The road to deforestation: An assessment of forest loss and its causes in Basho Valley, Northern Pakistan

Deforestation in the Himalayas is generally seen as caused primarily by population growth. Based on interviews and the analysis of satellite images, we critically examine this view using Basho Valley in the Western Himalayas of Pakistan as a case study. Our findings indicate that the forest of Basho has been reduced by at least 50% after the valley was opened up through the construction of a link road in 1968. Large-scale legal and illegal commercial harvesting was carried out after the construction of the road. While legal commercial harvesting was stopped in 1987, illegal harvesting has since continued with the involvement of the Forest Department. The findings of this study do not support theories in which deforestation is attributed to rapid population growth. Instead, mismanagement and illegal commercial harvesting endorsed by the Forest Department have been the main causes of deforestation in Basho Valley.     

A soil acidification study using the PROFILE model on two contrasting regions in Switzerland

The steady-state soil chemistry model PROFILE was used to calculate the chemical status of forest soils under present deposition loads for two areas with dissimilar ecosystem properties. Two regions in Switzerland, with contrasting bedrock geology were selected to be investigated in detail: 88 locations in the Jura Mountains, representative for carbonate bedrock and 91 locations in the Ticino Area dominated by metamorphic crystalline host rocks. Weathering rates calculated for the key regions cover the tremendous range between 0.013 and 25 keq ha⁻¹ yr⁻¹. In the Ticino Area, the effect of increased abundance of relatively fast weathering silicates (epidote, hornblende and plagioclase) on the weathering rate is apparently masked by the total effects of the physical conditions applied and by the variation in the deposition load. In the Jura Mountains, generally high weathering rates occur with about 50% of the sites yielding rates above 1 keq ha⁻¹ yr⁻¹. In many of the sites investigated, however, carbonates have already been dissolved completely in the soil horizons of interest resulting in very low weathering rates. The critical load of actual acidity was calculated according to: CL_Acidity=R_Weathering−ANC_Leaching, where alkalinity leaching is estimated by keeping the base cation to aluminum molar ratio at the critical limit of 1 at steady-state. The minimum critical load calculated was 0.2 keq ha⁻¹ yr⁻¹ and the maximum was 6.2 keq ha⁻¹ yr⁻¹. Comparing the cumulative frequency distributions of critical loads of actual acidity for forest soils in the individual areas it can be seen that the differences between the key regions are less substantial than with the weathering rates. Critical loads of acidity for the Ticino Area range from 1 to 3.9 keq ha⁻¹ yr⁻¹. Sites yielding the lowest critical loads of acidity are observed in the Jura Mountains. Among these apparent sensitive soils are soils with intermediate or high weathering rates, although it has depleted topsoil layers. Within the context of this model application, it becomes apparent that the sensitivity of these soils with respect to acidification is also governed by the alkalinity leaching term and not only by the susceptibility of its minerals to weathering.     

The Gunnison's prairie dog structures a high desert grassland landscape as a keystone engineer

The influence of landscape spatial structure on ecological processes has recently received much attention. Comparisons are made here between the spatial structure of grasslands, and active and extirpated Gunnison's prairie dog (Cynomys gunnisoni Hollister) towns at the Petrified Forest National Park, Arizona, U.S.A. The spatial structure of bare ground was quatified using a box-counting technique to extract landscape fractal dimensions, D, and bare-ground patch size. These landscapes are fractal, and active prairie dog towns had higher fractal dimensions, i.e. a more homogeneous spatial structure as D approaches 2, than inactive towns, which had higher fractal dimensions than unmodified grasslands. Morisita's index suggested that shrubs were more randomly distributed on prairie dog towns and more aggregated on grassland habitats. The different spatial distributions of bare ground and shrubs have the potential to influence resource distributions between these habitats for both prairie dogs and other fauna. Consequently, the presence of prairie dogs in these grasslands increases grassland landscape heterogeneity at large spatial scales, potentially enhancing beta diversity.     

Zircon ages and Nd isotopic and chemical compositions of orthogneisses from the Black Forest, Germany: evidence for a Cambrian magmatic arc

 Single zircon U–Pb dating combined with ²⁰⁷Pb/²⁰⁶Pb ages obtained by the evaporation method constrains the emplacement of tonalitic, trondhjemitic, and granodioritic orthogneisses of the Moldanubian zone in the Black Forest between 500 and 510 Ma. Two detrital zircon populations of 1.9 and 1.6 Ga indicate Early-Middle Proterozoic material in the former setting of the basement. The initial e_Nd values range from –0.1 to –3.4 and mean crustal residence ages of 1.0–1.4 Ga are consistent with involvement of Early-Middle Proterozoic crust, and a subordinate juvenile component probably originating from subduction-related melting of the mantle. The orthogneisses have fractionated REE patterns and slightly higher K₂O/Na₂O ratios than typical low-K tonalite–trondhjemite–granite suites. The chemical data are interpreted as evidence for melting of amphibolite and contributions from evolved crust. The emplacement of the orthogneisses was superceded by a high-temperature metamorphic event at ∼480 Ma which we interpret as a result of lithospheric thinning in a marginal basin behind a Cambrian magmatic arc. Received: 29 March 1999 / Accepted: 25 August 1999     

茂兰森林生态系统对岩溶环境的适应与调节

通过对贵州茂兰森林区岩溶作用下森林生态特点的研究表明,岩溶山区由于岩溶作用导致了地貌、土壤、水分等状况的特异性,其森林生态系统行为对岩溶作用也作出了相应的响应,如森林生态系统虽然生物多样性、物种的特有性仍然较好,但物种以钙生性、旱生性为主,生产力低下,森林生态系统主要通过诸如无性更新、不间断随时更新等方式来适应严酷的岩溶环境。因此要保持和恢复岩溶石山区森林生态系统生产力,其首要的基础研究问题是岩溶作用影响下森林植物的生境胁迫的机制及其动态,森林植物对这种胁迫的适应性及其基因调控机理。      

Double funnelling in a mature coastal British Columbia forest: spatial patterns of stemflow after infiltration

Many studies have focused on the amount of stemflow in different forests and for different rainfall events, but few studies have focused on how stemflow intensity varies during events or the infiltration of stemflow into the soil. Stemflow may lead to higher water delivery rates at the base of the tree compared with throughfall over the same area and fast and deeper infiltration of this water along roots and other preferential flow pathways. In this study, stemflow amounts and intensities were measured and blue dye experiments were conducted in a mature coniferous forest in coastal British Columbia to examine double funnelling of stemflow. Stemflow accounted for only 1% of precipitation and increased linearly with event total precipitation. Funnelling ratios ranged from less than 1 to almost 20; smaller trees had larger funnelling ratios. Stemflow intensity generally was highest for periods with high‐intensity rainfall later in the event. The maximum stemflow intensities were higher than the maximum precipitation intensities. Dye tracer experiments showed that stemflow infiltrated primarily along roots and was found more frequently at depth than near the soil surface. Lateral flow of stemflow was observed above a dense clay layer for both the throughfall and stemflow experiments. Stemflow appeared to infiltrate deeper (122 cm) than throughfall (85 cm), but this difference was in part a result of site‐specific differences in maximum soil depth. However, the observed high stemflow intensities combined with preferential flow of stemflow may lead to enhanced subsurface stormflow. This suggests that even though stemflow is only a very minor component of the water balance, it may still significantly affect soil moisture, recharge, and runoff generation. Copyright © 2016 John Wiley & Sons, Ltd.     

Forest cover classification using Landsat ETM+ data and time series MODIS NDVI data

Forest cover plays a key role in climate change by influencing the carbon stocks, the hydrological cycle and the energy balance. Forest cover information can be determined from fine-resolution data, such as Landsat Enhanced Thematic Mapper Plus (ETM+). However, forest cover classification with fine-resolution data usually uses only one temporal data because successive data acquirement is difficult. It may achieve mis-classification result without involving vegetation growth information, because different vegetation types may have the similar spectral features in the fine-resolution data. To overcome these issues, a forest cover classification method using Landsat ETM+ data appending with time series Moderate-resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (NDVI) data was proposed. The objective was to investigate the potential of temporal features extracted from coarse-resolution time series vegetation index data on improving the forest cover classification accuracy using fine-resolution remote sensing data. This method firstly fused Landsat ETM+ NDVI and MODIS NDVI data to obtain time series fine-resolution NDVI data, and then the temporal features were extracted from the fused NDVI data. Finally, temporal features combined with Landsat ETM+ spectral data was used to improve forest cover classification accuracy using supervised classifier. The study in North China region confirmed that time series NDVI features had significant effects on improving forest cover classification accuracy of fine resolution remote sensing data. The NDVI features extracted from time series fused NDVI data could improve the overall classification accuracy approximately 5% from 88.99% to 93.88% compared to only using single Landsat ETM+ data.     

A forestry GIS-based study on evaluating the potential of imaging spectroscopy in mapping forest land fertility

Fertility, or the availability of nutrients and water, controls forest productivity. It affects its carbon sequestration, and thus the forest's effect on climate, as well as its commercial value. Although the availability of nutrients cannot be measured directly using remote sensing methods, fertility alters several vegetation traits detectable from the reflectance spectra of the forest stand, including its pigment content and water stress. However, forest reflectance is also influenced by other factors, such as species composition and stand age. Here, we present a case study demonstrating how data obtained using imaging spectroscopy is correlated with site fertility. The study was carried out in Hyytiälä, Finland, in the southern boreal forest zone. We used a database of state-owned forest stands including basic forestry variables and a site fertility index. To test the suitability of imaging spectroscopy with different spatial and spectral resolutions for site fertility mapping, we performed two airborne acquisitions using different sensor configurations. First, the sensor was flown at a high altitude with high spectral resolution resulting in a pixel size in the order of a tree crown. Next, the same area was flown to provide reflectance data with sub-meter spatial resolution. However, to maintain usable signal-to-noise ratios, several spectral channels inside the sensor were combined, thus reducing spectral resolution. We correlated a number of narrowband vegetation indices (describing canopy biochemical composition, structure, and photosynthetic activity) on site fertility. Overall, site fertility had a significant influence on the vegetation indices but the strength of the correlation depended on dominant species. We found that high spatial resolution data calculated from the spectra of sunlit parts of tree crowns had the strongest correlation with site fertility.     

Historical forest biomass dynamics modelled with Landsat spectral trajectories

Estimation of forest aboveground biomass (AGB) is informative of the role of forest ecosystems in local and global carbon budgets. There is a need to retrospectively estimate biomass in order to establish a historical baseline and enable reporting of change. In this research, we used temporal spectral trajectories to inform on forest successional development status in support of modelling and mapping of historic AGB for Mediterranean pines in central Spain. AGB generated with ground plot data from the Spanish National Forest Inventory (NFI), representing two collection periods (1990 and 2000), are linked with static and dynamic spectral data as captured by Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) sensors over a 25 year period (1984–2009). The importance of forest structural complexity on the relationship between AGB and spectral vegetation indices is revealed by the analysis of wavelet transforms. Two-dimensional (2D) wavelet transforms support the identification of spectral trajectory patterns of forest stands that in turn, are associated with traits of individual NFI plots, using a flexible algorithm sensitive to capturing time series similarity. Single-date spectral indices, temporal trajectories, and temporal derivatives associated with succession are used as input variables to non-parametric decision trees for modelling, estimation, and mapping of AGB and carbon sinks over the entire study area. Results indicate that patterns of change found in Normalized Difference Vegetation Index (NDVI) values are associated and relate well to classes of forest AGB. The Tasseled Cap Angle (TCA) index was found to be strongly related with forest density, although the related patterns of change had little relation with variability in historic AGB. By scaling biomass models through small (∼2.5 ha) spatial objects defined by spectral homogeneity, the AGB dynamics in the period 1990–2000 are mapped (70% accuracy when validated with plot values of change), revealing an increase of 18% in AGB irregularly distributed over 814 km² of pines. The accumulation of C calculated in AGB was on average 0.65 t ha⁻¹ y⁻¹, equivalent to a fixation of 2.38 t ha⁻¹ y⁻¹ of carbon dioxide.     

Time-series analysis of multi-resolution optical imagery for quantifying forest cover loss in Sumatra and Kalimantan,Indonesia

Monitoring loss of humid tropical forests via remotely sensed imagery is critical for a number of environmental monitoring objectives, including carbon accounting, biodiversity, and climate modeling science applications. Landsat imagery, provided free of charge by the U.S. Geological Survey Center for Earth Resources Observation and Science (USGS/EROS), enables consistent and timely forest cover loss updates from regional to biome scales. The Indonesian islands of Sumatra and Kalimantan are a center of significant forest cover change within the humid tropics with implications for carbon dynamics, biodiversity maintenance and local livelihoods. Sumatra and Kalimantan feature poor observational coverage compared to other centers of humid tropical forest change, such as Mato Grosso, Brazil, due to the lack of ongoing acquisitions from nearby ground stations and the persistence of cloud cover obscuring the land surface. At the same time, forest change in Indonesia is transient and does not always result in deforestation, as cleared forests are rapidly replaced by timber plantations and oil palm estates. Epochal composites, where single best observations are selected over a given time interval and used to quantify change, are one option for monitoring forest change in cloudy regions. However, the frequency of forest cover change in Indonesia confounds the ability of image composite pairs to quantify all change. Transient change occurring between composite periods is often missed and the length of time required for creating a cloud-free composite often obscures change occurring within the composite period itself. In this paper, we analyzed all Landsat 7 imagery with <50% cloud cover and data and products from the Moderate Resolution Imaging Spectroradiometer (MODIS) to quantify forest cover loss for Sumatra and Kalimantan from 2000 to 2005. We demonstrated that time-series approaches examining all good land observations are more accurate in mapping forest cover change in Indonesia than change maps based on image composites. Unlike other time-series analyses employing observations with a consistent periodicity, our study area was characterized by highly unequal observation counts and frequencies due to persistent cloud cover, scan line corrector off (SLC-off) gaps, and the absence of a complete archive. Our method accounts for this variation by generating a generic variable space. We evaluated our results against an independent probability sample-based estimate of gross forest cover loss and expert mapped gross forest cover loss at 64 sample sites. The mapped gross forest cover loss for Sumatra and Kalimantan was 2.86% of the land area, or 2.86 Mha from 2000 to 2005, with the highest concentration having occurred in Riau and Kalimantan Tengah provinces.