Using Spatial Pattern to Quantify Relationship Between Samples, Surroundings, and Populations

The need for accurate carbon budgeting, climate change modelling, and sustainable resource management has lead to an increase in the number of large area forest monitoring programs. Large area forest monitoring programs often utilize field and remotely sensed data sources. Sampling, via field or photo plots, enables the collection of data with the desired level of categorical detail in a timely and efficient manner. When sampling, the aim is to collect representative detailed data enabling the statistical reporting upon the characteristics of larger areas. As a consequence, approaches for investigating how well sample data represent larger areas (i.e., the sample neighbourhood and the population) are desired. Presented in this communication is a quantitative approach for assessing the nature of sampled areas in relation to surrounding areas and the overall population of interest. Classified Landsat data is converted to forest/non-forest categories to provide a consistent and uniform data set over a 130,000 km² study region in central British Columbia, Canada. From this larger study area 322 2 × 2 km photo plots on a 20 × 20 km systematic grid are populated with composition and configuration information for comparison to non-sampled areas. Results indicate that typically, within the study area, the spatial pattern of forest within a photo plot is representative of the forest patterns found within primary and secondary neighbourhoods and over the entire population of the study. These methods have implications for understanding the nature of data used in monitoring programs worldwide. The ability to audit photo and field plot information promotes an increased understanding of the results developed from sampling and provides tools identifying locations of possible bias.     

Detecting Temporal Change in Watershed Nutrient Yields

Meta-analyses reveal that nutrient yields tend to be higher for watersheds dominated by anthropogenic uses (e.g., urban, agriculture) and lower for watersheds dominated by natural vegetation. One implication of this pattern is that loss of natural vegetation will produce increases in watershed nutrient yields. Yet, the same meta-analyses also reveal that, absent land-cover change, watershed nutrient yields vary from one year to the next due to many exogenous factors. The interacting effects of land cover and exogenous factors suggest nutrient yields should be treated as distributions, and the effect of land-cover change should be examined by looking for significant changes in the distributions. We compiled nutrient yield distributions from published data. The published data included watersheds with homogeneous land cover that typically reported two or more years of annual nutrient yields for the same watershed. These data were used to construct statistical models, and the models were used to estimate changes in the nutrient yield distributions as a result of land-cover change. Land-cover changes were derived from the National Land Cover Database (NLCD). Total nitrogen (TN) yield distributions increased significantly for 35 of 1550 watersheds and decreased significantly for 51. Total phosphorus (TP) yield distributions increased significantly for 142 watersheds and decreased significantly for 17. The amount of land-cover change required to produce significant shifts in nutrient yield distributions was not constant. Small land-cover changes led to significant shifts in nutrient yield distributions when watersheds were dominated by natural vegetation, whereas much larger land-cover changes were needed to produce significant shifts when watersheds were dominated by urban or agriculture. We discuss our results in the context of the Clean Water Act.     

Assessment of Soil Cover Degradation and Desertification in Northern Lowland Dagestan

New principles of the assessment of soil cover degradation and desertification, the scale and intensity of destructive processes manifestation are determined.     

洞庭湖区近50年土地利用/覆盖的变化研究

利用1978，1989，1998年的Landsat卫星遥感影像资料及20世纪50年代航测的地形图，研究了洞庭湖区近50年土地利用／覆盖及其景观结构的变化，土地利用／覆盖类型分为水体，湿地，农田，林地和建成区五类，各时期遥感影像的总体分类精度都在80％以上，运用ArcInfo和ArcView GIS软件，将不同时期的土地利用／覆盖格局在空间上清晰地显示出来，通过叠加4个不同时期的影像分类图，计算出各种土地利用／覆盖类型转变为其他土地利用／覆盖类型的比例，洞庭湖区50年来水体面积不断减少，减少量为1460km^2，其中1955年到1978年水面面积缩小了970。57km^2，分别为1978年到1989年和1989年到1998年缩小面积的2．23倍和1805倍，湿地面积逐渐增加，1998年湿地面积分别为1955，1978和1989年的1．46，1．41和1．09倍，农田的面积百分比从1955年的54．70％增加到1978年62．15％，又逐渐降低到1989年的51．88％和1998年的48．17％，林地的面积1978年比1955年减少了17％,，1989年比1978年增加了57％，1998年比1989年增加了11％，建成区的变化表明近50年来湖区城市化的进程，洞庭湖区土地利用／覆盖及其景观结构的变化是社会经济和自然因素综合作用的结果。     

Baseline assessment for environmental services payments from satellite imagery: a case study from Costa Rica and Mexico

In this study we evaluate the accuracy of four global and regional forest cover assessments (MODIS, IGBP, GLC2000, PROARCA) as tools for baseline estimation. We conduct this research at the national scale for Costa Rica and for two tropical dry forest study sites in Costa Rica (Santa Rosa) and Mexico (Chamela-Cuixmala). We found that at the national level, the total forest cover accuracy of the four land cover maps was inflated due to an overestimation of forest in areas with an evergreen canopy. However, the four maps greatly underestimated the extent of the deciduous forest (dry forest); an ecosystem that faces high deforestation pressure and poses complications to the mapping of its extent from remotely sensed data. For the tropical dry forest sites, all maps have low forest cover accuracies (mean for Santa Rosa: 27%; mean for Chamela-Cuixmala: 56%). This has implications for policy implementation.     

Urban development and landscape change in the Yangtze River Delta region in China

The impact of large-scale urban development on land resources has long been debated by urban planners and designers. This study investigated the extent to which different urban characteristics are associated with land-cover change. The Yangtze River Delta region in China, forming one of the largest sprawling urban landscapes among the regions around the world, was chosen for the study area. Spatial analysis and multiple regression methods were applied to empirically investigate the pattern of resource sites lost to urban development in the area between the 1950s and 2017. The results showed that contrary to the widespread notion that large-sized cities are predominantly responsible for a region’s environmental degradation, city size was not a significant factor in determining the rate of resource loss. Large-sized cities gained their populations with far lesser impacts on land than small-sized cities and towns if normalized to the same number of populations. One explanation for the diminishing effect of city size on land-cover change relates to the degree of spatial dispersion of urban development and local differences in social valuation of diversified lands by cities.     

人工园林大面积种植区土地利用/覆被变化对生态系统服务价值影响

近10a来由于经济利益的驱动,橡胶、茶园、咖啡和桉树等人工园林在云南省西南部西盟县大规模种植,使土地利用结构和布局发生了较大变化,影响了种植区的生态系统服务价值。以西盟县为研究对象,基于2000年、2005年和2010年的遥感影像解译的土地利用/覆被数据,参照"中国生态系统单位面积生态服务价值当量",修订了西盟县生态系统单位面积服务价值,结合敏感度分析,探讨了土地利用/覆被变化及其对生态系统服务价值的影响。结果表明:(1)2000~2010年西盟县的耕地、园地、水域和乡镇用地面积增加,林地和草地面积减少,西南部的土地利用/覆盖类型相互转化主要表现在林地和耕地转化为园地,而东北部表现在林地转化为耕地;(2)从时间上看,生态系统服务价值呈减少趋势,10 a间净减少106.29×106元,林地的生态系统服务价值始终最高;(3)研究期内,只有食物生产服务有价值量的增加,其余生态系统服务的价值量均为不同程度的减少;(4)从空间上看,西盟县生态系统服务价值东北部和东南部高,西部、中部和东部低。力所乡生态系统服务价值有小幅度增加,其余乡镇均呈减少趋势。西盟县以经济利益为目的的发展模式给生态系统服务和可持续发展带来巨大压力,在一定程度上使区域整体生态效应下降。因此,西盟县的发展应该在保证生态系统稳定的前提下,适当发展园地,同时优化土地利用结构,在生态效益和经济利益之间,找到双赢的平衡点。     

Viable contribution of Tibetan sacred mountains in southwestern China to forest conservation

The Tibetan sacred mountains (TSMs) cover a large area and may represent a landscape‐scale conservation opportunity. We compared the conservation value of forests in these mountains with the conservation value of government‐established nature reserves and unmanaged open‐access areas in Danba County, southwestern China. We used Landsat satellite images to map forest cover and to estimate forest loss in 1974–1989, 1989–1999, and 1999–2013. The TSMs (n = 41) and nature reserves (n = 4) accounted for 21.6% and 29.7% of the county's land area, respectively. Remaining land was open‐access areas (i.e., areas without any restrictions on resource use) (56.2%) and farmlands (2.2%). Within the elevation range suitable for forests, forest cover did not differ significantly between nature reserves (58.8%) and open‐access areas (58.4%), but was significantly higher in TSMs (65.5%) after controlling for environmental factors such as aspect, slope, and elevation. The TSMs of great cultural importance had higher forest cover, but patrols by monastery staff were not necessarily associated with increased forest cover. The annual deforestation rate in nonsacred areas almost tripled in 1989–1999 (111.4 ha/year) relative to 1974–1989 (40.4 ha/year), whereas the rate in TSMs decreased in the later period (19.7 ha/year vs. 17.2 ha/year). The reduced forest loss in TSMs in 1989–1999 was possibly due to the renaissance of TSM worship and strengthened management by the local Buddhist community since late 1980s. The annual deforestation rate in Danba decreased dramatically to 4.4 ha/year in 1999–2013, which coincided with the implementation of a national ban on logging in 1998. As the only form of protected area across the Tibetan region during much of its history, TSMs have positively contributed to conserving forest at a landscape scale. Conservation of TSM forests largely relied on the strength of local religious institutions. Integrating community‐based conservation of TSMs within the government conservation network would benefit the conservation of the Tibetan region.     

Decline of traditional rice farming constrains the recovery of the endangered Asian crested ibis (Nipponia nippon)

Traditional agriculture benefits a rich diversity of plants and animals. The winter-flooded rice fields in the Qinling Mountains, China, are the last refuge for the endangered Asian crested ibis (Nipponia nippon), and intensive efforts have been made to protect this anthropogenic habitat. Analyses of multi-temporal satellite data indicate that winter-flooded rice fields have been continuously reduced across the current range of crested ibis during the past two decades. The rate of loss of these fields in the core-protected areas has unexpectedly increased to a higher level than that in non-protected areas in the past decade. The best fit (R² = 0.87) numerical response model of the crested ibis population shows that a reduction of winter-flooded rice fields decreases population growth and predicts that the population growth will be constrained by the decline of traditional winter-flooded rice fields in the coming decades. Our findings suggest that the decline of traditional rice farming is likely to continue to pose a threat to the long-term survival and recovery of the crested ibis population in China.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0649-5) contains supplementary material, which is available to authorized users.     

A regression tree-based method for integrating land-cover and land-use data collected at multiple scales

As data sets of multiple types and scales proliferate, it will be increasingly important to be able to flexibly combine them in ways that retain relevant information. A case in point is Amazonia, a large, data-poor region where most whole-basin data sets are limited to understanding land cover interpreted through a variety of remote sensing techniques and sensors. A growing body of work, however, indicates that the future state of much of Amazonia depends on the land use to which converted areas are put, but land use in the tropics is difficult to assess from remotely sensed data alone. An earlier paper developed new snapshots of agricultural land use in this region using a statistical fusion of satellite data and agricultural census data, an underutilized ancillary data source available across Amazonia. The creation of these land-use maps, which have the spatial detail of a satellite image and the attribute information of an agricultural census, required the development of a new statistical technique for merging data sets at different scales and of fundamentally different data types. Here we describe and assess this nonlinear technique, which reinterprets existing land cover classifications by determining what categories are most highly related to the polygon land-use data across the study area. Although developed for this region, the technique appears to hold broad promise for the systematic fusion of multiple data sets that are closely related but of different origins. The figures in the printed version of this article appear in black and white. Color figures are available from the author upon request.