Holocene survival of the wild horse in Europe: a matter of open landscape?

The wild horse Equus ferus was one of the most frequent species of the Late Pleistocene large ungulate fauna in Eurasia and played an important role in the subsistence of human groups, especially at the end the Late Glacial. It is frequently assumed that E. ferus became extinct in Europe at the beginning of the Holocene because of the development of woodlands and loss of open habitats. Because of its preference for open habitats and in spite of its adaptability, the appearance or disappearance of the wild horse could therefore be a suitable palaeoecological indicator for the opening of the Holocene primeval woodlands. We revised the dating and reliability of the subfossil record and dated several bones by atomic mass spectrometry ¹⁴C dating. From the beginning of the Holocene (9600 cal a BC) to the end of the Atlantic Period (3750 cal a BC) there are 207 archaeological sites with wild horse records available in Europe. E. ferus survived the Pleistocene Holocene transition in Europe, but the spatiotemporal dynamics of populations fluctuated remarkably in the early and middle Holocene. Small and sparse populations increasingly became extinct during the early Holocene, until between 7100 and 5500 cal a BC the wild horse was almost absent in central parts of the European Lowlands. Particular conditions in natural open patches in the canopy forests, chalklands and floodplains may have maintained the local survival of the horse in some regions of the Lowlands, however. In the Late Atlantic, between 5500 and 3750 cal a BC the range of the wild horse was again extended. It re‐immigrated into central and western Europe, probably as a consequence of increasing landscape opening by Neolithic peoples. The data presented here may be a valuable part of the debate on the degree of openness of the early and middle Holocene landscape. Copyright © 2011 John Wiley & Sons, Ltd.     

甘孜州天然林禁伐的影响与区域持续发展对策

森林采伐向来是甘孜州经济的重大支柱，对地方财政收入的贡献率达58．63％（1997年）。天然林禁伐影响巨大而广泛，既使经济产出与财政收入锐减，又导致一系列相关 产业萎缩，劳动就业压力增大，研究指出，选择新经济增长点与生长点产业大力加以培育发展迫在眉睫。其中，以加大财政转移支付力度加强基础设施建设、加强绿色产品与绿色食品发展以及天然药物开发，大力发展旅游业和流通产业等应是正确选择。     

大兴安岭原始森林覆盖区化探异常查证方法研究与实践

文章综述了原始森林覆盖区勘查技术方法研究历史、现状及意义.通过对区内某1:20万化探异常进行追踪、查证方法的实验性研究,初步确定适合原始森林覆盖区的物探方法和化探方法.对具有成矿远景的1:20万异常的查证方法、过程为:①1:5万网格法水系沉积物或1:5万土壤测量;②配合以适量的1:1万或1:2万剖面土壤测量,最终达到分解异常、缩小找矿靶区的目的;③1:1万～1:2万地质简测,结合地表工程确定是否为矿致异常,初步确定矿化类型;④选用高精度磁测、双频激电测量方法进行1:2.5万或1:1万的面积性物探测量;⑤运用槽探、坑探、浅井及钻探等探矿手段寻找工业矿体.对二根河、洛古河、阿南林场3个1:20万异常查证证明该方法是适宜森林覆盖景观区的快捷且行之有效的异常查证方法.     

Location offarm woodlands in Denmark: a quantification of the results of the scheme for field afforestation in Ribe and Vejle counties

The article analyses the results of the scheme for field afforestation (EU-regulation 2080/92) in Denmark. The purpose is twofold, firstly to document the afforestation on arable land taking place both within the scheme and outside the scheme for field afforestation. The former is documented in Ribe and Vejle counties whereas the latter is documented in three smaller areas: Varde, Vorbasse, and Vejle. Secondly, the article argues that in order to evaluate the afforestation not only the location within designated areas hut also the spatial parameters and configuration of new woodlands must be considered. Two methods -'forest-pictures' and ‘gradient-pictures’-are presented and applied in order to quantify the spatial configuration of new woodlands in the landscape.     

Vegetation patterns and diversity along an altitudinal and a grazing gradient in the Jabal al Akhdar mountain range of northern Oman

Little is known about the effects of grazing on vegetation composition on the Arabian Peninsula. The aim of this study therefore was to analyse the vegetation response to environmental conditions of open woodlands along an altitudinal and a grazing gradient in the Jabal al Akhdar mountain range of Oman. The species composition, vegetation structure, grazing damage and several environmental variables were investigated for 62 samples using a nested plot design. Classification analysis and a Canonical Variate Analysis (CVA) were used to define vegetation types and to identify underlying environmental gradients. The relationship between environmental variables and diversity was analysed using correlation coefficients and a main-effects ANOVA. The plant species richness followed a unimodal distribution along the altitudinal gradient with the highest number of species at the intermediate altitudinal belt. The cluster analysis led to five vegetation groups: The Sideroxylon mascatense–Dodonaea viscosa group on grazed and the Olea europaea–Fingerhuthia africana group on ungrazed plateau sites at 2000 m a.s.l., the Ziziphus spina-christi–Nerium oleander group at wadi sites and the Moringa peregrina–Pteropyrum scoparium group at 1200 m a.s.l, and the Acacia gerrardii–Leucas inflata group at 1700 m a.s.l. The CVA indicated a clear distinction of the groups obtained by the agglomerative cluster analysis. The landform, altitude and grazing intensity were found to be the most important variables distinguishing between clusters. Overgrazing of the studied rangeland is an increasing environmental problem, whereas the plant composition at ungrazed sites pointed to a relatively fast and high regeneration potential of the local vegetation.     

Operationalizing measurement of forest degradation: Identification and quantification of charcoal production in tropical dry forests using very high resolution satellite imagery

Quantification of forest degradation in monitoring and reporting as well as in historic baselines is among the most challenging tasks in national REDD+ strategies. However, a recently introduced option is to base monitoring systems on subnational conditions such as prevalent degradation activities. In Tanzania, charcoal production is considered a major cause of forest degradation, but is challenging to quantify due to sub-canopy biomass loss, remote production sites and illegal trade. We studied two charcoal production sites in dry Miombo woodland representing open woodland conditions near human settlements and remote forest with nearly closed canopies. Supervised classification and adaptive thresholding were applied on a pansharpened QuickBird (QB) image to detect kiln burn marks (KBMs). Supervised classification showed reasonable detection accuracy in the remote forest site only, while adaptive thresholding was found acceptable at both locations. We used supervised classification and manual digitizing for KBM delineation and found acceptable delineation accuracy at both sites with RMSEs of 25–32% compared to ground measurements. Regression of charcoal production on KBM area delineated from QB resulted in R²s of 0.86–0.88 with cross-validation RMSE ranging from 2.22 to 2.29 Mg charcoal per kiln. This study demonstrates, how locally calibrated remote sensing techniques may be used to identify and delineate charcoal production sites for estimation of charcoal production and associated extraction of woody biomass.     

Introduction to ‘A tribute to Edward P. Glenn (1947–2017): A legacy of scientific environmental assessment and applications in hydrological processes’

This special issue (SI) ‘A Tribute to Edward P. Glenn (1947-2017): A legacy of Scientific Environmental Assessment and Applications in Hydrological Processes’ is a celebration of the extensive work of Dr. Ed Glenn that was instrumental across multiple sub-disciplines of hydrology. The SI highlights four primary areas of hydrological processes that are cornerstones of Ed Glenn's over four decades of research. These contributions cover the following specialties: (i) Hydrology in the Colorado River Delta; (ii) Riparian ecosystem water use; (iii) Riparian Plant ecophysiology and ecohydrology; and (iv) Methods and models to characterize evapotranspiration. Since Ed was passionate about the dryland delta at the end of the Colorado River, we begin with four research studies that focus on this special region on the U.S.–Mexico border which encompasses four states (Baja and Sonora in Mexico and California and Arizona in United States) as well as tribal communities in the transboundary area. The Colorado River delta reaches the Northern Gulf of California in the Sea of Cortez which has been designated as a UNESCO international biosphere reserve (‘Reserva de la Biosfera El Pinacate y Gran Desierto de Altar’), which includes the Upper Gulf of California and Delta of the Colorado River (‘Reserva de la Biosfera Alto Golfo de California y Delta del Río Colorado’). Ed spent the majority of his last three decades on water balance studies and on ground-based transpiration quantification for validation of satellite and airborne remote sensing methods. We wrap up the special issue with contributions related to improving satellite and airborne remote sensing estimation of actual evapotranspiration. It is our pleasure to summarize the 16 research studies contributed to the special issue to honour Ed Glenn's research interests.     

广西百色大王岭原始森林风景区气候条件分析

采用广西百色大王岭原始森林景区1976～1991年平均资料及2005-2008年该地自动气象监测站资料对景区旅游气象条件进行统计分析,结果表明：风景区气温适中,年温差振幅小,夏、冬温差5℃,夏季少有35℃以上的高温,年舒适指数等级在-1～1的最佳舒适期长达9个月;影响景区旅游活动的主要气象灾害有强降雨、寒害等。     

Predicting forest carbon stocks from high resolution satellite data in dry forests of Zimbabwe: exploring the effect of the red-edge band in forest carbon stocks estimation

In this study, we tested whether the inclusion of the red-edge band as a covariate to vegetation indices improves the predictive accuracy in forest carbon estimation and mapping in savanna dry forests of Zimbabwe. Initially, we tested whether and to what extent vegetation indices (simple ratio SR, soil-adjusted vegetation index and normalized difference vegetation index) derived from high spatial resolution satellite imagery (WorldView-2) predict forest carbon stocks. Next, we tested whether inclusion of reflectance in the red-edge band as a covariate to vegetation indices improve the model's accuracy in forest carbon prediction. We used simple regression analysis to determine the nature and the strength of the relationship between forest carbon stocks and remotely sensed vegetation indices. We then used multiple regression analysis to determine whether integrating vegetation indices and reflection in the red-edge band improve forest carbon prediction. Next, we mapped the spatial variation in forest carbon stocks using the best regression model relating forest carbon stocks to remotely sensed vegetation indices and reflection in the red-edge band. Our results showed that vegetation indices alone as an explanatory variable significantly (p < 0.05) predicted forest carbon stocks with R² ranging between 45 and 63% and RMSE ranging from 10.3 to 12.9%. However, when the reflectance in the red-edge band was included in the regression models the explained variance increased to between 68 and 70% with the RMSE ranging between 9.56 and 10.1%. A combination of SR and reflectance in the red edge produced the best predictor of forest carbon stocks. We concluded that integrating vegetation indices and reflectance in the red-edge band derived from high spatial resolution can be successfully used to estimate forest carbon in dry forests with minimal error.