东北地区玉米整地、播种和收获气象适宜度评价模型

天气、土壤条件影响玉米整地、播种和收获作业的质量及作业效率,进而影响到苗情、产量和生产成本,东北地区相关的农业气象要素是土壤湿度、土壤解冻深度、温度、日雨量和风力等.根据气象、土壤条件对玉米整地、播种和收获的影响,用模糊隶属函数建立了这些农事活动气象适宜度评价函数及其农业气象指标,用权重法分别建立了整地、播种和收获综合气象适宜度评价模型.检验结果表明,这些模式和指标符合实际,可以用于相关农事活动的气象适宜度评价业务.在气温和降水等气象要素预报的基础上,该模型还可以用于相关农事气象适宜度和适宜期的预报.     

用物候作农业气象预报

农业气象预报和情报是当前气象为农业服务的一种重要手段。我们试用了能够综合反映气候变化的植物物候,即利用指示植物物候期编制农事活动和作物发育期预报。这种方法不仅简单易行,符合实际,而且还利于提高预报的准确性。现简介如下:一、适宜播种期预报1.冬小麦适宜播种期预报     

不同方法在湖南省早稻产量动态预报中的比较

为了提高产量趋势预报的准确性和定量预报的准确率,利用1962—2002年气象、早稻产量和田间观测资料,建立基于气候适宜度、关键气象因子、作物生长模型的湖南省早稻产量动态预报方法,进行回代检验;并利用2003—2012年资料进行预报检验。分析表明:3种方法的预报准确率比较接近,平均在93.8%以上;基于气候适宜度预报方法的趋势预报准确性最高,较基于关键气象因子的预报方法高4%~6%;基于作物生长模型预报方法的误差5%以内样本百分率最高,较基于气候适宜度的预报方法高2%~20%。研究结果为湖南省早稻产量动态预报筛选出了较优的方法,即产量趋势预报选用基于气候适宜度的方法,定量预报选用基于作物生长模型的方法,同时可供我国其他早稻区的产量动态预报方法研究借鉴。     

内蒙古草原蝗虫发生发展气象适宜度指数构建方法

通过对内蒙古草原蝗虫发生发展关键气象条件进行分析,选取蝗虫生长发育期关键生理气象影响因子,建立草原蝗虫发生发展气象适宜度指数,对内蒙古草原蝗虫发生发展气象等级进行预报,平均预报准确率达到68％以上。用草原蝗虫发生发展气象适宜度指数根据气象站点观测资料可对站点区域蝗虫发生发展气象等级进行预报,从而根据站点空间分布和区域气象条件对草原蝗虫发生发展气象条件的满足程度进行空间分析,具有直观、便捷、分析能力强等业务化应用特点。     

陕西苹果农用天气预报探索与实践

利用陕西29个苹果基地县40年气象资料和7个代表站10年苹果物候观测资料,结合苹果生长发育适宜气象条件与气象灾害指标,选取天气状况、气温、空气相对湿度、风速等主要气象因子,运用农业气象基本原理和农业气象统计方法,综合评估农业气象资源匹配和灾害影响,研究开发了苹果生育期主要气象灾害、主要农事活动和生长气象条件适宜性等一系列农用天气预报产品,在果业生产管理和防灾减灾中发挥了积极作用。并结合业务服务提出了深化农用天气预报服务的建议和设想。     

蔬菜农事操作天气适宜性判别模型验证

基于从化国家气象站2013~2015年的逐日气象资料,利用农事操作天气适宜性判别模型计算逐日农事操作适宜度,并根据广州神农田园农业有限公司2013~2015年共计691天生产记录中提取的约8000条农事操作记录,对施肥、喷药和收获这三项农事操作天气适宜性判别模型进行了验证。通过逐日对比、卡方检验以及典型气象灾害过程个例分析,得到如下结论:(1)天气适宜性模型判别结论与实际农事操作较为一致,施肥、喷药和收获操作一致率分别为77.9%、89.7%和93.5%;(2)经卡方检验,天气适宜性模型判别结论与施肥、喷药和收获决定是否进行操作均显著关联(P0.001);(3)在持续性不利天气条件下,天气适宜性模型判别结论与实际农事操作不一致的情况容易出现,受到实际生产条件的制约,有时需要在不利天气条件下进行农事操作;(4)需要调整和细化天气适宜性模型,以提升农事操作预报服务产品的实用性。     

夏玉米产量动态预报方法研究

利用洛阳市1981—2014年夏玉米产量资料、生育期内的气象资料,结合夏玉米的生物学特性,分别构建夏玉米温度、光照、水分适宜度模型,利用夏玉米生长季内不同时段的气候适宜度指数与气象产量的相关关系,构建夏玉米产量预报模型,并分别利用1981—2010年、2011—2014年数据进行回代、预报检验。结果表明,气候适宜度与夏玉米气象产量存在显著的相关性,两者变化趋势一致。1981—2010年各时段预报模型的单产回代检验准确率在89.19%~91.42%之间,趋势回代检验准确率达89.66%~96.55%。2011—2014年预报检验,预报准确率最高为96.16%,最低为91.05%,趋势预报准确率最高为100%,最低为75%,预报准确率较高,建立的产量动态预报模型可以在业务上推广应用。     

农林重大病虫害和农业气象灾害的预警及控制技术研究

1 农业气象灾害预警技术研究 对华北农业干旱、东北作物低温冷害、江淮小麦油菜渍害、华南经济林果寒害和水产寒害等农业气象灾害分别建立了统计预测模型和机理预测模型相结合、长中短不同预报时效相结合的预警预测模型。其中作物生长模型与区域气候模式相结合的新一代农业气象灾害预测技术在实现区域尺度预测应用上取得重要进展；各类预测模型在灾害指标、预测方法上取得新的突破，预报准确率进一步提高。在此基础上，成功研制出包含多种预测方法、不同预报时效、可供准业务运行的农业气象灾害多灾种综合预测预警系统。课题研制的模型进行了业务试验，部分成果如广东经济林果寒害预警已投入业务运行。课题于2005年12月顺利通过项目主持单位农业部组织的专家验收。该课题成果代表了我国目前农业气象灾害预警预测研究的最新进展和水平，对于进一步开展和提高其他地区、其他灾害的预报能力具有一定的推广借鉴作用和应用前景。     

农林重大病虫害和农业气象灾害的预警及控制技术研究

1 农业气象灾害预警技术研究 对华北农业干旱、东北作物低温冷害、江淮小麦油菜渍害、华南经济林果寒害和水产寒害等农业气象灾害分别建立了统计预测模型和机理预测模型相结合、长中短不同预报时效相结合的预警预测模型.其中作物生长模型与区域气候模式相结合的新一代农业气象灾害预测技术在实现区域尺度预测应用上取得重要进展;各类预测模型在灾害指标、预测方法上取得新的突破,预报准确率进一步提高.在此基础上,成功研制出包含多种预测方法、不同预报时效、可供准业务运行的农业气象灾害多灾种综合预测预警系统.课题研制的模型进行了业务试验,部分成果如广东经济林果寒害预警已投入业务运行.课题于2005年12月顺利通过项目主持单位农业部组织的专家验收.该课题成果代表了我国目前农业气象灾害预警预测研究的最新进展和水平,对于进一步开展和提高其他地区、其他灾害的预报能力具有一定的推广借鉴作用和应用前景.     

2011年西安世园会花卉气象服务探索与实践

根据2011年西安世界园艺博览会气象服务需求,收集整理206种参展花卉的相关信息,建立花卉生长习性气象指标、分科属种植信息、灾害敏感性、展园种植信息等数据库;运用模糊综合评判方法和专家打分方法分别建立了艳丽指数、移栽指数、喷洒指数、遮蔽指数等花卉气象指数模型和花期、果期、生育期适宜气象条件预报模型;开发了基于信息检索和预报服务为主要功能的西安世园会花卉气象服务系统,为西安世界园艺博览会提供花卉的生长和管理等方面的气象服务,并取得了较好的服务效果。     

农作物气候适宜度实时判定系统

以旬、月、季、作物生育期为单位时段,根据农作物生长发育所需要的气象条件,把单位时段内气候因子的数量变化,通过模糊数学中隶属函数的方法,转化成对作物生长发育的适宜程度,计算各时段内的温度、降水、日照及光温水综合因子对作物生育影响的适宜度,计算结果以表格和图形的方式输出。经过业务试应用,效果良好,所计算的不同作物不同时段的温度适宜度、降水适宜度、日照适宜度、光温水综合适宜度符合实际情况,为定量判定气象条件对农作物影响提供了依据。     

河南省夏玉米气候适宜度评价

为定量评价气象条件对作物生长及产量形成的影响,本文依据夏玉米不同发育阶段上限温度、最适温度、下限温度、需水量、需光性等生物学指标,构建了河南省夏玉米气候适宜度评价模型。通过对13个代表站30 a全生育期气候适宜度和相对气象产量进行相关分析,表明该模型能较好地反映河南省夏玉米的气候适宜水平及其动态变化。利用检验后的模型计算了河南省67个站1981-2011年夏玉米生长季单因子及综合气候适宜度,结果表明河南省夏玉米大部分生育期光热资源较适宜,能满足玉米生长所需,仅在灌浆后期略显不足,降水是影响夏玉米产量形成的主要限制因子,且降水适宜度年际变化幅度大于日照和温度。综合气候适宜度年际波动表现为抽雄—乳熟期〉出苗—抽雄期〉全生育期。空间分布上气候适宜度呈自西北向东南方向的递增趋势,适宜度高值区分布在南阳东部及驻马店部分地区。     

Relationship between projected changes in future climatic suitability and demographic and functional traits of forest tree species in Spain

The response of plant species to future climate conditions is probably dependent on their ecological characteristics, including climatic niche, demographic rates and functional traits. Using forest inventory data from 27 dominant woody species in Spanish forests, we explore the relationships between species characteristics and projected changes in their average climatic suitability (occurrence of suitable climatic conditions for a species in a given territory) obtained by empirical niche-based models, under a business-as-usual climate change scenario (A1, HadCM3, 2001–2100). We hypothesize that most species will suffer a decline in climatic suitability, with a less severe for species (i) currently living in more arid climates or exhibiting a broader current climatic niche; (ii) with higher current growth rates; (iii) with functional traits related to resistance to water deficits. The analysis confirm our hypothesis since apart from a few Mediterranean species, most species decrease their climatic suitability in the region under future climate, characterized by increased aridity. Also, species living in warmer locations or under a wider range of climatic conditions tend to experience less decrease in climatic suitability. As hypothesized, a positive relationship was detected between current relative growth rates and increase in future climatic suitability. Nevertheless, current tree mortality did not correlate with changes in future climatic suitability. In contrast with our hypothesis, functional traits did not show a clear relationship with changes in climate suitability; instead species often presented idiosyncratic responses that, in some cases, could reflect past management. These results suggest that the extrapolation of species performance to future climatic scenarios based on current patterns of dominance is constrained by factors other than species autoecology, particularly human activity.     

Targeting areas for Reducing Emissions from Deforestation and forest Degradation (REDD+) projects in Tanzania

Reducing Emissions from Deforestation and forest Degradation (REDD+) has gained momentum as a climate mitigation strategy that can be implemented at multiple scales. Sub-nationally, REDD+ projects that aim to capture carbon funding are implemented throughout tropical countries. A spatial targeting approach for optimal REDD+ project landscape is demonstrated using Tanzania as an example. This study used GIS-based Multi-criteria Decision Analysis to identify potential areas for REDD+ projects development incorporating different combinations of criteria. The first approach, efficient targeting, focuses on areas with high forest carbon content, high deforestation risk and low opportunity cost. The second approach, co-benefits targeting, aims at areas with high biodiversity and high poverty rate on top of criteria in efficient targeting. The resulting suitability maps displays areas of high, medium and low suitability for future REDD+ projects development based on the targeting approaches. Locations of current REDD+ projects in Tanzania were also overlaid with suitability map to visually inspect how they match up. This approach allows decision-makers to prioritize preferences for various site-selection criteria and make informed decisions about REDD+ projects locations.     

LULUCF in the post-2012 regime: fixing the problems of the past?

One of the reasons why the Kyoto Protocol has been environmentally ineffective is the flaws in the land use, land-use change and forestry (LULUCF) accounting rules, including voluntary accounting for Article 3.4 activities, the adoption of a definition of forest management that allowed parties to preferentially include and exclude forest lands, and allowing parties with net emissions from LULUCF in 1990 to include deforestation emissions in their 1990 emissions base year. Three proposed amendments to the LULUCF rules for the post-2012 regime are discussed and analysed: (1) a force majeure rule, (2) a baseline-and-credit system for forest management and (3) an ‘emissions-to-atmosphere’ approach for harvested wood products. Although these proposals have the potential to significantly improve the accounting framework, there are still significant problems such as the failure to account for the biophysical effects of forest activities, uncertainties associated with the application of the forest management baseline-and-credit system and continuing optional coverage of Article 3.4 activities.     

基于气候适宜度的夏玉米发育期模拟模型

结合前人气候适宜度的研究成果,以作物生理生态发育过程为基础,构建了夏玉米发育期预报模型。模型中分别建立了夏玉米温度、降水、日照时数适宜度函数,并结合河南省19个农业气象试验站的夏玉米发育期资料,运用通径分析法确定各个生育期温度、降水和日照的影响权重系数,计算出综合适宜度,用来预测夏玉米生育期。结果表明,模型能够较好地预测各个发育期(出苗、七叶、拔节、抽雄、乳熟和成熟)。建模资料的模拟值与观测值比较的均方根误差分别为1.5、3.1、3.4、2.9、4.0、4.5 d。运用独立资料对模型所作预测值的均方根误差在1.0~4.6 d之间。     

Illicit Drivers of Land Use Change: Narcotrafficking and Forest Loss in Central America

Illegal activity, such as deforestation for illicit crops for cocaine production, has been inferred as a cause of land change. Nonetheless, illicit activity is often overlooked or difficult to incorporate into causal inference models of land change. Evidence continues to build that narcotrafficking plays an important, yet often unreported, role in forest loss. This study presents a novel strategy to meet the challenge of estimating the causal effect of illicit activity in land change using consolidated news media reports to estimate the relationship between drug trafficking and accelerated forest loss in Central America. Drug trafficking organizations engage in illegal land transactions, money laundering, and territorial control that can manifest as forest conversion to agriculture or pasture land uses. Longitudinal data on 50 sub-national units over a period of 16 years (2001-2016) are used in fixed effects regressions to estimate the role of narcotrafficking in forest loss. Two narcotrafficking activity proxies were developed as explanatory variables of forest loss: i) an “official” proxy from drug seizures data within 14 sub-national units; and, ii) an “unofficial” proxy developed from georeferenced news media accounts of narcotrafficking events. The effect of narcotrafficking was systematically compared to the other well-known causes of forest loss, such as rural population growth and other conventional drivers. Both proxies indicate narcotrafficking is a statistically significant (p<0.01) contributor to forest loss in the region, particularly in Nicaragua (p<0.05, official proxy), Honduras (p<0.05, media proxy), and Guatemala (p<0.05, media proxy). Narcotrafficking variables explain an additional 5% (media proxy) and 9% (official proxy) of variance of forest loss not captured by conventional models. This study showed the ability of news media data to capture the signal of illicit activity in land use changes such as forest loss. The methods employed here could be used to estimate the causal effect of illicit activities in other land and environmental systems. Our results suggest that current drug policy, which concentrates drug trafficking in remote areas of very high cultural and environmental value, has helped to accelerate the loss of Central America's remaining forests.     

Drivers and mechanisms of forest change in the Himalayas

Mountains are critical ecosystems that have a strong influence far beyond their topographic boundaries. More than 50 million people inhabit the Himalayas, and more than one billion people depend on the ecosystem services they provide. Anthropogenic activities have driven concurrent deforestation and regeneration in the Himalayas, and interventions to reduce forest loss and promote forest recovery require a synthetic understanding of the complex and interacting drivers of forest change. We conducted a systematic review of case studies from 1984 to 2020 (n = 137) and combined a system dynamics approach with a causal network analysis to identify, map and articulate the relationships between the drivers, actors and mechanisms of forest change across the entirety of the Himalayan mountain range. In total, the analysis revealed five proximate drivers, 12 underlying drivers, two institutional factors and five ‘other’ factors connected by a total of 221 linkages. Forest change dynamics have been dominated by widespread smallholder agriculture, extensive non-timber forest product extraction, widespread commercial and non-commercial timber extraction, and high rates of agricultural abandonment. Underlying drivers include population growth, poor agricultural productivity, international support for development projects, and successful community forest management systems. Contradictory linkages emerge from a combination of contextual factors, which can have negative impacts on conservation goals. Global processes such as shifts in governance, transnational infrastructure-development programs, economic slowdowns, labor migrations and climate change threaten to destabilize established dynamics and change forest trajectories. The underlying and proximate drivers interact through multiple pathways that can be utilized to achieve conservation goals. Based on this analysis, we highlight five thematic focus areas to curtail forest loss and promote recovery: (1) decreasing the population pressure, (2) sustainable increase of agricultural productivity, (3) strengthening of forest management institutions, (4) leveraging tourism growth and sustainable infrastructure expansion, and (5) fuel transition and establishing firewood plantations on degraded land. The broader adoption of systems thinking, and specifically a system dynamics approach and causal network analysis, will greatly enhance the rigour of policy development, help design site-specific interventions at multiple spatial scales which can respond to local and global changes, and guide deeper inquiry to enhance our understanding of driver-forest dynamics.     

Implications of Country-Level Decisions on the Specification of Crown Cover in the Definition of Forests for Land Area Eligible for Afforestation and Reforestation Activities in the CDM

Within the Kyoto Protocol, countries have significant latitude to define a forest. The most important parameter affecting area designated as forest is the minimum crown density which can be set between 10 and 30 percent. The choice will have implications for the amount of land available in a country for afforestation and reforestation (A/R) activities within the Clean Development Mechanism (CDM). In this paper, we used GIS analysis to look at four case studies from countries involved in the EU-funded ENCOFOR project: Bolivia, Ecuador, Uganda and Kenya. We also looked at the effects of other factors that would exclude land from eligibility for A/R projects. A low threshold of 10 percent crown cover resulted in exclusion of 70 to 90 percent of the land area of all countries except Kenya, which differed from the other countries by its large dryland areas. Much less area was excluded when higher thresholds were used. The spatial analyses showed not only the effects of the choice of the crown cover criterion, but also where the land was available for CDM activities within each country at different thresholds. This is the first time that the effect of the crown cover element of the Kyoto forest definition on land availability and distribution for CDM A/R activities has been quantified. While there are a number of reasons to choose different thresholds, this analysis suggests that countries that are considering using CDM finance for rural development might want to select the higher minimum threshold for crown cover in order to maximize their participation and flexibility.     

中国森林乔木林碳储量及其固碳潜力预测

加强对我国森林碳储量和固碳潜力的研究,是制定中国增汇减排政策的重要依据,对我国国际气候谈判和全面了解森林碳汇潜力具有重要作用。利用我国第七次和第八次森林资源清查中各优势树种的面积和蓄积量数据,采用IPCC材积源生物量法（volume-biomass method),估算了我国森林（乔木林）碳储量和碳密度及其分布,分析我国不同省份天然乔木林和人工乔木林碳储量龄组结构特征;建立分区域、分起源主要优势树种的单位面积蓄积-林龄Logistic生长方程,结合我国森林2020年和2030年面积蓄积增长目标,预测我国乔木林2010—2050年间碳汇潜力。结果表明：第八次清查期间中国乔木林总碳储量为6135.68 Tg,碳密度为37.28 Mg/hm ²;天然乔木林和人工乔木林的碳储量分别为5246.07 Tg和889.61 Tg,分别占总碳储量的85.50%和14.50%。到2050年,中国乔木林和新造林的总碳储量和平均碳密度将分别达到11125.76 Tg和52.52 Mg/hm ²,与2010年相比分别增加81%和41%。分析结果表明中国乔木林有很大的碳汇潜力,将在应对和减缓全球气候变化中发挥重要作用。