不同施肥方式下土壤氨氧化细菌的群落特征

为了研究长期定位施肥对棕壤中氨氧化细菌（ammonia-oxidizing bacteria,AOB）种群结构多样性和垂直分布特征的影响,本研究采用化学分析、荧光定量PCR（qPCR）和变性梯度凝胶电泳（PCR-DGGE）技术,针对沈阳农业大学试验区不同施肥方式（不施肥、低量无机氮肥、高量无机氮肥、无机氮肥与有机肥配施）下不同土壤深度（0~20 cm、20~40 cm、40~60 cm）的土壤理化性质、AOB丰度及种群多样性进行分析,比较不同施肥方式对土壤AOB种群的影响。结果显示,与不施肥相比,施肥会降低土壤pH,增加土壤铵态氮（70.5%~939.21%）和硝态氮（253.20%~625.48%）含量。随土壤深度增加,土壤pH升高,铵态氮和硝态氮含量除低量无机氮肥处理外,多呈降低趋势。土壤增施氮肥可提高AOB丰度,降低总细菌丰度。其中,0~20 cm土层中AOB丰度较高,且高量无机氮肥处理的AOB数量最高,为9.65×10⁵拷贝数·g^-1（干土）。DGGE图谱分析显示,不同处理下,AOB群落结构多样性指数存在明显差异（P<0.05）,各多样性指数均在表层（0~20 cm）最高,增施氮肥则显著降低AOB的多样性。聚类分析表明,4个施肥处理中,高量无机氮肥处理聚为一类,其他处理则因土壤深度不同而异;3个土壤深度中,除不施肥处理外,所有施肥处理均表现为0~20 cm、20~40 cm土层发生聚类,40~60 cm则明显与其他两层分开。冗余梯度分析（RDA）显示,硝态氮（P=0.027）是造成影响AOB群落结构差异的主要原因。上述研究结果表明,长期定位施肥土壤AOB的数量和群落结构多样性受施肥方式显著影响,并表现出明显的垂直分布特征。与无机氮肥相比,有机无机配施处理有助于改善土壤pH,维持不同土壤深度下AOB群落结构多样性。     

A simple biomonitor for measuring ammonia deposition in rural areas

Summary Knowledge of the contribution of NH₃ to the total deposition of N in rural areas is sparse, because the determination of NH₃ deposition is costly and labour-intensive. A simple biomonitor consisting of barley plants grown in pots with an inert growth medium is therefore proposed for estimating total N deposition, including NH₃. The rise in total N of the plant-soil system reflects the deposition. The biomonitor was tested near a dairy farm. Different N contents in the green biomass reflected differences in deposition, and the deposition correlated very well with NH₃ levels in the area and in two background stations. The biomonitors were placed above the crop, the measurements thus representing total N at the edge of a plant community. In 1 month the deposition in the NH₃ plume was 8 kg N ha^–1.     

Effects of Temperature and Soil Type on Ammonia Volatilization from Slow-Release Nitrogen Fertilizers

Ammonia (NH₃) volatilization is the major pathway for mineral nitrogen (N) loss from N sources applied to soils. The information on NH₃ volatilization from slow-release N fertilizers is limited. Ammonia volatilization, over a 78-d period, from four slow-release N fertilizers with different proportions of urea and urea polymer [Nitamin 30L (liquid) (L30), Nitamin RUAG 521G30 (liquid) (G30), Nitamin 42G (granular) (N42), and Nitroform (granular) (NF)] applied to a sandy loamy soil was evaluated. An increase in temperature from 20 to 30 °C increased cumulative NH₃ volatilization loss in the sandy soil by 1.4-, 1.7-, and 1.8-fold for N42, L30, and G30, respectively. Increasing the proportion of urea in the slow-release fertilizer increased NH₃ volatilization loss. At 30 °C, the cumulative NH₃ volatilization over 78 d from a sandy soil accounted for 45.6%, 43.9%, 22.4%, and <1% of total N applied as N42, L30, G30, and NF, respectively. The corresponding losses in a loamy soil were 9.2%, 3.1%, and 1.7%. There was a significantly positive correlation between NH₃ volatilization rate and concentration of NH₄-N released from all fertilizers, except for NF (n = 132; r = 0.359, P = 0.017 for N42; r = 0.410, P = 0.006 for L30; and r = 0.377, P < 0.012 for G30). Lower cumulative NH₃ volatilization from a loamy soil as compared to that from a sandy soil appeared to be related to rapid nitrification of NH₄-N in the former soil than that in the latter soil. These results indicate the composition of slow-release fertilizer, soil temperature, and soil type are main factors to dominate NH₃ volatilization from slow- release fertilizers.     

秸秆还田对关中地区麦玉复种体系土壤氨排放的影响

农业氨减排是雾霾治理最经济有效的方法,而农田肥料施用造成的氨排放是农业氨排放的重要部分。本研究旨在探讨冬小麦-夏玉米复种体系下土壤氨排放对秸秆还田的响应,为减少农业氨排放和控制雾霾提供理论依据。本试验于2018年6月—2019年6月在陕西关中杨凌地区,对土壤氨排放、0～40 cm土壤无机氮以及产量进行了测定分析。试验采用双因素裂区设计,主区为秸秆还田方式,设不还田(S0)、半量还田(S0.5)和全量还田(S1)3个水平;副区为施肥,设不施肥(F0)、减量施肥(F0.8)、常规施肥(F1)3个水平。结果表明:秸秆还田与施肥及两者互作对夏玉米季土壤氨累积排放量(C)有显著影响。秸秆还田对冬小麦季土壤氨累积排放量无显著影响。整个麦玉复种体系的氨累积排放量为1.31～19.26kg·hm~(-2),占施肥量的2.17%～4.69%,各处理之间表现为:S0F1S0.5F1S1F1S0F0.8S0.5F0.8S1F0.8S1F0S0.5F0S0F0。在不施肥情况下,秸秆还田能增加土壤氨累积排放量,但秸秆还田配施氮肥较不还田处理显著减少土壤氨累积排放量和氨损失率,秸秆全量还田和半量还田之间的氨排放无明显差异。其中S1F0.8和S0.5F0.8处理在整个复种体系中减排效果最为显著,分别较S0F0.8处理(11.62 kg·hm~(-2))减排38.64%和37.35%。相比于只施氮肥,秸秆还田配施氮肥能显著减少土壤中无机氮,显著提高夏玉米产量6.23%～20.20%,冬小麦产量16.60%～28.17%。通过PCA分析发现,S1F0.8和S0.5F0.8处理是减排增产的最优组合。综合考虑土壤氨排放和作物产量,长期秸秆还田配减量施肥处理,能在保证作物高产的基础上减少土壤氨排放,可在关中地区实施。     

3, 4-Dimethylpyrazole phosphate reduces nitrous oxide emissions from grassland after slurry application

Abstract. A field study was conducted to assess the effect of the nitrification inhibitor 3,4-dimethylpyrazole phosphate (DMPP), applied at a rate of 1 kg ha⁻¹, on nitrous oxide (N₂O) emissions, forage production and N extraction from a grassland soil after cattle slurry applications in autumn and spring. Nitrous oxide emissions were measured daily or weekly using the closed chamber technique. DMPP efficiency after slurry application was lower in spring (16.7 °C mean soil temperature) than in autumn (11.4 °C mean soil temperature). Thus, DMPP was able to maintain soil mineral N in the ammonium form for 22 days and reduce cumulative N₂O emissions by 69% in autumn, while in spring its effect on soil mineral N lasted for 7–14 days, reducing cumulative N₂O losses by 48%. Furthermore, application of DMPP after slurry did not decrease biomass yield or N uptake.     

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

Abstract. The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km² grid scale.
We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.     

面向地表过程模拟的降雨径流模型开发与应用

降雨径流是流域地表过程的主要驱动力,是众多地表模型的基础。该文在充分考虑流域气象及下垫面等要素空间异质性的基础上,提出了一个面向地表过程模拟的、基于DEM的分布式次降雨径流模型。模型将流域离散为栅格计算单元,并按水流特性将栅格划分为坡面单元和河网单元;模型考虑了降雨、植被截流和入渗等产流过程,利用运动波分级汇流的方式进行汇流演算。模型在江西躁口水流域进行了检验和应用。结果表明：该模型模拟的流量过程精度较高;模拟的径流深度及径流搬运力的空间分布符合水文规律。模型结构简洁、参数较少,具有较好的实用价值;为土壤侵蚀及非点源污染等以流路为基础的复杂地表过程研究奠定了基础。     

土地资源配置的可拓目标规划模型及其应用初探

从不同角度生成各种决策方案,可为土地资源优化配置提供充分的信息和备选方案,也是实现土地资源优化配置的基础,但目前对如何生成决策方案这一问题却研究得较少。该文通过可拓工程与目标规划模型相结合,建立了从不同角度生成各种方案的可拓目标规划模型方法,并以山西省隰县试区为例,探讨了可拓目标规划模型的应用及其方案生成的方法。结果表明：土地资源配置的可拓目标规划模型及其规划方案生成的方法,可通过变换规划目标、约束条件、决策变量等途径来实现,该方法是从不同角度生成各种土地资源配置方案的较好方法。     

Sources and rates of nitrous oxide emissions from grazed grassland after application of N-labelled mineral fertilizer and slurry

Nitrogen (N) fertilizer application and grazing are known to induce nitrous oxide (N₂O) emissions from grassland soils. In a field study, general information on rates of N₂O emission, the effect of cattle grazing and the type (mineral fertilizer, cattle slurry) and amount of N supply on the flux of N₂O from a sandy soil were investigated. N₂O emissions from permanent grassland managed as a mixed system (two cuts followed by two grazing cycles) were monitored over 11 months during 2001-2002 in northern Germany using the closed chamber method. The field experiment consisted of four regionally relevant fertilizer combinations, i.e. two mineral N application rates (0 and 100 kg N ha⁻¹ yr⁻¹) and two slurry levels (0 and 74 kg N ha⁻¹ yr⁻¹).Mean cumulative N₂O-N loss was 3.0 kg ha⁻¹ yr⁻¹, and the cumulative ¹⁵N-labelled N₂O emissions varied from 0.03% to 0.19% of the ¹⁵N applied. ¹⁵N labelling indicated that more N₂O was emitted from mineral N than from slurry treated plots, and in all treatments the soil N pool was always clearly the major source of N₂O. Regarding the total cumulative N₂O losses, differences among treatments were not significant, which was caused by: (i) a high variance in emissions during and after cattle grazing due to the random distribution of excrements and by (ii) high N₂ fixation of white clover in the 0 kg N ha⁻¹ treatments, which resulted in similar N status of all treatments. However before grazing started, treatments showed significant differences. After cattle grazing in summer, N₂O emission rates were higher than around the time of spring fertilizer application, or in winter. Grazing resulted in N₂O flux rates up to 489 μg N₂O-N m⁻² h⁻¹ and the grazing period contributed 31-57% to the cumulative N₂O emission. During freeze-thaw cycles in winter (December-February) N₂O emission rates of up to 147 μg N₂O-N m⁻² h⁻¹ were measured, which contributed up to 26% to the annual N₂O flux. The results suggest that N fertilizer application and grazing caused only short-term increases of N₂O flux rates whereas the major share of annual N₂O emission emitted from the soil N pool. The significantly increased N₂O fluxes during freeze-thaw cycles show the importance of emission events in winter which need to be covered by measurements for obtaining reliable estimates of annual N₂O emissions.     

Synthesis of an eco-friendly nanocomposite fertilizer for common bean based on carbon nanoparticles from agricultural waste biochar

The burning of agricultural waste is a major cause of environmental pollution. In this study, we sought to prepare biochar from agricultural waste as a source material for the preparation of carbon nanoparticles (CNPs). Surface morphology, hydrodynamic particle size, and purity and crystallinity of CNPs were extensively investigated using transmission electron microscopy (TEM), zeta sizing, and X-ray diffraction (XRD) spectroscopy, respectively. The CNPs were subsequently immersed in a solution of potassium nitrate (KNO³) to prepare a CNPs/NK nanocomposite (CNPs loaded with nitrogen (N) and potassium (K)) as a nanocomposite fertilizer for common bean (Phaseolus vulgaris L.). The CNPs/NK nanocomposite was sprayed as a foliar fertilizer at 0, 10, 20, 30, and 40 mg L^-1 on common bean plants 25 d after sowing on a farm in Shebin El-Kom, El-Monifia, Egypt. The growth, yield, and quality of common bean were investigated during two successive growing seasons (2017 and 2018). The highest seed yields of 2.04 and 2.01 t ha^-1 and the highest values of growth parameters including plant height of 61.5 and 59.2 cm, number of leaves per plant of 35 and 35, number of flowers per plant of 83.3 and 82.7, and plant fresh weight of 148.7 and 152.8 g plant^-1 were obtained when using the CNPs/NK nanocomposite at a concentration of 20 mg L^-1 during the 2017 and 2018 growing seasons, respectively.     

A simple method for estimating nitrate removal from floodwaters in river marginal wetlands

Abstract. Soil cores from river marginal wetlands in the UK, France and Ireland, sampled and contained within PVC piping, were flooded with nitrate-N enriched water. Half of the cores were sterilized prior to flooding to destroy the denitrifying bacteria. The change in nitrate-N concentration in the floodwater was measured over time. It is argued that the observed nitrate depletion rates (from 0.4 to 2.3 kg/ha per day) may be identified With microbially-mediated denitrification. The results show the method to be a simple and direct procedure for the assessment of spatial variation in nitrate-sink capacity. The depth of the denitrifying layer at the soil-water interface was confirmed to be of the order of a few mm.     

A software tool for estimating the capacity of agricultural land in England and Wales for recycling organic materials (ALOWANCE)

Agricultural Land and Organic ‘Waste’: A National Capacity Estimator (ALOWANCE) is a GIS‐based tool that estimates the available agricultural landbank in England and Wales for recycling organic materials based on a number of physical and practical constraints, and legislative restrictions. It can be used to identify areas where there is a potential shortage or surplus of available agricultural land and to determine the length of time for which the agricultural landbank would continue to be available to receive organic materials. Two versions of ALOWANCE have been developed. ALOWANCE‐PLUS is a PC‐based tool that provides the full functionality of ALOWANCE to a small number of ‘expert’ users. It incorporates scenario testing capabilities, allowing the agricultural landbank capacity to be calculated interactively. ALOWANCE‐ONLINE is a web‐based version that provides information to ‘general’ users, including pre‐selected map ‘layers’ (generated from ALOWANCE‐PLUS) and a simple query tool. Results from ALOWANCE‐PLUS showed that after exclusions and after accounting for current sources of organic materials (livestock manures, biosolids, compost, paper crumble and digestate), the estimated agricultural landbank in England and Wales for the addition of ‘new’ sources of organic materials was c. 5.1 million ha. Spatial representations showed that in some parts of the country (e.g. north‐west England), the agricultural landbank was already under ‘pressure’ and transport of any future emerging sources of organic materials away from these areas may be required.     

A STELLA model for the estimation of atrazine runoff,leaching, adsorption,and degradation from an agricultural land

Background, aim, and scope  

Atrazine (2-chloro-4-ethylamino-6-isopropylamino-1,3,5-triazine) is one of the most widely used herbicides for broadleaf weed and certain annual grass controls and is popular because of its effectiveness and low cost. Losses of atrazine from agricultural lands into adjacent surface water and underlying groundwater have raised public concerns. Several computer models have been developed for atrazine runoff in watersheds. One limitation for most of these models, however, is that vast amounts of input parameters are required for simulations. These input parameters are sometimes difficult to obtain through the experimental measurements for model calibrations, validations, and applications. Therefore, a need exists to develop a simple and yet a realistic modeling tool that can be used for effectively investigating atrazine dynamics in agricultural soils. This study was designed to meet this need.     

河套灌区玉米和向日葵ET的S-I估算模型关键参数分析

农田作物蒸散的快速评估对于灌区水资源最优调配和灌溉实时管理至关重要。简化S-I模型综合考虑作物冠层温度、田间气象参数和作物特征参数,可以进行实时农田作物ET的精确估算。该文利用河套灌区解放闸灌域2015—2016年2 a田间试验观测资料,对主要农作物玉米和向日葵的S-I模型中2个特征参数分别进行了率定和验证,并分析了模型蒸散估算的相关影响因素。结果表明:1)利用S-I简化模型可以对玉米和向日葵田间进行作物日蒸散量(daily evapotranspiration,ET_d)的估算,在该地区以13:00时率定和验证结果最优。在玉米主要生育期(6—8月),利用S-I模型估算ET_d可以达到较高的精度;而在7—8月,采用模型估算向日葵地ET_d也可以达到很高的精度;2)S-I模型中特征参数值受风速、地表覆盖度、表面粗糙度等因素的影响,不同作物其值不同。13:00时玉米S-I模型中特征参数值皆为负值,而向日葵中特征参数值为1正1负,进而影响模型估算精度。叶面积指数变化对特征参数值大小的影响在玉米和向日葵田块呈相反的趋势,而风速的影响则为一致。推荐13:00时率定的参数值可以在河套灌区玉米和向日葵作物需水量估算时直接应用。     

The utility of process-based models for simulating N2O emissions from soils: A case study based on Costa Rican coffee plantations

Soil moisture and gaseous N-flux (N₂O, N₂) dynamics in Costa Rican coffee plantations were successively simulated using a mechanistic model (PASTIS) and two process-based models (NGAS and NOE). Two fertilized (250 kg N ha⁻¹ y⁻¹) coffee plantations were considered, namely a monoculture and a system shaded by the N₂ fixing legume species Inga densiflora. In situ N₂O fluxes were previously measured in these plantations. NGAS and NOE used specific microbial activities for the soils. To parameterize NGAS, we estimated N mineralization via in situ incubations and the contribution of heterotrophic soil respiration to total soil respiration. Potential denitrification rates and the proportion of denitrified N emitted as N₂O were measured in the laboratory to define the values of NOE parameters, as well as nitrification rates and related N₂O production rates for parameterizing both models. Soil moisture and both NGAS and NOE N₂O fluxes were best modelled on an hourly time step. Soil moisture dynamics were satisfactorily simulated by PASTIS. Simulated N₂O fluxes by both NGAS and NOE (3.2 and 2.1 kg N ha⁻¹ y⁻¹ for NGAS; 7.1 and 3.7 kg N ha⁻¹ y⁻¹ for NOE, for the monoculture and shaded plantations respectively) were within a factor of about 2 of the observed annual fluxes (4.3 and 5.8 kg N ha⁻¹ y⁻¹, for the monoculture and shaded plantations respectively). Statistical indicators of association and coincidence between simulated and measured values were satisfactory for both models. Nevertheless, the two models differed greatly in describing the nitrification and denitrification processes. Some of the algorithms in the model NGAS were apparently not applicable to these tropical acidic Andosols. Therefore, more detailed information about microbial processes in different agroecosystems would be needed, notably if process-oriented models were to be used for testing strategies for mitigating N₂O emissions.     

基于InVEST模型的未利用地开发前后生境质量评价——以唐县为例

生境质量评价对生物多样性保护有至关重要的作用,为探究未利用地开发对唐县生境质量的影响,本文运用InVEST模型中的Habitat Quality模块分析2000年、2007年和2016年河北省唐县未利用地开发前后的生境质量变化情况。研究表明:1)2000—2016年,未利用地开发方向主要以草地、林地和耕地为主,未利用地比例从100%(以2000年未利用地面积为基数)减少到33.70%,草地、林地和耕地比例从0分别增加到27.43%、 21.30%和10.46%。2)唐县未利用地斑块所占景观面积比逐年减少,其平均斑块面积由开发前的94.73 hm~2减少到开发后的6.15hm~2;林地、水域和草地所占景观面积比例增加。未利用地开发后均匀度指数和多样性指数都有所增加,各景观组分所占面积比例差异减小,生态系统稳定性提高。3)未利用地开发后,研究区生境质量明显提升,生境质量得分由2000年的0.09上升到2007年的0.28,2016年又上升到0.39。研究结果可以为制定合理的土地规划以及土地开发工作中的生境及生物多样性保护等提供科学依据。     

A spatial frequency/spectral indicator-driven model for estimating cultivated land quality using the gradient boosting decision tree and genetic algorithm-back propagation neural network

Cultivated land quality (CLQ) is related to national food security. Rapid and high-precision monitoring of CLQ is crucial for the sustainable development of agriculture. However, current satellite image-based evaluation methods that only consider the crop's spatial spectrum characteristics in the key growth stages cannot accurately estimate CLQ. This study proposes a new method based on time-series spectral data of crop growth to improve the accuracy of CLQ estimation. This study was conducted in the Conghua District of Guangzhou, Guangdong Province, China. The results showed that seven spectral indicators were determined as the optimal indicators based on the gradient boosting decision tree (GBDT) and variance inflation factor (VIF). And the genetic algorithm-back propagation neural network (GA-BPNN) model provided more accurate CLQ estimates than the partial least squares regression (PLSR) model, indicating a nonlinear relationship between CLQ and the indicators. In addition, the GA-BPNN model with a normalized root mean square error (NRMSE) of 9.91% demonstrates the excellent potential for mapping CLQ over large areas. The model based on the seven optimal indicators of crop phenology provided higher accuracy than the GA-BPNN model based on the normalized difference vegetation index (NDVI) indicators in the spatial domain, significantly decreasing the NRMSE of the CLQ estimates by 3.17%. This further implied that the spectral indicators in the spatial frequency domain can improve the accuracy of estimating CLQ.     

一个用于分析土地覆被变化对径流机制影响的分布式月水量平衡模型

The Miyun Reservoir is the most important water source for Beijing Municipality, the capital of China with a population of more than 12 million. In recent decades, the inflow to the reservoir has shown a decreasing trend, which has seriously threatened water use in Beijing. In order to analyze the influents of land use and cover change （LUCC） upon inflow to Miyun Reservoir, terrain and land use information from remote sensing were utilized with a revised evapotranspiration estimation formula; a water loss model under conditions of human impacts was introduced; and a distributed monthly water balance model was established and applied to the Chaobai River Basin controlled by the Miyun Reservoir. The model simulation suggested that not only the impact of land cover change on evapotranspiration, but also the extra water loss caused by human activities, such as the water and soil conservation development projects should be considered. Although these development projects were of great benefit to human and ecological protection, they could reallocate water resources in time and space, and in a sense thereby influence the stream flow.     

Characteristics of greenhouse gas emissions from rice paddy fields in South Korea under climate change scenario RCP-8.5 using the DNDC model

Understanding the greenhouse gas(GHG)emission from rice paddy fields is essential to come up with appropriate countermeasure in response to global warming.However,GHG emissions from paddy fields in South Korea are not well characterized.The objectives of this study were to estimate the carbon dioxide(CO₂)and methane(CH₄)emissions from rice paddy fields in South Korea,under the Representative Concentration Pathway 8.5(RCP-8.5)climate change scenario using the DNDC(i.e.,DeNitrification-DeComposition)model at 1-km²resolution.The performance of the model was verified with field data collected using a closed chamber,which supports the application of the model to South Korea.Both the model predictions and field measurements showed that most(>95%)GHG emissions occur in the cropping period,between April and October.As a baseline(assuming no climate change),the national sums of the CO₂and CH₄emissions for the 2020 s and 2090 s were estimated to be 5.8×10⁶and 6.0×10⁶t CO₂-equivalents(CO₂-eq)year^-1for CO₂and 6.4×10⁶and 6.6×10⁶t CO₂-eq year^-1for CH₄,respectively,indicating no significant changes over 80 years.Under RCP-8.5,in the 2090 s,CH₄emissions were predicted to increase by 10.7×10⁶and 14.9×10⁶t CO₂-eq year^-1,for a 10-or 30-cm tillage depth,respectively.However,the CO₂emissions gradually decreased with rising temperatures,due to reduced root respiration.Deep tillage increased the emissions of both GHGs,with a more pronounced effect for CH₄than CO₂.Intermittent drainage in the middle of the cropping season can attenuate the CH₄emissions from paddy fields.The findings of this work will aid in developing nationwide policies on agricultural land management in the face of climate change.     

基于主观偏好和景观空间指标的农业景观特征偏好模型: 以北京市11个农业景观特征区域为例

本研究以北京市11个农业景观特征区域的真实照片为评价资料,通过对46位环境相关专业大学生进行的平衡非完全区组排序评判测试得到他们对不同景观照片的偏好数值。以250m为边长的正三角形在2006年110000土地利用图上截取出照片所对应的数据,根据这些数据计算了反映该照片景观特征的空间格局指数。利用多元逐步回归,以相对应的空间格局指数以及主观判断得到的绿色覆盖度和管理水平等共11个指标,分别针对不同景观特征区域构建景观偏好模型。研究表明,除各指标在权重上的差异外,有些指标在不同特征区域内,甚至在对景观偏好影响的方向上都有所差异:绿色覆盖度、管理水平、斑块黏合度、斑块聚合程度、分维度指数均体现出对景观可视偏好的正向影响,开阔地比例在可视范围体现了对景观偏好的逆向影响,而斑块数量、蔓延度、最大斑块指数、干扰比例和林地比例在不同景观特征分区内则表现不同的影响趋向。