Soil Chemical Analysis

Beginning with Emlen (1966) and MacArthur and Pianka (1966) and extending through the last ten years, several authors have sought to predict the foraging behavior of animals by means of mathematical models. These models are very similar,in that they all assume that the fitness of a foraging animal is a function of the efficiency of foraging measured in terms of some "currency" (Schoener, 1971) -usually energy- and that natural selection has resulted in animals that forage so as to maximize this fitness. As a result of these similarities, the models have become known as "optimal foraging models"; and the theory that embodies them, "optimal foraging theory." The situations to which optimal foraging theory has been applied, with the exception of a few recent studies, can be divided into the following four categories: (1) choice by an animal of which food types to eat (i.e., optimal diet); (2) choice of which patch type to feed in (i.e., optimal patch choice); (3) optimal allocation of time to different patches; and (4) optimal patterns and speed of movements. In this review we discuss each of these categories separately, dealing with both the theoretical developments and the data that permit tests of the predictions. The review is selective in the sense that we emphasize studies that either develop testable predictions or that attempt to test predictions in a precise quantitative manner. We also discuss what we see to be some of the future developments in the area of optimal foraging theory and how this theory can be related to other areas of biology. Our general conclusion is that the simple models so far formulated are supported are supported reasonably well by available data and that we are optimistic about the value both now and in the future of optimal foraging theory. We argue, however, that these simple models will requre much modification, espicially to deal with situations that either cannot easily be put into one or another of the above four categories or entail currencies more complicated that just energy.

Citation classic - optimal foraging - a selective review of theory and tests

With the availability of multisensor, multitemporal, multiresolution and multifrequency image data from operational Earth observation satellites the fusion of digital image data has become a valuable tool in remote sensing image evaluation. Digital image fusion is a relatively new research field at the leading edge of available technology. It forms a rapidly developing area of research in remote sensing. This review paper describes and explains mainly pixel based image fusion of Earth observation satellite data as a contribution to multisensor integration oriented data processing.

Multisensor image fusion in remote sensing: Concepts, methods and applications

Thank you very much for downloading remote sensing and image interpretation. As you may know, people have look hundreds times for their favorite novels like this remote sensing and image interpretation, but end up in malicious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they are facing with some malicious virus inside their computer. remote sensing and image interpretation is available in our digital library an online access to it is set as public so you can get it instantly. Our book servers spans in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Merely said, the remote sensing and image interpretation is universally compatible with any devices to read.

Remote Sensing And Image Interpretation

Global Biodiversity Assessment

Network theoretic approach has been used to model and study the flow of ecological information, growth and connectivity on landscape level of anemochory plant species Abied pindrow, Betula utilis and Taxus wallichiana in the Western Himalaya region. A network is formally defined and derived for seed dispersion model of aforementioned species where vertices represent habitat patches which are connected by an edge if the distance between the patches is less than a threshold distance. We define centrality of a network and computationally identify the habitat patches that are central to the process of seed dispersion to occur across the network. We find that the network of habitat patches is a scale free network and at the same time it also displays small world property characterized by high clustering and low average shortest path length. Due to high clustering, the spread of species is locally even as seed disperse mutually among the member vertices of a cluster. Also since every vertex is only a short number of steps away from every other vertex, the species rapidly covers all the habitat patches in the component. Also due to presence of hubs in the network the spread of species is greatly boosted whenever the species establish and thrive in a hub patch and disperse to adjacent patches. However, the network is not modular due to geographical constraints, and is is negatively assortative as the high degree vertices are connected to vertices of low degree.

A network theoretic study of ecological connectivity in Western Himalayas

Forest fires in Uttarakhand state have considerable economic, social and environmental impacts on humans and biodiversity. Forest fire danger indices are important tools for mitigating and suppressing forest fires, but, operational fire danger index system has not been developed for the India. In general, Fire danger indices have been developed based on the parameters which are associated for the cause of ignition, spreading of forest fires. These properties include forest fuel type, topographic conditions and moisture conditions. Vegetation and topographic conditions are static, i.e. they do not change frequently, whereas moisture conditions are dynamic. Dynamic properties such as air temperature, relative humidity, wind speed changes regularly in a day. In this study, Static Fire danger Index has been developed using MODIS Land cover type yearly L3 global 500 m SIN grid (MCD12Q1) and ASTER GDEM datasets. International Geosphere-Biosphere Programme (IGBP) land cover type has been generated from MCD12Q1, which has been used to compute the forest fuel type index based on historical fire data. Slope danger index, Aspect danger index, Elevation danger index and Terrain rugged Index has been computed from the ASTER GDEM datasets. Finally, Static Fire Danger Index has been developed by integrating the above mentioned indices. Estimated accuracy of static fire danger index was around 95%, i.e. developed static fire danger index was accurately model the fire danger over the study area.

Developing the static fire danger index using geospatial technology

The global COVID-19 pandemic has resulted in a complete lockdown of economic activities and movement across the world This provides an opportunity to evaluate the impact of minimal anthropogenic activities on forest fire occurrences in the Western Himalaya, India Significant reduction of 83 4% in the cumulative fire incidences during 24 March to 5 May 2020 was observed in this region compared to the average of fire incidences during the corresponding period of 2006-20 Though during the current lockdown period, precipitation was high (similar to 281 mm) compared to the average for the last 15 years (similar to 125 mm), it did not contribute to the build-up of soil moisture Comparatively higher NDVI (by 30 59%) and EVI (by 12 18%) in the lockdown phase unlike the average of previous years which showed declining trend, indicates that the lockdown provided an opportunity for the canopy to sustain and have higher vigour;this was not visible earlier due to fire incidences The present study emphasizes that anthropogenic activities play a major role in forest fire incidences in this region

COVID-19 lockdown a window of opportunity to understand the role of human activity on forest fire incidences in the Western Himalaya, India

Information about the spatial distribution of the different tree species is important for sustainable ecosystem management and planning in the western Himalaya. Remote sensing has proved to be useful to assess the spatial and qualitative distribution of vegetation cover over large areas. Present investigation has been carried out to discriminate three different gregarious forest types, i.e. sal (Shorea robusta), chir pine (Pinus roxburghii) and oak (Quercus spp.) in part of western Himalaya. The use of existing classical classifiers has limitation in classification of overlapping classes and in mixed vegetation formations. To overcome this, fuzzy-based possibilistic C-means (PCM) classifier was used to separate the classes. Temporal Landsat 8 imagery (representing the different phenological states) has been used to classify the three forest types. Phenological information and spectral variability were used to select the best suitable dates, i.e. temporal NDVI to use in PCM classifier. It was obser...

https://tandfonline.com/doi/pdf/10.1080/22797254.2017.1379363

Applicability of NDVI temporal database for western Himalaya forest mapping using Fuzzy-based PCM classifier

The long-term vegetation pattern in landslide-prone regions is studied using simulation and modeling. A simulator is developed to study the impact of landslides on vegetation status. The first part of the model deals with simulation of the effects of rainfall, earthquakes, and deforestation in the creation of landslides and the concomitant damage to vegetation. The second part is a deterministic model of vegetation regeneration. The authors assume that the interarrival time of earthquakes, the intensity of these earthquakes, and rainfall intensity are stochastic in nature and that the earthquake frequency is independent of earthquake intensity. An estimate is made of the damage to vegetation due to the occurrence of landslides under the combined influence of earthquakes, rainfall, and deforestation. After the ecosystem parameters get modified due to the damage, the vegetation status is recalculated for the annual change according to the vegetation regeneration model.

Arijit Roy

Papers

A network theoretic study of ecological connectivity in Western Himalayas

Developing the static fire danger index using geospatial technology

COVID-19 lockdown a window of opportunity to understand the role of human activity on forest fire incidences in the Western Himalaya, India

Applicability of NDVI temporal database for western Himalaya forest mapping using Fuzzy-based PCM classifier

Computer Simulation of Long-Term Vegetation Status in Landslide-Prone Areas in the Himalayan Region: