Improvement of bacterial blight resistance of the high yielding, fine-grain, rice variety, Gangavati sona through marker-assisted backcross breeding.

Gangavati sona (GS) is a high-yielding, fine-grain rice variety widely grown in the Tungabhadra command area in Karnataka, India; however, it is susceptible to bacterial blight (BB). Therefore, the present study was conducted to improve the GS variety for BB resistance. Three BB-resistant genes (xa5, xa13, and Xa21) were introgressed into the genetic background of susceptible cultivar GS through marker-assisted backcrossing (MABB) by using Improved samba Mahsuri (ISM), a popular, high-yielding, bacterial blight resistant rice variety as a donor parent. Foreground selection was carried out using gene-specific markers, viz., xa5FM (xa5), xa13prom (xa13), and pTA248 (Xa21), while background selection was carried out using well-distributed 64 polymorphic microsatellite markers. The true heterozygote F1 was used as the male parent for backcrossing with GS to obtain BC1F1. The process was repeated in BC1F1 generation, and a BC2F1 plant (IGS-5-11-5) possessing all three target genes along with maximum recurrent parent genome (RPG) recovery (86.7%) was selfed to obtain BC2F2s. At BC2F2, a single triple gene homozygote plant (IGS-5-11-5-33) with 92.6% RPG recovery was identified and advanced to BC2F5 by a pedigree method. At BC2F5, the seven best entries were selected, possessing all three resistance genes with high resistance levels against bacterial blight, yield level, and grain quality features equivalent to better than GS. The improved versions of GS will immensely benefit the farmers whose fields are endemic to BB.

Genome-wide association studies in rice germplasm reveal significant genomic regions for root and yield-related traits under aerobic and irrigated conditions.

The development of nutrient-use efficient rice lines is a priority amidst the changing climate and depleting resources viz., water, land, and labor for achieving sustainability in rice cultivation. Along with the traditional transplanted irrigated system of cultivation, the dry direct-seeded aerobic system is gaining ground nationwide. The root-related traits play a crucial role in nutrient acquisition, adaptation and need to be concentrated along with the yield-attributing traits. We phenotyped an association panel of 118 rice lines for seedling vigour index (SVI) traits at 14 and 21 days after sowing (DAS), root-related traits at panicle initiation (PI) stage in polythene bags under controlled aerobic condition, yield and yield-related traits under the irrigated condition at ICAR-IIRR, Hyderabad, Telangana; irrigated and aerobic conditions at ARS, Dhadesugur, Raichur, Karnataka. The panel was genotyped using simple sequence repeats (SSR) markers and genome-wide association studies were conducted for identifying marker-trait associations (MTAs). Significant correlations were recorded for root length, root dry weight with SVI, root volume at the PI stage, number of productive tillers per plant, spikelet fertility, the total number of grains per panicle with grain yield per plant under irrigated conditions, and the total number of grains per panicle with grain yield per plant under aerobic condition. The panel was divided into three sub-groups (K = 3) and correlated with the principal component analysis. The maximum number of MTAs were found on chromosomes 2, 3, and 12 with considerable phenotypic variability. Consistent MTAs were recorded for SVI traits at 14 and 21 DAS (RM25310, RM80, RM22961, RM1385), yield traits under irrigated conditions (RM2584, RM5179, RM410, RM20698, RM14753) across years at ICAR-IIRR, grain yield per plant (RM22961, RM1146) under the aerobic condition, grain yield per plant at irrigated ICAR-IIRR and SVI (RM5501), root traits at PI stage (RM2584, RM80, RM410, RM1146, RM18472). Functionally relevant genes near the MTAs through in-silico expression analysis in root and panicle tissues viz., HBF2 bZIP transcription factor, WD40 repeat-like domain, OsPILS6a auxin efflux carrier, WRKY108, OsSCP42, OsMADS80, nodulin-like domain-containing protein, amino acid transporter using various rice expression databases were identified. The identified MTAs and rice lines having high SVI traits (Langphou, TI-128, Mouli, TI-124, JBB-631-1), high yield under aerobic (Phouren, NPK-43, JBB-684, Ratnamudi, TI-112), irrigated conditions (KR-209, KR-262, Phouren, Keibi-Phou, TI-17), robust root traits like root length (MoirangPhou-Angouba, Wangoo-Phou, JBB-661, Dissi, NPK-45), root volume (Ratnachudi, KJ-221, Mow, Heimang-Phou, PUP-229) can be further employed in breeding programs for the targeted environments aimed at improving seedling vigour, yield-related traits under irrigated condition, aerobic condition as adaptability to water-saving technology.

Evaluation of genotype by environment interaction and adaptability in lowland irrigated rice hybrids for grain yield under high temperature.

Recent predictions on climate change indicate that high temperature episodes are expected to impact rice production and productivity worldwide. The present investigation was undertaken to assess the yield stability of 72 rice hybrids and their parental lines across three temperature regimes over two consecutive dry seasons using the additive main effect and multiplicative interaction (AMMI), genotype and genotype × environment interaction (GGE) stability model analysis. The combined ANOVA revealed that genotype × environment interaction (GEI) were significant due to the linear component for most of the traits studied. The AMMI and GGE biplot explained 57.2% and 69% of the observed genotypic variation for grain yield, respectively. Spikelet fertility was the most affected yield contributing trait and in contrast, plant height and tiller numbers were the least affected traits. In case of spikelet fertility, grain yield and other yield contributing traits, male parent contributed towards heat tolerance of the hybrids compared to the female parent. The parental lines G74 (IR58025B), G83 (IR40750R), G85 (C20R) and hybrids [G21 (IR58025A × KMR3); G3 (APMS6A × KMR3); G57 (IR68897A × KMR3) and G41 (IR79156A × RPHR1005)] were the most stable across the environments for grain yield. They can be considered as potential genotypes for cultivation under high temperature stress after evaluating under multi location trials.

Novel major QTLs associated with low soil phosphorus tolerance identified from the Indian rice landrace, Wazuhophek.

With an objective of mapping novel low soil P (Phosphorus) tolerance loci in the non-Pup1 type donor rice line, Wazuhophek, we screened a recombinant inbred line (RIL) mapping population consisting of 330 lines derived from the cross Wazuhophek x Improved Samba Mahsuri (which is highly sensitive to low soil P) in a plot with low soil P for tolerance associated traits. Molecular mapping with SSR markers revealed a total of 16 QTLs (seven major and nine minor QTLs), which are associated with low soil P tolerance related traits. Interestingly, a QTL hotspot, harbouring 10 out of 16 QTLs were identified on the short arm of chromosome 8 (flanked by the makers RM22554 and RM80005). Five major QTLs explaining phenotypic variance to an extent of 15.28%, 17.25%, 21.84%, 20.23%, and 18.50%, associated with the traits, plant height, shoot length, the number of productive tillers, panicle length and yield, respectively, were located in the hotspot. Two major QTLs located on chromosome 1, associated with the traits, total biomass and root to shoot ratio, explaining 15.44% and 15.44% phenotypic variance, respectively were also identified. Complex epistatic interactions were observed among the traits, grain yield per plant, days to 50% flowering, dry shoot weight, and P content of the seed. In-silico analysis of genomic regions flanking the major QTLs revealed the presence of key putative candidate genes, possibly associated with tolerance.

Grain Fe and Zn content, heterosis, combining ability and its association with grain yield in irrigated and aerobic rice.

Genetic improvement of rice for grain micronutrients, viz., iron (Fe) and zinc (Zn) content is one of the important breeding objectives, in addition to yield improvement under the irrigated and aerobic ecosystems. In view of developing genetic resources for aerobic conditions, line (L) × tester (T) analysis was conducted with four restorers, four CMS lines and 16 hybrids. Both hybrids and parental lines were evaluated in irrigated and aerobic field conditions for grain yield, grain Fe and Zn content. General Combining Ability (GCA) effects of parents and Specific Combining Ability (SCA) effects of hybrids were observed to be contrasting for the micronutrient content in both the growing environments. The grain Fe and Zn content for parental lines were negatively correlated with grain yield in both the contrasting growing conditions. However, hybrids exhibited positive correlation for grain Fe and Zn with grain yield under limited water conditions. The magnitude of SCA mean squares was much higher than GCA mean squares implying preponderance of dominance gene action and also role of complementary non-allelic gene(s) interaction of parents and suitability of hybrids to the aerobic system. The testers HHZ12-SAL8-Y1-SAL1 (T1) and HHZ17-Y16-Y3-Y2 (T2) were identified as good combiners for grain Zn content under irrigated and aerobic conditions respectively.

Marker assisted improvement of low soil phosphorus tolerance in the bacterial blight resistant, fine-grain type rice variety, Improved Samba Mahsuri.

Improved-Samba-Mahsuri (ISM), a high-yielding, popular bacterial blight resistant (possessing Xa21, xa13, and xa5), fine-grain type, low glycemic index rice variety is highly sensitive to low soil phosphorus (P). We have deployed marker-assisted backcross breeding (MABB) approach for targeted transfer of Pup1, a major QTL associated with low soil P tolerance, using Swarna as a donor. A new co-dominant marker, K20-1-1, which is specific for Pup1 was designed and used for foreground selection along with functional markers specific for the bacterial blight resistance genes, Xa21, xa13, and xa5. A set of 66 polymorphic SSR marker were used for the background selection along with a pair of flanking markers for the recombination selection in backcross derived progenies and in BC2F2 generation, 12 plants, which are homozygous for Pup1, all the three bacterial blight resistance genes and possessing agro-morphological traits equivalent to or better than ISM were selected and selfed to produce BC2F3s. They were evaluated in plots with low soil P and normal soil P at ICAR-IIRR, Hyderabad for their low soil P tolerance, and bacterial blight resistance and superior lines were advanced to BC2F6. One of the lines, when tested at multiple locations in India was found promising under both normal as well as low soil P conditions.

Mapping QTL hotspots associated with weed competitive traits in backcross population derived from Oryza sativa L. and O. glaberrima Steud.

To improve grain yield under direct seeded and aerobic conditions, weed competitive ability of a rice genotype is a key desirable trait. Hence, understanding and dissecting weed competitive associated traits at both morphological and molecular level is important in developing weed competitive varieties. In the present investigation, the QTLs associated with weed competitive traits were identified in BC1F2:3 population derived from weed competitive accession of O. glaberrima (IRGC105187) and O. sativa cultivar IR64. The mapping population consisting of 144 segregating lines were phenotyped for 33 weed competitive associated traits under direct seeded condition. Genetic analysis of weed competitive traits carried out in BC1F2:3 population showed significant variation for the weed competitive traits and predominance of additive gene action. The population was genotyped with 81 genome wide SSR markers and a linkage map covering 1423 cM was constructed. Composite interval mapping analysis identified 72 QTLs linked to 33 weed competitive traits which were spread on the 11 chromosomes. Among 72 QTLs, 59 were found to be major QTLs (> 10% PVE). Of the 59 major QTLs, 38 had favourable allele contributed from the O. glaberrima parent. We also observed nine QTL hotspots for weed competitive traits (qWCA2a, qWCA2b, qWCA2c, qWCA3, qWCA5, qWCA7, qWCA8, qWCA9, and qWCA10) wherein several QTLs co-localised. Our study demonstrates O. glaberrima species as potential source for improvement for weed competitive traits in rice and identified QTLs hotspots associated with weed competitive traits.

Utilizing the density of inventory samples to define a hybrid lattice for species distribution models: DISTRIB-II for 135 eastern U.S. trees.

Species distribution models (SDMs) provide useful information about potential presence or absence, and environmental conditions suitable for a species; and high-resolution models across large extents are desirable. A primary feature of SDMs is the underlying spatial resolution, which can be chosen for many reasons, though we propose that a hybrid lattice, in which grid cell sizes vary with the density of forest inventory plots, provides benefits over uniform grids. We examine how the spatial grain size affected overall model performance for the Random Forest-based SDM, DISTRIB, which was updated with recent forest inventories, climate, and soil data, and used a hybrid lattice derived from inventory densities.Modeled habitat suitability was compared between a uniform grid of 10 × 10 and a hybrid lattice of 10 × 10 and 20 × 20 km grids to assess potential improvements. The resulting DISTRIB-II models for 125 eastern U.S. tree species provide information on individual habitat suitability that can be mapped and statistically analyzed to understand current and potential changes.Model performance metrics were comparable among the hybrid lattice and 10-km grids; however, the hybrid lattice models generally had higher overall model reliability scores and were likely more representative of the inventory data.Our efforts to update DISTRIB models with current information aims to produce a more representative depiction of recent conditions by accounting for the spatial density of forest inventory data and using the latest climate data. Additionally, we developed an approach that leverages a hybrid lattice to maximize the spatial information within the models and recommend that similar modeling efforts be used to evaluate the spatial density of response and predictor data and derive a modeling grid that best represents the environment.

Depth of soil compaction predominantly affects rice yield reduction by reproductive-stage drought at varietal screening sites in Bangladesh, India, and Nepal.

AIMS: Drought is the major constraint to rainfed rice productivity in South Asia, but few reports provide detailed characterization of the soil properties related to drought stress severity in the region. The aim of the study was to provide a compilation of drought breeding network sites and their respective levels of drought stress, and to relate soil parameters with yield reduction by drought. METHODS: This study characterized levels of drought stress and soil nutrient and physical properties at 18 geographically distributed research station sites involved in rice varietal screening in Bangladesh, India, and Nepal, as well as at farmers' fields located near the research stations. RESULTS: Based on soil resistance to penetration profiles, a hardpan was surprisingly absent at about half of the sites characterized. Significant relationships of depth of compaction and yield reduction by drought indicated the effects of soil puddling on susceptibility to cracking, rather than water retention by hardpans, on plant water availability in this region. The main difference between research stations and nearby farmers' fields was in terms of soil compaction. CONCLUSIONS: These results present an initiative for understanding the range of severities of reproductive-stage drought stress in drought-prone rainfed lowland rice-growing areas in South Asia.

Macroscale intraspecific variation and environmental heterogeneity: analysis of cold and warm zone abundance, mortality, and regeneration distributions of four eastern US tree species.

I test for macroscale intraspecific variation of abundance, mortality, and regeneration of four eastern US tree species (Tsuga canadensis,Betula lenta,Liriodendron tulipifera, and Quercus prinus) by splitting them into three climatic zones based on plant hardiness zones (PHZs). The primary goals of the analysis are to assess the differences in environmental heterogeneity and demographic responses among climatic zones, map regional species groups based on decision tree rules, and evaluate univariate and multivariate patterns of species demography with respect to environmental variables. I use the Forest Inventory Analysis (FIA) data to derive abundance, mortality, and regeneration indices and split the range into three climatic zones based on USDA PHZs: (1) cold adapted, leading region; (2) middle, well-adapted region; and (3) warm adapted, trailing region. I employ decision tree ensemble methods to assess the importance of environmental predictors on the abundance of the species between the cold and warm zones and map zonal variations in species groups. Multivariate regression trees are used to simultaneously explore abundance, mortality, and regeneration in tandem to assess species vulnerability. Analyses point to the relative importance of climate in the warm adapted, trailing zone (especially moisture) compared to the cold adapted, leading zone. Higher mortality and lower regeneration patterns in the warm trailing zone point to its vulnerability to growing season temperature and precipitation changes that could figure more prominently in the future. This study highlights the need to account for intraspecific variation of demography in order to understand environmental heterogeneity and differential adaptation. It provides a methodology for assessing the vulnerability of tree species by delineating climatic zones based on easily available PHZ data, and FIA derived abundance, mortality, and regeneration indices as a proxy for overall growth and fitness. Based on decision tree rules, ecologically meaningful variations in species abundance among the climatic zones can be related to environmental variability and mapped.

Determination of an optimal dosing schedule for combining Irinophore C™ and temozolomide in an orthotopic model of glioblastoma.

Our laboratory reported that Irinophore C™ (IrC™; a lipid-based nanoparticulate formulation of irinotecan) is effective against an orthotopic model of glioblastoma (GBM) and that treatment with IrC™ was associated with vascular normalization within the tumor. Here, the therapeutic effects of IrC™ when used in combination with temozolomide (TMZ) in concurrent and sequential treatment schedules were tested. It was anticipated that IrC™ engendered vascular normalization would increase the delivery of TMZ to the tumor and that this would be reflected by improved treatment outcomes. The approach compared equally efficacious doses of irinotecan (IRN; 50 mg/kg) and IrC™ (25 mg/kg) in order to determine if there was a unique advantage achieved when combining TMZ with IrC™. The TMZ sensitive U251MG(O) cell line (null expression of O-6-methylguanine-DNA methyltransferase (MGMT)) modified to express the fluorescent protein mKate2 was inoculated orthotopically into NOD.CB17-SCID mice and treatment was initiated 14 days later. Our results demonstrated that IrC™ and TMZ administered concurrently resulted in optimal treatment outcomes, with 50% long term survivors (>180 days) in comparison to 17% long term survivors in animals treated with IRN and TMZ or TMZ alone. Indeed, the different treatments resulted in a 353%, 222% and 280% increase in median survival time (MST) compared to untreated animals for, respectively, IrC™ combined with TMZ, IRN combined with TMZ, and TMZ alone. When TMZ was administered after completion of IRN or IrC™ dosing, an increase in median survival time of 167-174% was observed compared to untreated animals and of 67% and 74%, respectively, when IRN (50 mg/kg) and IrC™ (25mg/kg) were given as single agents. We confirmed in these studies that after completion of the Q7D×3 dosing of IrC™, but not IRN, the tumor-associated vascular was normalized as compared to untreated tumors. Specifically, reductions in the fraction of collagen IV-free CD31 staining (p<0.05) and reductions in tumor vessel diameter were observed in tumors from IrC™-treated animals when compared to tumors from untreated or IRN treated animals. Analysis by transmission electron microscopy of the ultra-structure of tumors from IrC™-treated and untreated animals revealed that tumor-associated vessels from treated animals were smaller, more organized and exhibited a morphology comparable to normal blood vessels. In conclusion, optimal treatment outcomes were achieved when IrC™ and TMZ were administered concurrently, whereas IrC™ followed by TMZ treatment given sequentially did not confer any therapeutic advantage.

Physiological mechanisms contributing to the QTL-combination effects on improved performance of IR64 rice NILs under drought.

Characterizing the physiological mechanisms behind major-effect drought-yield quantitative trait loci (QTLs) can provide an understanding of the function of the QTLs-as well as plant responses to drought in general. In this study, we characterized rice (Oryza sativa L.) genotypes with QTLs derived from drought-tolerant traditional variety AdaySel that were introgressed into drought-susceptible high-yielding variety IR64, one of the most popular megavarieties in South Asian rainfed lowland systems. Of the different combinations of the four QTLs evaluated, genotypes with two QTLs (qDTY 2.2 + qDTY 4.1 ) showed the greatest degree of improvement under drought compared with IR64 in terms of yield, canopy temperature, and normalized difference vegetation index (NDVI). Furthermore, qDTY 2.2 and qDTY 4.1 showed a potential for complementarity in that they were each most effective under different severities of drought stress. Multiple drought-response mechanisms were observed to be conferred in the genotypes with the two-QTL combination: higher root hydraulic conductivity and in some cases greater root growth at depth. As evidenced by multiple leaf water status and plant growth indicators, these traits affected transpiration but not transpiration efficiency or harvest index. The results from this study highlight the complex interactions among major-effect drought-yield QTLs and the drought-response traits they confer, and the need to evaluate the optimal combinations of QTLs that complement each other when present in a common genetic background.

Grain yield and physiological traits of rice lines with the drought yield QTL qDTY12.1 showed different responses to drought and soil characteristics in upland environments.

To improve yield in upland conditions, near-isogenic lines (NILs) of the major-effect drought yield quantitative trait locus qDTY12.1 in rice (Oryza sativa L.) were developed in the background of the upland variety Vandana. These NILs have shown greater water uptake a larger proportion of lateral roots, and higher transpiration efficiency under drought than Vandana, and one NIL (481-B) was selected as having the highest yield. In this study, the NILs were assessed in two greenhouse and 18 upland field trials for their response to drought and different soil textures. Performance of qDTY12.1 NILs was not affected by soil texture but showed a notable response to drought stress severity. The yield advantage of 481-B over Vandana was highest in field trials with intermittent drought stress, in which the mean trial yield was greater than 0.5tha-1, and in the least favourable well watered trial. The effects of qDTY12.1 on water uptake were most apparent under mild to moderate stress but not in very severe drought or well watered treatments, whereas the lateral root and transpiration efficiency responses were observed under a range of conditions. These results highlight the varying response of qDTY12.1 across upland environments and the complexity of multiple mechanisms acting together to confer an effect on rice yield under drought.

Exploring tree species colonization potentials using a spatially explicit simulation model: implications for four oaks under climate change.

Climate change impacts tree species differentially by exerting unique pressures and altering their suitable habitats. We previously predicted these changes in suitable habitat for current and future climates using a species habitat model (DISTRIB) in the eastern United States. Based on the accuracy of the model, the species assemblages should eventually reflect the new quasi-equilibrium suitable habitats (~2100) after accounting for the lag in colonization. However, it is an open question if and when these newly suitable habitats will be colonized under current fragmented landscapes and realistic migration rates. To evaluate this, we used a spatially explicit cell-based model (SHIFT) that estimates colonization potentials under current fragmented habitats and several estimates of historical migration rates at a 1 km resolution. Computation time, which was previously the biggest constraint, was overcome by a novel application of convolution and Fast Fourier Transforms. SHIFT outputs, when intersected with future suitable habitats predicted by DISTRIB, allow assessment of colonization potential under future climates. In this article, we show how our approach can be used to screen multiple tree species for their colonization potentials under climate change. In particular, we use the DISTRIB and SHIFT models in combination to assess if the future dominant forest types in the north will really be dominated by oaks, as modelled via DISTRIB. Even under optimistic scenarios, we conclude that only a small fraction of the suitable habitats of oaks predicted by DISTRIB is likely to be occupied within 100 years, and this will be concentrated in the first 10-20 km from the current boundary. We also show how DISTRIB and SHIFT can be used to evaluate the potential for assisted migration of vulnerable tree species, and discuss the dynamics of colonization at range limits.

Regional scale patterns of fine root lifespan and turnover under current and future climate.

Fine root dynamics control a dominant flux of carbon from plants and into soils and mediate potential uptake and cycling of nutrients and water in terrestrial ecosystems. Understanding of these patterns is needed to accurately describe critical processes like productivity and carbon storage from ecosystem to global scales. However, limited observations of root dynamics make it difficult to define and predict patterns of root dynamics across broad spatial scales. Here, we combine species-specific estimates of fine root dynamics with a model that predicts current distribution and future suitable habitat of temperate tree species across the eastern United States (US). Estimates of fine root lifespan and turnover are based on empirical observations and relationships with fine root and whole-plant traits and apply explicitly to the fine root pool that is relatively short-lived and most active in nutrient and water uptake. Results from the combined model identified patterns of faster root turnover rates in the North Central US and slower turnover rates in the Southeastern US. Portions of Minnesota, Ohio, and Pennsylvania were also predicted to experience >10% increases in root turnover rates given potential shifts in tree species composition under future climate scenarios while root turnover rates in other portions of the eastern US were predicted to decrease. Despite potential regional changes, the average estimates of root lifespan and turnover for the entire study area remained relatively stable between the current and future climate scenarios. Our combined model provides the first empirically based, spatially explicit, and spatially extensive estimates of fine root lifespan and turnover and is a potentially powerful tool allowing researchers to identify reasonable approximations of forest fine root turnover in areas where no direct observations are available. Future efforts should focus on reducing uncertainty in estimates of root dynamics by better understanding how climate and soil factors drive variability in root dynamics of different species.

Irinophore C™, a lipid-based nanoparticulate formulation of irinotecan, is more effective than free irinotecan when used to treat an orthotopic glioblastoma model.

Given compelling evidences supporting the therapeutic potential of irinotecan (IRN) for patients with glioblastoma (GBM), the present study evaluated the activity of Irinophore C™ (IrC™), a lipid-based nanopharmaceutical formulation of IRN, in GBM. The levels of IRN and SN-38 were determined in plasma and brain after a single intravenous dose of IRN or IrC™ in tumor-free mice. Treatment with IrC™ significantly increased the plasma AUC(0-24h) of the active (lactone) forms of IRN and SN-38 when compared to free drug (760 and 30-fold increase, respectively). Levels of IRN and SN-38 in brain tissue were also increased significantly (compared to IRN treatment) following IrC™ administration. A tolerability study revealed that IrC™ is better tolerated than IRN. The efficacy of IrC™ and IRN was assessed in an orthotopic model of GBM. The therapeutic efficacy of IrC™ given at 25mg/kg weekly was comparable to the efficacy achieved using twice the dose of IRN. At the maximum tolerated dose, IrC™ (100mg/kg) increased the survival time of tumor-bearing mice of 83% compared to untreated animals. Ki67 immunostaining analysis of IrC™-treated tumors revealed a transient increase in cell proliferation after treatment. The results justify further studies evaluating the use of IrC™ for treating GBM.

Predicting extinctions as a result of climate change.

Widespread extinction is a predicted ecological consequence of global warming. Extinction risk under climate change scenarios is a function of distribution breadth. Focusing on trees and birds of the eastern United States, we used joint climate and environment models to examine fit and climate change vulnerability as a function of distribution breadth. We found that extinction vulnerability increases with decreasing distribution size. We also found that model fit decreases with decreasing distribution size, resulting in high prediction uncertainty among narrowly distributed species. High prediction uncertainty creates a conservation dilemma in that excluding these species under-predicts extinction risk and favors mistaken inaction on global warming. By contrast, including narrow endemics results in over-predicting extinction risk and promotes mistaken inaction on behalf of individual species prematurely considered doomed to extinction.