A Quantitative Assessment of Forest Cover Change in the Moulouya River Watershed (Morocco) by the Integration of a Subpixel-Based and Object-Based Analysis of Landsat Data

A quantitative assessment of forest cover change in the Moulouya River watershed (Morocco) was carried out by means of an innovative approach from atmospherically corrected reflectance Landsat images corresponding to 1984 (Landsat 5 Thematic Mapper) and 2013 (Landsat 8 Operational Land Imager). An object-based image analysis (OBIA) was undertaken to classify segmented objects as forested or non-forested within the 2013 Landsat orthomosaic. A Random Forest classifier was applied to a set of training data based on a features vector composed of different types of object features such as vegetation indices, mean spectral values and pixel-based fractional cover derived from probabilistic spectral mixture analysis). The very high spatial resolution image data of Google Earth 2013 were employed to train/validate the Random Forest classifier, ranking the NDVI vegetation index and the corresponding pixel-based percentages of photosynthetic vegetation and bare soil as the most statistically significant object features to extract forested and non-forested areas. Regarding classification accuracy, an overall accuracy of 92.34% was achieved. The previously developed classification scheme was applied to the 1984 Landsat data to extract the forest cover change between 1984 and 2013, showing a slight net increase of 5.3% (ca. 8800 ha) in forested areas for the whole region

How Spatial Heterogeneity of Cover Affects Patterns of Shrub Encroachment into Mesic Grasslands

We used a multi-method approach to analyze the spatial patterns of shrubs and cover types (plant species, litter or bare soil) in grassland-shrubland ecotones. This approach allows us to assess how fine-scale spatial heterogeneity of cover types affects the patterns of Cytisus balansae shrub encroachment into mesic mountain grasslands (Catalan Pyrenees, Spain). Spatial patterns and the spatial associations between juvenile shrubs and different cover types were assessed in mesic grasslands dominated by species with different palatabilities (palatable grass Festuca nigrescens and unpalatable grass Festuca eskia). A new index, called RISES (“Relative Index of Shrub Encroachment Susceptibility”), was proposed to calculate the chances of shrub encroachment into a given grassland, combining the magnitude of the spatial associations and the surface area for each cover type. Overall, juveniles showed positive associations with palatable F. nigrescens and negative associations with unpalatable F. eskia, although these associations shifted with shrub development stage. In F. eskia grasslands, bare soil showed a low scale of pattern and positive associations with juveniles. Although the highest RISES values were found in F. nigrescens plots, the number of juvenile Cytisus was similar in both types of grasslands. However, F. nigrescens grasslands showed the greatest number of juveniles in early development stage (i.e. height<10 cm) whereas F. eskia grasslands showed the greatest number of juveniles in late development stages (i.e. height>30 cm). We concluded that in F. eskia grasslands, where establishment may be constrained by the dominant cover type, the low scale of pattern on bare soil may result in higher chances of shrub establishment and survival. In contrast, although grasslands dominated by the palatable F. nigrescens may be more susceptible to shrub establishment; current grazing rates may reduce juvenile survival

Collaborative Storage Management In Sensor Networks

In this paper, we consider a class of sensor networks where the data is not required in real-time by an observer; for example, a sensor network monitoring a scientific phenomenon for later play back and analysis. In such networks, the data must be stored in the network. Thus, in addition to battery power, storage is a primary resource: the useful lifetime of the network is constrained by its ability to store the generated data samples. We explore the use of collaborative storage technique to efficiently manage data in storage constrained sensor networks. The proposed collaborative storage technique takes advantage of spatial correlation among the data collected by nearby sensors to significantly reduce the size of the data near the data sources. We show that the proposed approach provides significant savings in the size of the stored data vs. local buffering, allowing the network to run for a longer time without running out of storage space and reducing the amount of data that will eventually be relayed to the observer. In addition, collaborative storage performs load balancing of the available storage space if data generation rates are not uniform across sensors (as would be the case in an event driven sensor network), or if the available storage varies across the network.Comment: 13 pages, 7 figure

A Comparison Of Methods For Scaling Field Data For Use In Mapping Dryland Ecosystem Vegetation With Airborne Imaging Spectroscopy

This research investigated scaling methods of field data to interpret aerial surveys for foliar N estimation using imaging spectroscopy. Foliar nitrogen (N) is an indicator of vegetative growth, which is related dryland ecosystem services. We compared four field-based methods to scale sagebrush foliar N estimates from shrub to the plot level (10 m x 10 m) for 21 plots collected in a dryland ecosystem in 2014 and 2015. Partial least squares regression related estimates to imaging spectroscopy variables. Results showed sensitivity to scaling method; pretreatment of imaging spectroscopy signals; subdividing the dataset into years; reducing predictor variables to reduce noise; and number of model iterations. The best performing methods used biomass allometry with density counts or cover estimates with leaf thickness with a log transformation and Savitzky-Golay smoothing method. Models selected different wavelengths as predictors. Several relied on wavelengths in the visual range associated with chlorophyll and few relied on wavelengths in the "red edge" of 800-850 nm. The best performing model used biomass allometry and a subset of wavelengths that consistently performed well across model iterations. This was used to map predicted foliar N values across the Reynolds Creek Experimental Watershed and can be used to support rangeland management

Tree Island Response to Fire and Flooding in the Short-Hydroperiod Marl Prairie Grasslands of the Florida Everglades

Within the marl prairie grasslands of the Florida Everglades, USA, the combined effects of fire and flooding usually lead to very significant changes in tree island structure and composition. Depending on fire severity and post-fire hydroperiod, these effects vary spatially and temporally throughout the landscape, creating a patchy post-fire mosaic of tree islands with different successional states. Through the use of the Normalized Difference Vegetation Index (NDVI) and three predictor variables (marsh water table elevation at the time of fire, post-fire hydroperiod, and tree island size), along with logistic regression analysis, we examined the probability of tree island burning and recovering following the Mustang Corner Fire (May to June 2008) in Everglades National Park. Our data show that hydrologic conditions during and after fire, which are under varying degrees of management control, can lead to tree island contraction or loss. More specifically, the elevation of the marsh water table at the time of the fire appears to be the most important parameter determining the severity of fire in marl prairie tree islands. Furthermore, in the post-fire recovery phase, both tree island size and hydroperiod during the first year after the fire played important roles in determining the probability of tree island recovery, contraction, or loss

Environmental degradation and the demand for children : searching for the vicious circle

The authors explore the hypothesis that--because of the important role children play in collection activities (firewood, water, grazing)--the demand forchildren may increase as local environmental resources are depleted, setting up a vicious circle between resource depletion and population growth. Using a large-scale household data set from Pakistan, with detailed information on fertility and the allocation of time to collection activities, they find that: (i) collection activities absorb a substantial part of household resources--firewood collection accounts for 6.2 percent of household expenditures, valued in collection time; (ii) collection absorbs a quarter of the time of children; (iii) women benefit when there are older children in the household; they work 2.6 hours a week less in household activities for each child aged 10 to 15, and 3.2 hours less for each child over 15; and (iv) there seems to be an inverse relationship between fertility and the availability of firewood; even after controlling for other determinants of fertility in reduced form regressions, the authors show that households that live some distance from firewood have more children, whereas households that live where firewood is more expensive have fewer children.Health Monitoring&Evaluation,Gender and Development,Environmental Economics&Policies,Population&Development,Public Health Promotion,Environmental Economics&Policies,Youth and Governance,Housing&Human Habitats,Educational Sciences,Forestry

Vegetation Modeling of Holocene Landscapes in the Southern Levant

abstract: This dissertation creates models of past potential vegetation in the Southern Levant during most of the Holocene, from the beginnings of farming through the rise of urbanized civilization (12 to 2.5 ka BP). The time scale encompasses the rise and collapse of the earliest agrarian civilizations in this region. The archaeological record suggests that increases in social complexity were linked to climatic episodes (e.g., favorable climatic conditions coincide with intervals of prosperity or marked social development such as the Neolithic Revolution ca. 11.5 ka BP, the Secondary Products Revolution ca. 6 ka BP, and the Middle Bronze Age ca. 4 ka BP). The opposite can be said about periods of climatic deterioration, when settled villages were abandoned as the inhabitants returned to nomadic or semi nomadic lifestyles (e.g., abandonment of the largest Neolithic farming towns after 8 ka BP and collapse of Bronze Age towns and cities after 3.5 ka BP during the Late Bronze Age). This study develops chronologically refined models of past vegetation from 12 to 2.5 ka BP, at 500 year intervals, using GIS, remote sensing and statistical modeling tools (MAXENT) that derive from species distribution modeling. Plants are sensitive to alterations in their environment and respond accordingly. Because of this, they are valuable indicators of landscape change. An extensive database of historical and field gathered observations was created. Using this database as well as environmental variables that include temperature and precipitation surfaces for the whole study period (also at 500 year intervals), the potential vegetation of the region was modeled. Through this means, a continuous chronology of potential vegetation of the Southern Levantwas built. The produced paleo-vegetation models generally agree with the proxy records. They indicate a gradual decline of forests and expansion of steppe and desert throughout the Holocene, interrupted briefly during the Mid Holocene (ca. 4 ka BP, Middle Bronze Age). They also suggest that during the Early Holocene, forest areas were extensive, spreading into the Northern Negev. The two remaining forested areas in the Northern and Southern Plateau Region in Jordan were also connected during this time. The models also show general agreement with the major cultural developments, with forested areas either expanding or remaining stable during prosperous periods (e.g., Pre Pottery Neolithic and Middle Bronze Age), and significantly contracting during moments of instability (e.g., Late Bronze Age).Dissertation/ThesisPh.D. Geography 201

Species richness and abundance estimates of small mammals in Zaraninge coastal forest in Tanzania

A study on small mammals

Soil properties of North Iberian wet heathlands in relation to climate, management and plant community

Financiado para publicación en acceso aberto: Universidade da Coruña/CISUG[Abstract] Background and aims: Heathlands are a broad vegetation type characterized by the dominance of evergreen shrub species that thrive on nutrient-poor soils, thus sensitive to small changes in soil conditions. Here we aimed to identify soil gradients related to climate, management and main species in wet heathlands. Methods: Soil nutrient levels, organic matter and acidity were studied at two soil depths on ninety plots from 18 sites in Erica mackayana wet heaths of NW Iberian Peninsula, in relation to presence and cover of structural plant species (shrubs and graminoids) at two scales: plot and site (landscape) scale. Results: We identified one main soil gradient explained by soil organic matter (SOM), the effective cation exchange complex (eCEC), available phosphorus (P), and Aluminium-Calcium ratio (Al:Ca). Cattle density had a positive correlation with the main gradient in the surface layer, all other climate and management factors were unrelated to soil conditions. Molinia caerulea had a positive relation with SOM, eCEC, basic cations and low Al:Ca ratio. Erica cinerea showed the opposite reaction at both scales. Ulex gallii showed a negative correlation with C:N ratio at the plot scale and deeper layer. Conclusion: SOM accumulation, low nutrient levels and Al toxicity explain the uniqueness of E. mackayana heathland vegetation and soils. Main indicator species react to soil conditions at plot and landscape scales. Cattle density correlated positively with soil nutrient levels, but density of wild ponies is unrelated to soil conditions. Large herbivores, especially ponies, are needed for conservation management of these heathlands