Barren‐ground caribou (Rangifer tarandus groenlandicus) behaviour after recent fire events; integrating caribou telemetry data with Landsat fire detection techniques

Fire regimes are changing throughout the North American boreal forest in complex ways. Fire is also a major factor governing access to high‐quality forage such as terricholous lichens for barren‐ground caribou (Rangifer tarandus groenlandicus). Additionally, fire alters forest structure which can affect barren‐ground caribou's ability to navigate in a landscape. Here, we characterize how the size and severity of fires are changing across five barren‐ground caribou herd ranges in the Northwest Territories and Nunavut, Canada. Additionally, we demonstrate how time since fire, fire severity, and season result in complex changes in caribou behavioural metrics estimated using telemetry data. Fire disturbances were identified using novel gap‐free Landsat surface reflectance composites from 1985 to 2011 across all herd ranges. Burn severity was estimated using the differenced normalized burn ratio. Annual area burned and burn severity were assessed through time for each herd and related to two behavioural metrics: velocity and relative turning angle. Neither annual area burned nor burn severity displayed any temporal trend within the study period. However, certain herds, such as the Ahiak/Beverly, have more exposure to fire than other herds (i.e. Cape Bathurst had a maximum forested area burned of less than 4 km²). Time since fire and burn severity both significantly affected velocity and relative turning angles. During fall, winter, and spring, fire virtually eliminated foraging‐focused behaviour for all 26 years of analysis while more severe fires resulted in a marked increase in movement‐focused behaviour compared to unburnt patches. Between seasons, caribou used burned areas as early as 1‐year postfire, demonstrating complex, nonlinear reactions to time since fire, fire severity, and season. In all cases, increases in movement‐focused behaviour were detected postfire. We conclude that changes in caribou behaviour immediately postfire are primarily driven by changes in forest structure rather than changes in terricholous lichen availability.     

Relationships between vegetation patterns and hydroperiod on the Roanoke River floodplain,North Carolina

This study quantified relationships between forest composition and flooding gradients on the Roanoke River floodplain, North Carolina. Because flooding is highly variable in time and space, the research was designed to determine the specific hydrological parameters that control woody species abundance on the landscape scale. I specifically tested the importance of spring vs. yearly flood duration, as well as flood duration during hydrologically wet vs. dry years. Field vegetation samples of woody species composition were integrated with spatial data from a Landsat Thematic Mapper (TM) classification and a flood simulation model derived in part from synthetic aperture radar (SAR) imagery. Flood simulations were output and summarized for the periods 1912–1950 (before dams were constructed on the river) and 1965–1996 (after all of the dams were completed). Tenth percentile (dry), median, and 90th percentile (wet) hydroperiod (flood duration) regimes were generated for the spring and year, both pre- and post-dam. Detrended correspondence analysis (DCA) was used to ordinate the plot data, and correlation/regression between ordination axis scores and the flood variables were used to explore the relationships between flooding and species composition. Nineteenth percentile hydroperiod (i.e., wet conditions) correlated most strongly with DCA axis 1 (r>0.9), indicating that inundation during extremely wet years strongly controls species composition on the floodplain. The results were used to quantitatively determine the niche width for both species and mapped vegetation classes in terms of number of days flooded annually and during the spring growth period. The results suggest that spring hydroperiod is an important mechanism that may drive competitive sorting along the flooding gradient, especially during the early years of succession (i.e., pre-dam, which represents the period during which most of the forests sampled were established), and that annual hydroperiod affects the relative dominance of species as the forests mature.     

甘南地区二氧化碳施肥效应对生态系统的影响

陆地生态系统是全球第二大碳库,其碳收支一直是气候变化研究的热点领域,而研究二氧化碳（CO₂）施肥效应又是全球变化碳循环领域较为关注的前沿部分。CO₂与生态系统关系复杂,当前仍无法厘清CO₂对陆地生态系统碳循环的影响作用。基于太阳辐射数据、气温数据及归一化植被指数数据等,利用光能利用率遥感模型,模拟2019年甘南地区的碳循环,选取三个指标,即GPP （陆地生态系统总初级生产力）、NPP （净初级生产力）和NEP （净生态系统生产力）来分析甘南地区植被固碳的时空变化特征及CO₂施肥效应。结果表明：（1）甘南地区2019年植被固碳总量约为2611 tC。甘南地区生态系统GPP、NPP和NEP季节性特征明显,其值均在夏季达到最高;而在空间上,GPP、NPP表现为东高西低的特征,NEP呈现出北高南低的分布特征。（2） CO₂对GPP、NPP存在正向的施肥效应,分别增加了14.4%和14.3%;而对NEP具有负向反馈效应,使其减少了0.3%,并且CO₂对NEP的影响整体也表现为北高南低的特征。研究揭示出：虽然CO₂在提升GPP和NPP时,正向的施肥效应明显,但是对甘南地区的NEP,即固碳量来说,CO₂的影响却很有限。因此在研究CO₂施肥效应时不应一概而论,生态地理环境对其的影响不可忽视。研究可以为揭示陆地生态系统碳循环的动态机制提供一定的理论依据。     

Integrating field surveys and remote sensing data to study distribution, habitat use and conservation status of the herpetofauna of the Comoro Islands

We studied the non-marine reptile and amphibian species of the volcanic Comoro archipelago in the Western Indian Ocean, a poorly known island herpetofauna comprising numerous microendemic species of potentially high extinction risk and widespread, non-endemic and often invasive taxa. According to our data, the Comoro islands are inhabited by two amphibian species and at least 28 species of reptiles although ongoing genetic studies and unconfirmed historical records suggest an even higher species diversity. 14 of the 28 currently recognized species of terrestrial reptiles (50%) and the two amphibians are endemic to a single island or to the Comoro archipelago. The majority of species are most abundant at low elevation. However, a few endemic species, like the gekkonid lizards Paroedura sanctijohannis and Phelsuma nigristriata, are more common in or even confined to higher altitudes. We created habitat maps from remotely sensed data in combination with detailed species distribution maps produced using comprehensive data from field surveys between 2000 and 2010, literature, and historical locality records based on specimens in zoological collections. Using these data, we assessed the conservation status of the endemic terrestrial reptiles and amphibians according to the IUCN Red List criteria. Our results show that although little area of natural forest remains on the Comoros, many species are abundant in degraded forest or plantations. Competition and predation by invasive species appears to be the most important threat factor for the endemic herpetofauna, together with habitat degradation and destruction, which further favours invasive species. We propose the status Endangered for three species, Vulnerable for one species, Near Threatened for six species, Least Concern for four and Data Deficient for two species. The endemic subspecies Oplurus cuvieri comorensis is proposed for the status Critically Endangered. Based on the results of this study, seven areas of importance for reptile and amphibian conservation on the Comoros are identified. This study shows how remote sensing data can contribute to increasing accuracy and objectiveness of conservation assessments.     

Seasonal Foliage Changes in the Eastern Amazon Basin Detected from Landsat Thematic Mapper Satellite Images1

Seasonal changes in tropical forests are difficult to measure from the ground, especially in areas of high species diversity and low phenological synchrony. Satellite images, which integrate individual tree canopies and cover a large spatial extent, facilitate tests for stand-level canopy phenology. Variability in near-infrated radiance (TM bands 4 and 5) of several distinct vegetation types was used to detect seasonal changes in a series of three Landsat Thematic Mapper (TM) images from the wet season to the dry season in Marabá, Brazil (eastern Amazon basin). Despite different atmospheric and instrumental conditions among the images, spectral changes were distinguishable. A phenological process (leaf aging, leaf drop, water stress) was determined from the spectral changes for each vegetation type. Changes in the spectral properties suggest that during the dry season, upland terra firme forest increased the rate of leaf exchange and some riparian vegetation was deciduous. Terra firme forest that had been altered by penetration of fires from nearby pastures increased in leaf biomass over a 14-month period. This study shows that a time series of images can provide information on temporal changes in primary vegetation and guide field studies to investigate seasonal changes that may not be detectable from the ground.     

Scaling-up knowledge of growing-season net ecosystem exchange for long-term assessment of North Dakota grasslands under the Conservation Reserve Program

Scaling‐up knowledge of land‐atmosphere net ecosystem exchange (NEE) from a single experimental site to numerous perennial grass fields in the Northern Great Plains (NGP) requires appropriate scaling protocols. We addressed this problem using synoptic data available from the Landsat sensor for 10 growing seasons (April 15 to September 30) over a North Dakota field‐site, where we continuously measured CO₂ exchange using a Bowen Ratio Energy Balance (BREB) system. NEE observed during the growing season at our field‐site from 1997 to 2006 vacillated with drought and deluge, with net carbon (C) losses to the atmosphere in 2006. We used stepwise linear regression with 10 years of Landsat and NEE data to construct and validate a model for estimating grassland growing‐season NEE from field to landscape scales. Eighty‐nine percent of the variability in NEE was explained by year, live biomass, carbon : nitrogen ratio, day of image acquisition, and annual precipitation. We then applied this model on 20 620 ha of North Dakota perennial grass fields enrolled in the Conservation Reserve Program (CRP), including 1272 fields east of the Missouri River and 165 fields west‐river. Growing‐season NEE for individual CRP fields was highly variable from 1997 to 2006, ranging from ?366 to 692 g C m^?2 growing season^?1. Mean annual growing‐season fluxes over 10 years for CRP fields located east‐river and west‐river were 317 g C m^?2 growing season^?1 and 239 g C m^?2 growing season^?1, respectively. Average cumulative growing‐season NEE modeled for fields east‐ and west‐river diverged from one another in 2002–2006, when west‐river fields received < 70% of the long‐term annual average precipitation during these years. Results indicate assessment of conservation practices on grassland CO₂ exchange during the growing season can be remotely estimated at field and landscape scales under variable environmental conditions and should be followed up with similar, spatially explicit investigations of NEE during the dormant season.     

Upscaling leaf area index in an Arctic landscape through multiscale observations

Monitoring and understanding global change requires a detailed focus on upscaling, the process for extrapolating from the site‐specific scale to the smallest scale resolved in regional or global models or earth observing systems. Leaf area index (LAI) is one of the most sensitive determinants of plant production and can vary by an order of magnitude over short distances. The landscape distribution of LAI is generally determined by remote sensing of surface reflectance (e.g. normalized difference vegetation index, NDVI) but the mismatch in scales between ground and satellite measurements complicates LAI upscaling. Here, we describe a series of measurements to quantify the spatial distribution of LAI in a sub‐Arctic landscape and then describe the upscaling process and its associated errors. Working from a fine‐scale harvest LAI–NDVI relationship, we collected NDVI data over a 500 m × 500 m catchment in the Swedish Arctic, at resolutions from 0.2 to 9.0 m in a nested sampling design. NDVI scaled linearly, so that NDVI at any scale was a simple average of multiple NDVI measurements taken at finer scales. The LAI–NDVI relationship was scale invariant from 1.5 to 9.0 m resolution. Thus, a single exponential LAI–NDVI relationship was valid at all these scales, with similar prediction errors. Vegetation patches were of a scale of ～0.5 m and at measurement scales coarser than this, there was a sharp drop in LAI variance. Landsat NDVI data for the study catchment correlated significantly, but poorly, with ground‐based measurements. A variety of techniques were used to construct LAI maps, including interpolation by inverse distance weighting, ordinary Kriging, External Drift Kriging using Landsat data, and direct estimation from a Landsat NDVI–LAI calibration. All methods produced similar LAI estimates and overall errors. However, Kriging approaches also generated maps of LAI estimation error based on semivariograms. The spatial variability of this Arctic landscape was such that local measurements assimilated by Kriging approaches had a limited spatial influence. Over scales >50 m, interpolation error was of similar magnitude to the error in the Landsat NDVI calibration. The characterisation of LAI spatial error in this study is a key step towards developing spatio‐temporal data assimilation systems for assessing C cycling in terrestrial ecosystems by combining models with field and remotely sensed data.     

Comparison of the urban heat island intensity quantified by using air temperature and Landsat land surface temperature in Hangzhou,China

This study compared different measures of urban heat island (UHI) intensity, which were calculated using both air temperature (T_air) at a height of 1.5 m and Landsat land surface temperature (LST) in Hangzhou, China. Two UHI-driven indicators (range and magnitude) and two land-cover-driven indicators (urban-rural and urban-agriculture) were calculated to quantify the UHI intensity based on hourly T_air from five stations and fifteen Landsat 5 LST images. Pearson correlation testing and a moving average times series of the previous 30 days were used to investigate the relationship between UHI intensities calculated by different indicators and data. The results indicate that the land-cover-driven indicators explain UHI better than the UHI-driven indicators, while the calculated values of UHI intensity using Landsat LST and hourly T_air are not comparable. We also investigated the influence of weather conditions on UHI intensity. Generally, Landsat-LST-based UHI performs best on hot sunny days, while T_air-based UHI has a better chance during the nighttime following a dry sunny day. This study suggests that the value of UHI intensity can be influenced by the selected indicators, the data used, the acquisition time and the weather conditions. Thus, these factors should be considered when comparing UHI intensity between different cities or quantifying their influences (e.g., population size, land use and land cover change) on UHI intensity.     

基于长时间序列landsat数据的科尔沁沙地土地利用演变分析

以科尔沁沙地沙丘-草甸过渡带区域主要土地覆被类型为研究对象,以1987-2017年多时相Landsat TM/OLI遥感影像解译分类为基础,参考生态学植被演替研究方法,系统分析研究区30年来的土地利用/覆被动态演变规律,研究结果表明：（1）决策树法在复杂下垫面不同覆被类型的同步识别效果较好,所有影像分类精度均达到88%以上,分类效果较好,其中2017年分类精度最高为95.24%,达到了分类研究的要求;（2）研究区存在着"半灌丛-草甸地-灌丛"的植被结构特征,且整体表现为"南进北退"的变化趋势。结合土地利用动态度分析结果表明人类活动干涉下,研究区整体上遵循了半干旱区植被条件改善的一般规律,侧面反映该研究区域生态环境的持续不稳定性和脆弱性;（3）研究区覆被类型发生变化的总面积达到2623.59 hm²,总变化强度为63.76%。其中正向演替的比例为52.61%,以半灌丛面积的持续减小与沙地草甸面积的持续扩张为主要变化特征。但同时,半灌丛转为沙地的面积为184.95 hm²,表明以放牧为主的研究区同时发生着局部的逆行演变;（4）质心迁移结果反映了1987-2017年间,除人为影响较大的林地、草地以及耕地向北迁移外,其他植被类型的质心都有很明显的南迁,主要植被类型重心迁移距离依次由大到小为耕地 > 半灌丛 > 灌丛 > 沙地草甸 > 湿地草甸 > 林地。研究通过记录科尔沁沙地连续扩展的时空模式,展示了遥感-生态和时间序列影像在30 m分辨率下跟踪土地利用/覆被变化的潜力,为提高干旱半干旱区土地利用情况的动态监测效率,开展土地利用/覆被动态演变研究提供参考。     

沙化和退化状态对甘南草地生态系统固碳的影响

陆地生态系统作为全球第二大碳库,其碳收支应对气候变化一直是研究的热点领域.多数研究主要探讨温/湿度、CO2浓度等对陆地生态系统碳循环的影响,而针对草地的沙化、退化对植被整个固碳过程所产生影响的研究相对不足.本研究以30 m×30 m空间分辨率的遥感数据做支撑,参考国家标准GB/T 24255-2009解译草地沙化和退化...