snapshot of the landscape,

Environmental Management Table 2 Areas for LULC categories and their proportions to total area in the Sanjiang Plain during different time points Year

Units

Cropland

Forest

Grassland

Water body

Built-up

Unused

Wetlands

1976

1,000 ha

3,587

3,599

833

320

174

3

2,231

33

33

8

3

2

0

20

4,525

3,728

748

278

213

1

1,389

(%) 1986

1,000 ha

1995

1,000 ha

2005

1,000 ha

(%)

42

34

7

3

2

0

13

4,942

3,851

411

282

213

2

1,173

(%)

45

35

4

3

2

0

11

5,569

3,442

420

280

214

2

959

51

32

4

3

2

0

9

(%)

Unit = 1,000 ha. All values are rounded to the nearest integer

Table 3 LULC change characteristics in the Sanjiang Plain during different time intervals Time intervals 1976–1986

1986–1995

1995–2005

1976–2005

Items

Cropland

Forest

Grassland

Water body

Built-up

Unused

Wetlands

LC 1.42

NCA

938,198

129,244

-98486

-41967

39262

-1308

-841337

CA/a

93,820

12,924

-9849

-4197

3926

-131

-84135

Kti

2.62

0.36

-1.49

-1.31

2.26

-5.01

-3.77

NCA

415576

122939

-337194

43338

9427

805

-215890

CA/a

46175

13660

-37466

482

1047

89

-23988

Kti

1.02

0.37

-5.01

0.17

0.49

6.86

-1.73

NCA

628389

-408752

9493

-2245

-11219

-304

-214692

CA/a

57126

-37159

863

-204

-1020

-28

-19517

Kti

1.16

-0.96

0.21

-0.07

-0.46

-1.31

-1.66

NCA

1982163

-156569

-413445

-39873

37469

-806

-1271917

CA/a Kti

66072 1.84

-5219 -0.15

-13782 -1.65

-1329 -0.42

1249 0.72

-27 -1.03

-42397 -1.90

1.16

1.21

1.33

Unit = 1000 ha NCA net changed area, CA/a net changed area per annum, Kti annual change relative to the category’s initial size (see Eq. 1 for detail), LC annual change expressed as a percent of the study area (see Eq. 2 for detail) for a particular time interval

Table 4 Area of wetlands converted into other LULC during various time intervals Interval

Cropland

Forest

Grassland

Water body

Built-up

Unused

Area

%

Area

%

Area

%

Area

%

Area

%

Area

%

1976–1986

852

70

136

11

202

17

21

2

4

0.3

0.03

0.0

1986–1995

245

70

49

14

42

12

12

3

0.6

0.2

0.09

0.0

1995–2005

397

91

24

5

10

2

4

1

0.3

0.1

0.7

0.2

1976–2005

1557

91

83

5

46

3

23

1.3

7

0.4

0.2

0.01

Unit = 1000 ha. The percentage indicates the portion of wetlands being converted into a specific LULC cover versus the total area of converted wetlands during a specific time interval

some grassland or forest, if flooded, can be interpreted as wetlands, and some water bodies, if dried up, can be interpreted as wetlands (Song et al. 2008; Gong et al. 2010). This may explain why grassland, water bodies, and forest are observed to contribute greatly to the wetland

increase and other LULC types reverted to wetlands seem unimportant. The cropland reverted to wetlands during the study interval was mainly the result of indiscriminant flooding of low-lying areas (Huang et al. 2010a; Zhang et al. 2010).

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Environmental Management

Fig. 5 Transitions that involve wetland during various time intervals: a 1976–1986, b 1986–1995, c 1995–2005, and d 1976–2005. In the legend for each subplot, A wetland, B cropland; C forest, D grassland, E water body. X ? Y conversion of LULC from category X to category Y where X(Y) can be A, B, C, D, and E, respectively

Driving-Forces Analysis Institutional Policies In the Sanjiang Plain, LULC has changed as a result of agricultural and economic policies adaptation since the foundation of the People’s Republic of China (1949), and this is in agreement with many investigations in various countries (Rao and Rekha 2001; Weng 2002; Foley et al. 2005; Serra et al. 2008; Soler and Verburg 2010). Four important time intervals related to the conversion of wetlands were witnessed in the Sanjiang Plain (Fig. 6). First,

123

from 1956 to 1960, a great number of veterans (approximately 81,500) swarmed to the Sanjiang Plain to convert wetlands into cropland for increasing food production during the 1958 Great Leap Forward period (He 2000). Second, from 1968 to 1972, approximately 450,000 educated youths were forced to settle in the region to take part in agricultural activities in response to the Going to the Countryside and Settling in the Communes movement (1960s–1970s), which was an important part of the Great Cultural Revolution. The third cultivation peak was during 1979–1982 when relatively dry weather facilitated wetland development (Wang et al. 2006). The last period, due to the

Environmental Management Table 5 Land area reverting to wetlands from other LULC during various time intervals Interval

Cropland

Forest

Grassland

Area

%

Area

%

Area

1976–1986

776

25

34

11

1986–1995

32

33

16

16

1995–2005

23

28

15

1976–2005

46

18

29

Water body

Built-up

Unused land

%

Area

%

Area

%

Area

%

131

42

66

21

1

0.3

0.4

0.1

43

44

7

7

0.3

0.3

0

0.0

19

27

34

14

17

0.7

0.8

0.9

0.4

12

115

45

61

24

2

0.6

0.5

0.0

Market Influences In 1992, a market-oriented economic system began to replace the former planned economic system. Because ricegrowing is more profitable than dry cropland farming, many farmers converted their dry croplands to paddy fields during the time interval from 1992 to 2005, other than reclaimed croplands from wetlands, because wetland-protection regulations were reinforced, and suitable wetlands remaining for cultivation were limited. Consequently wetland conversions have decreased ever since (Wang et al. 2006; Song et al. 2008). However, converting some wetlands to croplands to either dry cropland or to paddy fields (He 2000; Liu and Ma 2002) is still reported

Cultivated area (ha)

policy of agricultural modernization, modern agricultural machinery was introduced and large farms built at the end of 1980s, particularly after ‘‘household contract responsibility system’’ as part of ‘‘reform and open’’ policy was reinforced in China (Feng et al. 2005; Li and Wei 2010). The policy called ‘‘reform of rural taxes and administrative charges’’ was introduced in 2004 and was first adopted in Heilongjiang, the province of major food producers (Lin et al. 2006; HPSY 2006). Increased abandonment of cropland resulting from farming labor migrating to the city to improve their family income was reverted due to the introduction of this policy (Song et al. 2008). Due to the increase of farming profit, some illegal croplands were developed in the Sanjiang Plain during 2003–2005, and this trend has been going on until now (Song et al. 2008; Huang et al. 2010b; Zhang et al. 2010; see Supplementary Material in Figs. S1 and Table S1). Wetland loss is occurring; the wetland landscape structure is being damaged; and finally the functionality will disappear (Zhang et al. 2010; Gong et al. 2010; Niu et al. 2011). The current article and discussion highlight the need to protect the Sanjiang Plain wetlands by understanding and assessing the impact of these cropping changes on local natural resources (Gong et al. 2010; Niu et al. 2011; Qiu 2011; Zhang et al. 2011).

10000

Unit = 1,000 ha. The percentage indicates the portion of wetlands being converted into a specific LULC cover versus the total area of converted wetlands during a specific time interval

35 30 25 20 15 10 5 0 1940

1950

1960

1970

1980

1990

2000

2010

Year (1949-2005)

Fig. 6 Amounts of cropland cultivated in the Sanjiang Plain from 1949 to 2005. The cultivated areas are not available for some other years

occasionally (Zhang et al. 2010). Furthermore, the ecological functions of wetlands were universally recognized in the late 1990s, and thus some national ecological projects were put forward and accomplished, e.g. ‘‘Farmland Back to Wetlands’’ and ‘‘Construction of the Ecological Province in Heilongjiang’’ (Wang et al. 2006; Zhang et al. 2010). During this period, several national nature reserves were established (Wang et al. 2006; Qiu 2011; Zhang et al. 2011) including the three Ramsar sites that have been listed internationally important wetlands (see Fig. 1b). The historical record provides detailed government land-management strategies on natural resources of the Sanjiang Plain (He 2000; Liu and Ma 2002). Both household farmers and government owned ranches were influenced by as far as how to manage their croplands. Figure 7 shows that there was little paddy field before 1979 (no data available for paddy fields from HPSY before 1979), especially in government-owned ranches. Figure 7 also shows that both dry cropland and paddy field increased greatly for household farmers, but the total cropland area changed little for government-owned ranches, for which most paddy

123

300

L-Dry cropland R-Dry cropland

L-Paddy field R-Paddy field

180 140

200

120 100

150

80

100

60 40

0 1976

20 1981

1986

1991

1996

2001

0 2006

Year (1979-2005)

Fig. 7 Areal changes of dry cropland and paddy field in the Sanjiang Plain from 1979 to 2005. L local household cropland, R governmentowned ranches

field was converted from dry cropland. The paddy field area increased greatly to approximately 911,700 ha in 1997 from 520,600 ha in 1994. It reached to approximately 1,215,200 ha in 2000, and then kept increasing to approximately 1,514,100 ha in 2005. Compared with paddy field, the increase in the combined area of dry cropland was small, increasing from approximate 3,047,600 ha in 1980 to 3,728,300 ha in 1997, and increased slightly to approximately 3,814,600 ha in 2005. The spatial distribution of paddy field is presented in Fig. 8. It can be observed that paddy field has increased dramatically since 1986. With the new food-security project launched in 2009 in Heilongjiang Province, more paddy fields will be converted due to the high yield of rice growing (Zhu and Yan 2011; Yu 2011). Overuse of fertilizers and pesticides, combined with the overuse of groundwater, have caused degradation of surface water and Fig. 8 Paddy field maps of the Sanjiang Plain in 1986 (a) and 2005 (b), and the two crosses show the location for groundwater-monitoring wells in Tongjiang County and Baoqing County, respectively

123

groundwater (Wo et al. 2009; Qiu 2010a, b; Gong et al. 2011; Yu 2011; Zhu and Yan 2011; Song et al. 2012).

160

250

50

10000

200

350

Ranch cropland area (ha)

Local cropland area (ha)

10000

Environmental Management

Demographic Development Both demographic and socioeconomic considerations play an important role in natural-resource exploitation and dynamics (Guyer 1997; Rao and Rekha 2001; Li and Wei 2010; Bonilla-Moheno et al. 2012). A high correlation between LULC change and an increase in anthropogenic activities was observed in the region (Fig. 9). Approximately 1.39 million residents lived in the plain in 1949 (HPSY 1990) with an average population density of 13 person/km2, and it increased to 8.71 million in 2005 with an average population density of 79 person/km2 (HPSY 2006). The analysis above shows that wetlands were lost to cropland (see Fig. S2 for detail). Figure 9 shows that the farming population and cropland area in the plain kept increasing during 1949–2005 (HPSY 1990, 2000, 2006), whereas government-owned ranches have been stabilized since 1986 after agricultural modernization. A significant correlation between cropland area and farming population was evident for both household-owned (R2 = 0.93, P \ 0.001) and government-owned ranch (R2 = 0.96, P \ 0.001) farming systems (Fig. 10), and a coefficient of determination 0.93 is obtained when these two data sets are combined. From 1992, the local household farming population and cropland increased, whereas the population and cropland area remained stable in government-owned ranches. The correlation of farming population with cropland area is high in our study’s temporal

Environmental Management

500

Farming population

400

350 300 250 200

300

150

200

100 100

10000

400

Local farmer Ranch farmer Local cropland Ranch cropland

50

0 1949

0 1959

1969

1979

1989

1999

Year

Fig. 9 Changes in the farming population and cropland area in the Sanjiang Plain since the foundation of the People’s Republic of China. Note that data are unavailable for some specific years

Cropland (in thousand ha)

4000

(a)

3500 3000 2500 2000 1500

y = 0.4734x + 550.85 R2 = 0.93 n = 43 p < 0.001

1000

500 0 0

1000

2000

3000

4000

5000

6000

Local farmers (in thousand) 1600

(b)

Cropland (1000 ha)

1400 1200 1000 800 600

y = 1.3099x + 126.41 R2 = 0.96 n = 35 p < 0.001

400 200

the study’s temporal extent (Feng et al. 2005; Liu et al. 2005; Qiu 2011; Yu 2011). Environmental-Impact Analysis

Cropland area (ha)

10000

600

Ecological Impacts The dramatic loss of wetlands in the Sanjiang Plain has caused serious ecological problems (Wang et al. 2006; Gong et al. 2010; Zhang et al. 2010). Large-scale reclamation has resulted in damage to the ecological environment such as land degradation, nonpoint source pollution, decreased biodiversity, and regional climate change (Lambin and Geist 2006; Zhang et al. 2007, 2010; Zhu and Yan 2011). For example, meadow soil, one of the important soil types in this region (approximately 37 %), has a substantial degradation after cultivation (Table 6). All soil nutrient levels decreased substantially after conversion to agriculture, especially during the first 5 years. Other soil types showed similar trends to some higher or lower degree, which implies a huge amount of carbon being emitted from the cropland in the region (Zhang et al. 2007; Mandal et al. 2012). In recent years, especially since the late 1990s, the government has been fully aware of the seriousness of environmental problems resulting from damage to natural ecosystems and has taken various actions to cure the severely disturbed environment (Zhang et al. 2011) as other countries did (Dahl 1990; Gerakis and Kalburtji 1998; Brinson and Malvarez 2002; Gong et al. 2010; Qiu 2010a, b). With more and more natural reserves being established and enforced protection management occurring in recent years, people have begun to realize the importance of environmental protection (Gong et al. 2010; Wang et al. 2011; Qiu 2010a, 2011). Some of the habitat became more suitable for Ciconia boyciana inhabitation; the number of this species began to increase in recent years, and this improvement has been observed for other important waterfowl and animals (Cheng et al. 2004; Wang et al. 2006; Qiu 2011). However, the wetland-protection situation in China is still not optimistic (Niu et al. 2011; Qiu 2011; Zhang et al. 2011; also see Fig. S1 and Table S1).

0 0

200

400

600

800

1000

Ranch farmers (in thousand)

Fig. 10 The relationship between the farming population and cropland area in the Sanjiang Plain: a local (household)-owned cropland and farming population and b government-owned cropland (ranches) and farming population. Each circle represents 1 year during 1954–2005

extent; however, with limited natural resources, less cropland can be developed, so this correlation is unlikely to hold true in the future. Still, it suggests that a population increase is the dominant reason for cropland expansion in

Hydrological Impacts Agriculture is the largest consumer of water resources worldwide (nearly 85 % of total human consumption). Although as not severe as that which happened in North China Plain (Yu 2011; Gong et al. 2011), the Sanjiang Plain has significant groundwater depletion because of rice-growing. Figure 11 shows that the groundwater level significantly decreased in pumping wells in Tongjiang and Baoqing County (see location in Fig. 8b). Groundwater levels usually decrease rapidly from May, reach to valley in mid-July, and then

123

Environmental Management Table 6 Nutrient changes over different cultivation years for meadow soil in the Sanjiang Plain Years Before cultivation (cm) 5 Years of cultivation (cm) 15 Years of cultivation (cm) 25 Years of cultivation (cm)

Layers (cm)

OM (g/kg)

TN (g/kg)

TP (g/kg)

TK (g/kg)

AN (mg/kg)

AP (mg/kg)

AK (mg/kg)

0–25

98.97

6.05

12.73

58.58

8.48

0.12

2.19

\25

8.14

0.94

10.49

68.47

1.18

0.18

1.21

0–26

36.47

3.03

8.76

71.32

3.24

0.11

2.41

\26

3.73

0.88

10.16

71.78

1.01

0.05

1.12

0–28

34.05

2.82

10.46

80.81

2.94

0.07

1.15

[28

4.72

0.76

5.74

92.36

0.84

0.04

0.72

0–27

21.26

1.44

8.70

68.02

3.15

0.07

0.66

\27

8.44

0.74

8.90

69.45

1.51

0.03

0.61

Regional Climate Change LULC change affects the global climate system through biogeophysical, biogeochemical, and energy-exchange

123

52

80 Baoqing ( ): y = -0.3271x + 702.75 R² = 0.66, p < 0.001

75

50

48

70

65

60 1993

46

Tongjiang ( ): y = -0.4416x + 950.31 R² = 0.87, p < 0.001

44 1997

2001

2005

Ground water level (a.s.l, m) for Region 2

gradually increase in November, which is consistent with riceirrigation activities. It can be observed that the groundwater level has decreased by approximately 5 m in the past 10 years in Tongjiang County and approximately 4 m in Baoqing County with an annual decrease rate of 0.44 and 0.33 m/year, respectively. It has been reported that there were approximately 11.26 9 104 pumping wells in the plain for 57.7 9 104 ha irrigated paddy rice in 1986, and the number of pumping wells has increased to 91.55 9 104 for 151.4 9 104 ha irrigated paddy rice in 2005 (Wo et al. 2009; Han et al. 2010). The harvested groundwater was 3.1 9 108 m3 and 17.6 9 108, respectively, in 1986 and 2005. Similarly, the establishment of a huge drainage system during wetland conversion to agriculture also affects wetland ecosystem health and composition (Huang et al. 2010a). Wetlands that are completely or partially supported by groundwater are likely affected by these changes in both surface and groundwater hydrological conditions (Wang et al. 2011). Some wetlands were degraded due to the groundwater or surface water change (Ralph et al. 1998; Uluocha and Okeke 2004; Dietrich et al. 2011). A water-level decline may also affect wetland vegetation and animals’ living habitat. It has been reported that wetland plants in Sanjiang Plain are degraded due to a decreased water table (Zhang et al. 2010; Huang et al. 2010a), and the habitat for some waterfowl had been reported to be affected (Gerakis and Kalburtji 1998). Moreover, contaminants introduced through agricultural practice (fertilizer and pesticide) may infiltrate the groundwater, and this will take long time to be remediated due to the contaminants’ long residence time (Zhu and Yan 2011). Farming people will pay more for groundwater harvesting due to decreased water tables (Liu and Ma 2002; Wo et al. 2009), which could more likely cause land subsidence in the long run (Qi et al. 2009).

Ground water level (a.s.l, m) for Region 1

OM organic matter, TN total nitrogen, TP total phosphorus, TK total potassium, AN available nitrogen, AP available phosphorus, AK available potassium

2009

Year (1994-2009)

Fig. 11 Changes in groundwater table (m a.s.l.) in Tongjiang (average from six wells [hollow diamond]) and Baoqing County (average from four wells [hollow circle]) located in the Sanjiang Plain. These changes were caused by the water use for rice-growing; for each year the minimum and maximum values indicate the groundwater fluctuation. See the pumping well locations in Fig. 8

processes (Foley et al. 2005; IPCC 2007). LULC changes in the Sanjiang Plain, especially wetland reclamation, in which water was drained for cropland development, alter ecosystems and release carbon dioxide (CO2), methane, and carbon monoxide to the atmosphere (IPCC 2001, 2007; Song et al. 2009; Huang et al. 2010b). Wetlands, in particular, peat land and swamp, are important carbon stores. When these wetlands are drained for agricultural purposes or degraded, CO2 and other greenhouse gases are released into the atmosphere in large quantities (Bartlett and Harris 1993; Baker and Maltby 1995; Ding et al. 2004; Song et al. 2009). In general, greenhouse gas emissions from undisturbed swamp or bogs in boreal or temperate region are estimated to range between 0.1 and 0.32 t C ha-1 year-1. However, the emission can reach 1–19 t C ha-1 year-1 when wetlands are drained and converted to agricultural land. Further work is still needed to further clarify the role of LULC change on changing regional climate, especially

Environmental Management 6

Annual temperature ( )

(a) 5 4 3 2 1

y = 0.0342 x - 64.303 R2 = 0.4716, p < 0.01

0 1950

1960

1970

1980

1990

2000

2010

Year

Annual precipitation (mm)

850

(b)

750 650 550 450 350

y = = -1.289 x + 3099.4 R2 = 0.044, p = 0.177

250 150 1950

1960

1970

1980

1990

2000

2010

Year

Fig. 12 a Averaged temperature and b precipitation of the Sanjiang Plain in different years from 1955 to 2005

wetland conversion to other LULC types (Song et al. 2009; Huang et al. 2010b). Figure 12 shows the monthly rainfall and temperature trend with averaged data from 23 weather stations distributed in the Sanjiang Plain. As shown in Fig. 12a, an obvious temperature increase was observed during the past 50 years with an average temperature change rate of 0.34 °C/decade. The increase is approximately 0.23 °C/ decade in Northeast China and approximately 0.10 °C/ decade when taking the entire country into consideration. It can be seen from Fig. 12b that the rainfall decreased gradually from the 1950s with the average rate of decline being 12.9 mm/decade, but the trend is insignificant (P = 0.177). A similar trend has been observed in Northeast China (15.7 mm/decade).

Conclusion This study investigated the dynamics of wetlands and their conversion into other LULC categories in the Sanjiang Plain, China. Wetlands accounted for 20 % of the Sanjiang Plain in 1976 and 9 % in 2005. The result from this study

also indicated that most of wetland loss was the result of agricultural cultivation, and only a small part was attributed to the conversion to grassland and forest. Increased human activities are the main cause of wetland losses in the Sanjiang Plain. Although the rate of wetland loss decreased during the later time intervals, the decrease did not stop, suggesting that the existing wetland-protection measures in the Sanjiang Plain should be reinforced further. Due to the growing recognition of the importance of wetlands in environmental and ecological functions, the rate of degradation of the wetlands in the Sanjiang Plain has decreased in recent years. This decrease in the rate of wetland degradation is ascribed to government legislations and has improved some natural habitats and the number of fauna in the last studied time interval. Future vigilance and action by both individuals and governments are required to protect wetland habitats in the Sanjiang Plain. Strategies balancing the agricultural production and environmental protection in a more practical manner through institutional arrangement should be introduced to allow local people to participate in the implementation of these strategies for wetland protection. It also should be highlighted that to tackle wetland protection issues in China, various government agencies must effectively coordinate to reinforce laws and regulations for wetland sustainability at both local and national scales. Acknowledgments The research was jointly supported by the National Basic Research Program of China (Grant No. 2012CB956103), the 100 Talents Program of the Chinese Academy of Sciences granted to Kaishan Song, and the National Natural Science Foundation of China (Grant No. 41171293). The authors are grateful to those who contributed to the generation of the 1986 and 1995 LULC data sets and to Huanjun Liu, Hongtao Duan, Ming Chen, and Jingping Xu for their efforts in generation of the 1976 and 2005 LULC data sets. The authors are indebted to Lin Li from Indiana University-Purdue University, Indianapolis, for valuable comments and improving the English language. Special thanks go to the handling editor and three anonymous reviewers for their helpful comments that improved this manuscript.

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