Preface to the Princeton Landmarks in Biology Edition vii Preface xi Symbols Used xiii 1. The Importance of Islands 3 2. Area and Number of Speicies 8 3. Further Explanations of the Area-Diversity Pattern 19 4. The Strategy of Colonization 68 5. Invasibility and the Variable Niche 94 6. Stepping Stones and Biotic Exchange 123 7. Evolutionary Changes Following Colonization 145 8. Prospect 181 Glossary 185 References 193 Index 201

The Theory of Island Biogeography

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

Unmanned aerial vehicles have become popular platforms for remote-sensing applications, particularly when spaceborne technology, manned airborne techniques, and in situ methods are not as efficient...

Recent applications of unmanned aerial imagery in natural resource management

Assessment of surface urban heat islands (SUHI) has been hampered by the lack of a consistent framework to permit consistent interpretation between cities. Local Climate Zones (LCZ) are a universal description of local scale landscape types based on expected variation at neighbourhood scale (≥1km2) in and around cities. In this study, we investigate the suitability of the LCZ scheme for SUHI studies based on 50 cities from across the globe. For comparability we use an annual temperature cycle model for MODIS land surface temperature (LST) at different overpass times and multi-year mean Landsat 8 LST. The SUHI analysis shows significant differences in the intra-urban estimate of SUHI for different built LCZ types. Substantial variability of SUHI within LCZ classes and between cities exists and SUHI patterns vary by time of day. Landsat derived estimates have very high correlations to those from MODIS at a similar time. The use of an LCZ approach combined with annual SUHI estimates provides a promising approach for a consistent and comprehensive SUHI analysis framework subject to further work to assess the spatial scale of matching LST and LCZ data, filter for topographic effects, and include the phenological status.

SUHI analysis using Local Climate Zones—A comparison of 50 cities

Large connected landscapes are paramount to maintain top predator populations. Across their range, tiger (Panthera tigris) populations occur in small fragmented patches of habitat, often isolated by large distances in human-dominated landscapes. We assessed connectivity between 16 protected areas (PAs) in central India, a global priority landscape for tiger conservation, using data on land use and land cover, human population density, and transportation infrastructure. We identified and prioritized movement routes using a combination of least-cost corridor modeling and circuit theory. Our analyses suggest that there are several opportunities to maintain connectivity in this landscape. We mapped a total of thirty-five linkages in the region and calculated metrics to estimate their quality and importance. The highest quality linkages as measured by the ratio of cost-weighted distance to Euclidean distance are Kanha–Phen/Bandhavgarh–SanjayGhasidas/Melghat–Satpura, and cost-weighted distance to least-cost path length are Nawegaon–Tadoba/Achanakmar–SanjayGhasidas/Kanha–Phen. We used current flow centrality to evaluate the contribution of each PA and linkage toward facilitating animal movement. Values are highest for Kanha and Pench tiger reserves, and the linkages between Kanha–Phen, Kanha–Pench, and Pench–Satpura, suggesting that these PAs and linkages play a critical role in maintaining connectivity in central India. In addition, smaller areas such as Bor, Nawegaon, and Phen have high centrality scores relative to their areas and thus may act as important stepping stones. We mapped pinch points, which are sections of the linkages where tiger movement is restricted due to unfavorable habitat, transportation networks, human habitation, or a combination of factors. Currently, very limited data exist on tiger movement outside of PAs to validate model results. Regional-scale connectivity mapping efforts can assist managers and policy makers to develop strategic plans for balancing wildlife conservation and other land uses in the landscape.

Connecting the dots: mapping habitat connectivity for tigers in central India

The Tiger (Panthera tigris) population in India has undergone a sharp decline during the last few years. Of the number of factors attributed to this decline, habitat fragmentation has been the most worrisome. Wildlife corridors have long been a subject of discussion amongst wildlife biologists and conservationists with contrasting schools of thought arguing their merits and demerits. However, it is largely believed that wildlife corridors can help minimize genetic isolation, offset fragmentation problems, improve animal dispersal, restore ecological processes and reduce man animal conflict. This study attempted to evaluate the possibilities of identifying a suitable wildlife corridor between two very important wildlife areas of central India – the Kanha National Park and the Pench National Park – with tiger as the focal species. Geographic Information System (GIS) centric Least Cost Path modeling was used to identify likely routes for movement of tigers. Habitat suitability, perennial water bodies, road density, railway tracks, human settlement density and total forest edge were considered as key variables influencing tiger movement across the Kanha-Pench landscape. Each of these variables was weighted in terms of relative importance through an expert consultation process. Using different importance scenarios, three alternate corridor routes were generated of which one was identified as the most promising for tiger dispersal. Weak links – where cover and habitat conditions are currently sub-optimal – were flagged on the corridor route. Interventions aimed at augmenting the identified corridor route have been suggested using accepted wildlife corridor design principles. The involvement of local communities through initiatives such as ecotourism has been stressed as a crucial long term strategy for conservation of the Kanha-Pench wildlife corridor. The results of the study indicate that restoration of the identified wildlife corridors between the two protected areas is technically feasible.

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Opportunities of Habitat Connectivity for Tiger (Panthera tigris) between Kanha and Pench National Parks in Madhya Pradesh, India

In 2015, the government of India allocated more than $1 billion for the development of 100 smart cities. These cities are forecast to help alleviate the mounting pressure being felt in Indi...

India’s “smart” cities mission: A preliminary examination into India’s newest urban development policy

Planning for sustainable cities generally focuses on compact, human-scale cities. The urban paradigms underlying each city produce morphologies which generate a distinctive local urban climate. In this paper, four sub-cities in Delhi NCR, India, are classified using local climate zone (LCZ), and then analysed for thermal performance and compactness. These sub-cities are broadly classified as a garden city (LCZ 5A), a resettlement colony (LCZ 3), a mixed land-use city (LCZ 5), and an industrial city (LCZ 56). The surface UHI (UHISurf) is estimated using Google Earth Engine with MODIS, canopy layer UHI (UHIUCL) with meteorological data, and density using Spacematrix. The nighttime UHIUCL is 7.52 °C (LCZ 5 and LCZ 5A) and the UHISurf is 5.2 °C (LCZ 5 and LCZ D). A major apprehension is the residual temperature at sunrise (5–8 °C) leading to high heat stress and detrimental health impacts. The heating and cooling rate, reduced by a factor of three is observed (LCZ 5–0.25 °C/h). The least UHI is experienced by LCZ 5A and the built density is highest in LCZ 3. The mixed-land use (LCZ 5) city performs poorly, whereas the industrial city (LCZ 56) performs optimally on both thermal and density scales.

Urban heat island effect of a polynuclear megacity Delhi – Compactness and thermal evaluation of four sub-cities

Environmental monitoring using external and Smartphone-interfaced wireless sensors has been widely used in the past. The roadblocks start emerging when we use on-board sensors in off-the-shelf Smartphones to estimate context aware environmental parameters like ambient temperature, humidity and atmospheric pressure. In this work, we evaluate the sensitivity and accuracy of the on-board ambient temperature sensor under various circumstances and measure its performance against standardized weather monitoring equipment. Additionally, we identify the roles of several internal and external factors that affect the temperature data. Such an investigation is motivated by the need of pervasive temperature sensing to power Smart HVAC environments and for weather crowdsourcing. Our experiments reveal that while the on-board temperature sensors have great potential, using them for large scale data collection still requires significant work.

Contextual sensitivity of the ambient temperature sensor in Smartphones

The arctic tundra vegetation classified in the study area, Toolik Lake Field Station, Alaska, was relatively small in stature (with varying species growing in clusters) and must therefore be placed in different communities. This study compared different digital image processing classification techniques, including unsupervised, supervised (using spectral and spatial features), and expert systems. The dataset was a pan-sharpened 5 × 5 meter spatial resolution SPOT image. Accuracy assessments based on field inspections of each final map were performed. The expert system classification yielded the highest overall accuracy of 74.66%, with a Kappa coefficient of agreeement of 0.6725.

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Prasad Pathak

Papers

Opportunities of Habitat Connectivity for Tiger (Panthera tigris) between Kanha and Pench National Parks in Madhya Pradesh, India

India’s “smart” cities mission: A preliminary examination into India’s newest urban development policy

Urban heat island effect of a polynuclear megacity Delhi – Compactness and thermal evaluation of four sub-cities

Contextual sensitivity of the ambient temperature sensor in Smartphones

Comparison of Digital Image Processing Techniques for Classifying Arctic Tundra