Importance of information on tillage practices in the modelling of environmental processes and in the use of environmental indicators

Tillage has been and will always be integral to crop production. Tillage can result in the degradation of soil, water, and air quality. Of all farm management practices, tillage may have the greatest impact on the environment. A wide variety of tillage equipment, practices and systems are available to farmers, providing opportunities to enhance environmental performance. These opportunities have made tillage a popular focus of environmental policies and programs such as environmental indicators for agriculture. This paper provides a very brief examination of the role of tillage in crop production, its effect on biophysical processes and, therefore, its impact on the environment. Models of biophysical processes are briefly examined to demonstrate the importance of tillage relative to other farm management practices and to demonstrate the detail of tillage data that these models can demand. The focus of this paper is an examination of the use of information on tillage in Canada's agri-environmental indicators initiative, National Agri-environmental Health Analysis and Reporting Program (NAHARP). Information on tillage is required for several of the indicators in NAHARP. The type of data used, its source, and its quality are discussed. Recommendations regarding the collection of tillage data and use of tillage information are presented.     

因子回归和交互联合探索区域植被覆盖度的影响因素——以三江源地区为例

利用SPOT VEGETATION数据获取的归一化植被指数（NDVI）,分析三江源地区植被覆盖度（FVC）的空间异质性,围绕自然和人类活动因素,基于因子回归与交互作用联合探索自然因素和人为因素对三江源地区植被覆盖的影响.结果表明：（1）三江源地区植被覆盖度整体呈现明显的空间异质性;（2）总体上FVC空间分布的影响因素表现为自然环境因素>人类活动因素;（3）降水是影响三江源地区FVC的主要驱动因子,解释力达0.777;（4）因子交互发现：驱动解释系统呈现双因子增强,说明从系统的角度来看不存在独立起作用的因子,年降水量与其他因子的交互作用最强;（5）降水梯度影响了三江源地区FVC空间异质性的解释程度.随着降水增加,因子解释力趋稳,在降水量较多的三江源东部地区,FVC趋向于更易受高程和气温的影响;（6）数据结果亦验证了因子独立的全局最优筛选仅仅是模拟因变量特征的最优函数,其解释效果与因变量的驱动解释不能完全等同.     

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。     

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.     

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.     

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.     

Promoting late-fall establishment of tall fescue with artificial soil covers to minimise soil erosion

Frequently, turfgrass seedings have been sown in the late fall, which usually results in a poor vegetative stand and the possibility of soil erosion the following spring. This study evaluates the effects of a spun-bonded polyester soil cover placed over a late-fall seeding on subsequent seedling growth and overwintering. Clemfine, Mustang, Rebel, and Rebel II cultivars of tall fescue (Festuca arundinacea Schreb.) were sown on a silt loam soil in late fall (on 17 October in 1989 and 19 October in 1990) and allowed to grow with and without a soil cover until June. In the spring the temperature under the soil cover was greater than 2°C warmer than the uncovered soil from mid-April through May. Over the winter, leaf and root weights showed no detrimental effects from being under the cover. Individual cultivars grown under the cover produced 2 to 11 times greater leaf yields and 38 to 270% better stand establishment than those sown on the exposed soil. However, plant winter injury was observed under the soil cover in small soil depressions which accumulated water originating from thawing. All cultivars had similar amounts of growth under the cover. However, leaf yields for Rebel were 30-55% less than the other cultivars when grown under the cover and this was probably related to a low seed germination rate. The covers also promoted weed growth, which comprised from 34–65% of total leaf weights and was found to be negatively correlated (r = –0.66) to the yields of the sown grass. The soil cover was found to be beneficial to improving the success of seedling establishment of late seedings of tall fescue in cold areas.     

An architectural model of spring wheat: Evaluation of the effects of population density and shading on model parameterization and performance

ADELwheat is an architectural model that describes development of wheat in 3D. This paper analyzes the robustness of the parameterization of ADELwheat for spring wheat cultivars in relation to plant population density and shading. The model was evaluated using data from two spring wheat experiments with three plant population densities and two light regimes. Model validation was done at two levels of aggregation: (a) by comparing parameterization functions used as well as parameter values to the data (leaf and tiller appearance, leaf number, blade dimensions, sheath length, internode length) and (b) by comparing ground cover (GC) and leaf area index (LAI) of simulated virtual wheat plots with GC and LAI calculated from data. A sensitivity analysis was performed by modulating parameters defining leaf blade dimensions and leaf or tiller appearance rate.In contrast to population density, shading generally increased phyllochron and delayed tiller appearance. Both at the level of the organ and at the level of the canopy the model performed satisfactorily. Parameterization functions in the model that had been established previously applied to independent data for different conditions; GC and LAI were simulated adequately at three population densities. Sensitivity analysis revealed that calibration of phyllochron and blade area needs to be accurate to prevent disproportional deviations in output.The robustness of the model parameterization and the simulation performance confirmed that the model is a complete architectural model for aboveground development of spring wheat. It can be used in studies that require simulation of spring wheat structure, such as studies on plant–insect interaction, remote sensing, and light interception.     

A Bayesian network approach to modelling land-use decisions under environmental policy incentives in the Brazilian Amazon

ABSTRACT

Deforestation driven by agricultural expansion is a major threat to the biodiversity of the Amazon Basin. Modelling how deforestation responds to environmental policy implementation has thus become a policy relevant scientific undertaking. However, empirical parameterization of land-use/cover change (LUCC) models is challenging due to the high complexity and uncertainty of land-use decisions. Bayesian Network (BN) modelling provides an effective framework to integrate various data sources including expert knowledge. In this study, we integrate remote sensing products with data from farm-household surveys and a decision game to model LUCC at the BR-163, in Brazil. Our ‘business as usual’ scenario indicates cumulative forest cover loss in the study region of 8,000 km² between 2014 and 2030, whereas ‘intensified law-enforcement’ would reduce cumulative deforestation to 1,600 km² over the same time interval. Our findings underline the importance of conservation law enforcement in modulating the impact of agricultural market incentives on land cover change.