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

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

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

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

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

Do Ecological Niche Model Predictions Reflect the Adaptive Landscape of Species?: A Test Using Myristica malabarica Lam., an Endemic Tree in the Western Ghats, India

Ecological niche models (ENM) have become a popular tool to define and predict the “ecological niche” of a species. An implicit assumption of the ENMs is that the predicted ecological niche of a species actually reflects the adaptive landscape of the species. Thus in sites predicted to be highly suitable, species would have maximum fitness compared to in sites predicted to be poorly suitable. As yet there are very few attempts to address this assumption. Here we evaluate this assumption. We used Bioclim (DIVA GIS version 7.3) and Maxent (version 3.3.2) to predict the habitat suitability of Myristica malabarica Lam., an economically important tree occurring in the Western Ghats, India. We located populations of the trees naturally occurring in different habitat suitability regimes (from highly suitable to poorly suitable) and evaluated them for their regeneration ability and genetic diversity. We also evaluated them for two plant functional traits, fluctuating asymmetry – an index of genetic homeostasis, and specific leaf weight – an index of primary productivity, often assumed to be good surrogates of fitness. We show a significant positive correlation between the predicted habitat quality and plant functional traits, regeneration index and genetic diversity of populations. Populations at sites predicted to be highly suitable had a higher regeneration and gene diversity compared to populations in sites predicted to be poor or unsuitable. Further, individuals in the highly suitable sites exhibited significantly less fluctuating asymmetry and significantly higher specific leaf weight compared to individuals in the poorly suitable habitats. These results for the first time provide an explicit test of the ENM with respect to the plant functional traits, regeneration ability and genetic diversity of populations along a habitat suitability gradient. We discuss the implication of these resultsfor designing viable species conservation and restoration programs.This study was supported with grants to JG and USR from the North-South Center, ETH Zurich, Switzerland and a grant awarded to RG and USR from the Department of Biotechnology (DBT), New Delhi

Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol

Acknowledging uncertainty in evolutionary reconstructions of ecological niches

Reconstructing ecological niche evolution can provide insight into the biogeography and diversification of evolving lineages. However, comparative phylogenetic methods may infer the history of ecological niche evolution inaccurately because (a) species' niches are often poorly characterized; and (b) phylogenetic comparative methods rely on niche summary statistics rather than full estimates of species' environmental tolerances. Here, we propose a new framework for coding ecological niches and reconstructing their evolution that explicitly acknowledges and incorporates the uncertainty introduced by incomplete niche characterization. Then, we modify existing ancestral state inference methods to leverage full estimates of environmental tolerances. We provide a worked empirical example of our method, investigating ecological niche evolution in the New World orioles (Aves: Passeriformes: Icterus spp.). Temperature and precipitation tolerances were generally broad and conserved among orioles, with niche reduction and specialization limited to a few terminal branches. Tools for performing these reconstructions are available in a new R package called nichevol