Geographic Information from Social Network Sites

Graduate Student, Geography The University of KansasPlatinum Sponsors Coca-Cola Gold Sponsors KU Department of Geography KU Institute for Policy & Social Research KU Libraries GIS and Data Services State of Kansas Data Access and Support Center (DASC) Wilson & Company Engineers and Architects Silver Sponsors Bartlett & West Kansas Applied Remote Sensing Program KansasView Bronze Sponsors Garmin KU Biodiversity Institut

Discovering and developing primary biodiversity data from social networking sites

An ever-increasing need exists for fine-scale biodiversity occurrence records for a broad variety of research applications in biodiversity and science more generally. Even though large-scale data aggregators like GBIF serve such data in large quantities, major gaps and biases still exist, both in taxonomic coverage and in spatial coverage. To address these gaps, in this dissertation, I explored social networking sites (SNS) as a rich potential source of additional biodiversity occurrence records. In my first chapter, I explored the idea of discovering, extracting, and organizing massive numbers of biodiversity occurrence records now available on SNSs. I presented a proof-of-concept with Flickr as the SNS and Snowy Owls (Bubo scandiacus) and Monarch Butterflies (Danaus plexippus) as target species. The methods presented in this chapter can easily be used for any other SNS, region, or species group. These approaches are broadly applicable to animal and plant groups that are photographed, and that can be identified from photographs with some degree of confidence (e.g., birds, butterflies, cetaceans, orchids, dragonflies, amphibians, and plants). SNS thus offer a rich new source of biodiversity data. To understand the strengths and weaknesses of biodiversity data, we need effective tools by which to explore and visualize these data. I developed a suite of such tools in an R package called bdvis, which is described in chapter two. The package allows users to explore spatial, temporal, and taxonomic dimensions of biodiversity data sets to highlight gaps and identify strengths. In the third chapter, I explored Flickr further as a source of biodiversity data for the birds of the world, to assess the potential of augmenting the largest portal to biodiversity occurrence data, i.e., the Global Biodiversity Information Facility (GBIF). GBIF provides access to ~190 x 106 bird records, compared to ~7 x 106 that I could discover from Flickr, out of which only ~1.3 x 106 were geotagged. However, the Flickr data showed the potential to add to knowledge about birds in terms of geographic, taxonomic, and temporal dimensions, as Flickr data tended to be complementary to the GBIF-derived information. Finally, I developed a case study to investigate the quantity of records existing, and the quality of identifications by users on Flickr. I developed a detailed case study of Indian swallowtail butterflies, and implemented a crowd-sourcing platform to recruit identification expertise and apply it to butterfly photographs from the SNS. Results were encouraging, with 93% correct identities for records of this family of butterflies from across India

Geographic Manifestation of Spanish Moss Physiology Across The Americas

Graduate Student, Ecology and Evolutionary Biology, The University of KansasPlatinum Sponsors Coca-Cola Gold Sponsors KU Department of Geography KU Institute for Policy & Social Research KU Libraries GIS and Data Services State of Kansas Data Access and Support Center (DASC) Wilson & Company Engineers and Architects Silver Sponsors Bartlett & West Kansas Applied Remote Sensing Program KansasView Bronze Sponsors Garmin KU Biodiversity Institut

Effectiveness of Medicinal Plant Conservation Areas in Western Ghats, India

Graduate Student, Department of Ecology and Evolutionary Biology, The University of KansasPlatinum Sponsors KU Institute for Policy & Social Research Gold Sponsors Bartlett & West KU Department of Geography KU Libraries State of Kansas Data Access and Support Center (DASC) Silver Sponsors Kansas Biological Survey KU Center for Global & International Studies KU Environmental Studies Program Bronze Sponsors Global Information Systems KU Center for Remote Sensing of Ice Sheets (CReSIS) TREKK Design Group, LL

Physiological constraints on geographic distributions of species

Understanding species’ geographic distributions constitutes a major priority in biodiversity science, biogeography, conservation biology, and evolutionary biology. Species’ geographic distribution are shaped by abiotic (climate) factors, biotic (e.g., resources for survival, competitors) factors, and dispersal factors. In this dissertation, I have used physiological parameters measured in the laboratory under controlled conditions to understand constraints on species’ distributions. In my first chapter, I explored how parameters documented in detailed physiological studies could be used to understand the constraints on the geographic distribution of Spansh moss (Tillandsia usneoides). I used four physiological parameters of Spanish moss that circumscribe optimal conditions for the species for survival and growth. Using high-temporal-resolution climate data, optimal and non-optimal areas in the species’ geographic distribution could be identified. My results indicated that Spanish moss survives under suboptimal conditions for few days in many parts of its geographic distribution, although numbers of days differed for various physiological parameters. Continuing from the first chapter’s results, I investigated whether optimal physiological parameters are available for Spanish moss populations specifically during the flowering/fruiting season. Flowering/fruiting season is an important life stage for plant species, as it is during this period that the plant produces new recruits for maintaining populations. Results in this chapter indicated that flowering/fruiting period of Spanish moss frequently is under suboptimal conditions, but that the flowering period tends to be tuned such that Spanish moss populations receive at least one optimal physiological parameter, and generally the parameter emphasized is that of minimum temperature. In the third and final chapter, I analyzed 33 anuran species for the critical maximum temperature parameter (CTmax). CTmax plays a crucial role in larval stages of anuran species. I evaluated whether any part of the species’ distribution experiences CTmax, and whether this CTmax is being experienced more often in recent years as a consequence of warming climates. My analysis supported the idea that 70% of the anuran species experienced CTmax at some point over a 22-year time period. However, only a single species saw CTmax being experienced across its distribution more often through time

Distribution Mapping of Medicinal Plants: A GIS assisted approach

Graduate Student Department of Geography University of KansasPlatinum Sponsors * KU Transportation Research Institute Gold Sponsors * KU Department of Geography * KU Institute for Policy & Social Research * State of Kansas Data Access and Support Center (DASC) * KU Libraries GIS and Scholar Services * Wilson & Company Engineers and Architects Silver Sponsors * Bartlett & West * KansasView Consortium * KU Biodiversity Institute Bronze Sponsors * AECOM * Kansas Biological Survey * C-CHANGE Program (NSF IGERT) * KU Environmental Studies Program * KU Department of Ecology and Evolutionary Biology * Mid-West CAD * National Weather Service * Spatial Data Researc

rangemap: An R Package to Explore Species' Geographic Ranges

Data exploration is a critical step in understanding patterns and biases in information about species’ geographic distributions. We present rangemap, an R package that implements tools to explore species’ ranges based on simple analyses and visualizations. The rangemap package uses species occurrence coordinates, spatial polygons, and raster layers as input data. Its analysis tools help to generate simple spatial polygons summarizing ranges based on distinct approaches, including spatial buffers, convex and concave (alpha) hulls, trend-surface analysis, and raster reclassification. Visualization tools included in the package help to produce simple, high-quality representations of occurrence data and figures summarizing resulting ranges in geographic and environmental spaces. Functions that create ranges also allow generating extents of occurrence (using convex hulls) and areas of occupancy according to IUCN criteria. A broad community of researchers and students could find in rangemap an interesting means by which to explore species’ geographic distributions

rangemap: An R Package to Explore Species' Geographic Ranges

Data exploration is a critical step in understanding patterns and biases in information about species’ geographic distributions. We present rangemap, an R package that implements tools to explore species’ ranges based on simple analyses and visualizations. The rangemap package uses species occurrence coordinates, spatial polygons, and raster layers as input data. Its analysis tools help to generate simple spatial polygons summarizing ranges based on distinct approaches, including spatial buffers, convex and concave (alpha) hulls, trend-surface analysis, and raster reclassification. Visualization tools included in the package help to produce simple, high-quality representations of occurrence data and figures summarizing resulting ranges in geographic and environmental spaces. Functions that create ranges also allow generating extents of occurrence (using convex hulls) and areas of occupancy according to IUCN criteria. A broad community of researchers and students could find in rangemap an interesting means by which to explore species’ geographic distributions

Climatic niche and flowering and fruiting phenology of an epiphytic plant

Species have geographic distributions constrained by combinations of abiotic factors, biotic factors and dispersal-related factors. Abiotic requirements vary across the life stages for a species; for plant species, a particularly important life stage is when the plant flowers and develops seeds. A previous year-long experiment showed that ambient temperature of 5–35 °C, relative humidity of >50 % and ≤15 consecutive rainless days are crucial abiotic conditions for Spanish moss (Tillandsia usneoides L.). Here, we explore whether these optimal physiological intervals relate to the timing of the flowering and fruiting periods of Spanish moss across its range. As Spanish moss has a broad geographic range, we examined herbarium specimens to detect and characterize flowering/fruiting periods for the species across the Americas; we used high-temporal-resolution climatic data to assess the availability of optimal conditions for Spanish moss populations during each population's flowering period. We explored how long populations experience suboptimal conditions and found that most populations experience suboptimal conditions in at least one environmental dimension. Flowering and fruiting periods of Spanish moss populations are either being optimized for one or a few parameters or may be adjusted such that all parameters are suboptimal. Spanish moss populations appear to be constrained most closely by minimum temperature during this period

Spatial Scaling of Prevalence and Population Variation in Three Grassland Sparrows

This is the publisher's version, also available electronically from http://www.bioone.org/doi/abs/10.1525/cond.2013.120055Henslow's Sparrows (Ammodramus henslowii) are distributed in tallgrass prairies in central North America; however, this species is restricted further to specific habitats within these prairies—large expanses with relatively little woody vegetation but an accumulation of standing grasses and forbs, conditions that result from infrequent disturbances by fire, mowing, or grazing. Henslow's Sparrows have been documented to be unpredictable at breeding sites from year to year, but studies to date have considered only local spatial scales. We compared resettlement behavior (prevalence of occurrence and variation in abundance) of Henslow's Sparrows to that of two other grassland sparrows, Grasshopper Sparrows (A. savannarum) and Savannah Sparrows (Passerculus sandwichensis), across multiple spatial resolutions. In Henslow's Sparrows, prevalence was lower and variation in abundance was greater than in the other two species. Indeed, Henslow's Sparrows do not occur consistently at extents of less than 120 000 km2, suggesting nomadic characteristics of where they breed from year to year. We suggest that these patterns reflect Henslow's Sparrows' responses to frequently changing habitat, such that this species is tracking spatiotemporal changes in optimal habitat that result from disturbances broadly across regional landscapes