A wide range of 2-pyridyl and other difficult-to-access heterocyclic N-methyliminodiacetic acid boronates can be readily prepared from the corresponding bromides via a new method involving direct transligation of trialkoxyborate salts with MIDA at elevated temperatures.
Spatially explicit forest carbon (C) monitoring aids conservation and climate change mitigation efforts, yet few approaches have been developed specifically for the highly heterogeneous landscapes of oceanic island chains that continue to undergo
rapid and extensive forest C change. We developed an approach for rapid mapping of aboveground C density (ACD; units = Mg or metric tons C ha−1) on islands at a spatial resolution of 30 m (0.09 ha) using a combination of cost-effective airborne LiDAR data and full-coverage satellite data. We used the approach to map forest ACD across the main Hawaiian Islands, comparing C stocks within and among islands, in protected and unprotected areas, and among forests dominated by native and invasive species.
Total forest aboveground C stock of the Hawaiian Islands was 36 Tg, and ACD distributions were extremely heterogeneous both within and across islands. Remotely sensed ACD was validated against U.S. Forest Service FIA plot inventory data (R2 = 0.67; RMSE = 30.4 Mg C ha−1). Geospatial analyses indicated the critical importance of forest type and canopy cover as predictors of mapped ACD patterns. Protection status was a strong determinant of forest C stock and density, but we found complex environmentally mediated responses of forest ACD to alien plant invasion.
A combination of one-time airborne LiDAR data acquisition and satellite monitoring provides effective forest C mapping in the highly heterogeneous landscapes of the Hawaiian Islands. Our statistical approach yielded key insights into the drivers of ACD variation, and also makes possible future assessments of C storage change, derived on a repeat basis from free satellite data, without the need for additional LiDAR data. Changes in C stocks and densities of oceanic islands can thus be continually assessed in the face of rapid environmental changes such as biological invasions, drought, fire and land use. Such forest monitoring information can be used to promote sustainable forest use and conservation on islands in the future.
Electronic supplementary material
The online version of this article (doi:10.1186/s13021-015-0043-4) contains supplementary material, which is available to authorized users.
Carbon stocks; Carnegie Airborne Observatory; Forest inventory; Invasive species; LiDAR; Random Forest Machine Learning
Few reports have examined the impact of HIV-1 transmitted drug resistance (TDR) in resource-limited settings where there are fewer regimen choices and limited pretherapy/posttherapy resistance testing. In this study, we examined TDR prevalence in Kampala and Mbarara, Uganda and assessed its virologic consequences after antiretroviral therapy initiation. We sequenced the HIV-1 protease/reverse transcriptase from n=81 and n=491 treatment-naive participants of the Uganda AIDS Rural Treatment Outcomes (UARTO) pilot study in Kampala (AMU 2002–2004) and main cohort in Mbarara (MBA 2005–2010). TDR-associated mutations were defined by the WHO 2009 surveillance mutation list. Posttreatment viral load data were available for both populations. Overall TDR prevalence was 7% (Kampala) and 3% (Mbarara) with no significant time trend. There was a slight but statistically nonsignificant trend indicating that the presence of TDR was associated with a worse treatment outcome. Virologic suppression (≤400 copies/ml within 6 months posttherapy initiation) was achieved in 87% and 96% of participants with wildtype viruses versus 67% and 83% of participants with TDR (AMU, MBA p=0.2 and 0.1); time to suppression (log-rank p=0.3 and p=0.05). Overall, 85% and 96% of study participants achieved suppression regardless of TDR status. Surprisingly, among the TDR cases, approximately half still achieved suppression; the presence of pretherapy K103N while on nevirapine and fewer active drugs in the first regimen were most often observed with failures. The majority of patients benefited from the local HIV care system even without resistance monitoring. Overall, TDR prevalence was relatively low and its presence did not always imply treatment failure.
Remote identification and mapping of canopy tree species can contribute valuable information towards our understanding of ecosystem biodiversity and function over large spatial scales. However, the extreme challenges posed by highly diverse, closed-canopy tropical forests have prevented automated remote species mapping of non-flowering tree crowns in these ecosystems. We set out to identify individuals of three focal canopy tree species amongst a diverse background of tree and liana species on Barro Colorado Island, Panama, using airborne imaging spectroscopy data. First, we compared two leading single-class classification methods—binary support vector machine (SVM) and biased SVM—for their performance in identifying pixels of a single focal species. From this comparison we determined that biased SVM was more precise and created a multi-species classification model by combining the three biased SVM models. This model was applied to the imagery to identify pixels belonging to the three focal species and the prediction results were then processed to create a map of focal species crown objects. Crown-level cross-validation of the training data indicated that the multi-species classification model had pixel-level producer’s accuracies of 94–97% for the three focal species, and field validation of the predicted crown objects indicated that these had user’s accuracies of 94–100%. Our results demonstrate the ability of high spatial and spectral resolution remote sensing to accurately detect non-flowering crowns of focal species within a diverse tropical forest. We attribute the success of our model to recent classification and mapping techniques adapted to species detection in diverse closed-canopy forests, which can pave the way for remote species mapping in a wider variety of ecosystems.
We used measurements from airborne imaging spectroscopy and LiDAR to quantify the biophysical structure and composition of vegetation on a dryland substrate age gradient in Hawaii. Both vertical stature and species composition changed during primary succession, and reveal a progressive increase in vertical stature on younger substrates followed by a collapse on Pleistocene-aged flows. Tall-stature Metrosideros polymorpha woodlands dominated on the youngest substrates (hundreds of years), and were replaced by the tall-stature endemic tree species Myoporum sandwicense and Sophora chrysophylla on intermediate-aged flows (thousands of years). The oldest substrates (tens of thousands of years) were dominated by the short-stature native shrub Dodonaea viscosa and endemic grass Eragrostis atropioides. We excavated 18 macroscopic charcoal fragments from Pleistocene-aged substrates. Mean radiocarbon age was 2,002 years and ranged from < 200 to 7,730. Genus identities from four fragments indicate that Osteomeles spp. or M. polymorpha once occupied the Pleistocene-aged substrates, but neither of these species is found there today. These findings indicate the existence of fires before humans are known to have occupied the Hawaiian archipelago, and demonstrate that a collapse in vertical stature is prevalent on the oldest substrates. This work contributes to our understanding of prehistoric fires in shaping the trajectory of primary succession in Hawaiian drylands.
Tropical forests store large amounts of carbon in tree biomass, although the environmental controls on forest carbon stocks remain poorly resolved. Emerging airborne remote sensing techniques offer a powerful approach to understand how aboveground carbon density (ACD) varies across tropical landscapes. In this study, we evaluate the accuracy of the Carnegie Airborne Observatory (CAO) Light Detection and Ranging (LiDAR) system to detect top-of-canopy tree height (TCH) and ACD across the Osa Peninsula, Costa Rica. LiDAR and field-estimated TCH and ACD were highly correlated across a wide range of forest ages and types. Top-of-canopy height (TCH) reached 67 m, and ACD surpassed 225 Mg C ha-1, indicating both that airborne CAO LiDAR-based estimates of ACD are accurate in tall, high-biomass forests and that the Osa Peninsula harbors some of the most carbon-rich forests in the Neotropics. We also examined the relative influence of lithologic, topoedaphic and climatic factors on regional patterns in ACD, which are known to influence ACD by regulating forest productivity and turnover. Analyses revealed a spatially nested set of factors controlling ACD patterns, with geologic variation explaining up to 16% of the mapped ACD variation at the regional scale, while local variation in topographic slope explained an additional 18%. Lithologic and topoedaphic factors also explained more ACD variation at 30-m than at 100-m spatial resolution, suggesting that environmental filtering depends on the spatial scale of terrain variation. Our result indicate that patterns in ACD are partially controlled by spatial variation in geologic history and geomorphic processes underpinning topographic diversity across landscapes. ACD also exhibited spatial autocorrelation, which may reflect biological processes that influence ACD, such as the assembly of species or phenotypes across the landscape, but additional research is needed to resolve how abiotic and biotic factors contribute to ACD variation across high biomass, high diversity tropical landscapes.
Woody biomass dynamics are an expression of ecosystem function, yet biomass estimates do not provide information on the spatial distribution of woody vegetation within the vertical vegetation subcanopy. We demonstrate the ability of airborne light detection and ranging (LiDAR) to measure aboveground biomass and subcanopy structure, as an explanatory tool to unravel vegetation dynamics in structurally heterogeneous landscapes. We sampled three communal rangelands in Bushbuckridge, South Africa, utilised by rural communities for fuelwood harvesting. Woody biomass estimates ranged between 9 Mg ha-1 on gabbro geology sites to 27 Mg ha-1 on granitic geology sites. Despite predictions of woodland depletion due to unsustainable fuelwood extraction in previous studies, biomass in all the communal rangelands increased between 2008 and 2012. Annual biomass productivity estimates (10–14% p.a.) were higher than previous estimates of 4% and likely a significant contributor to the previous underestimations of modelled biomass supply. We show that biomass increases are attributable to growth of vegetation <5 m in height, and that, in the high wood extraction rangeland, 79% of the changes in the vertical vegetation subcanopy are gains in the 1-3m height class. The higher the wood extraction pressure on the rangelands, the greater the biomass increases in the low height classes within the subcanopy, likely a strong resprouting response to intensive harvesting. Yet, fuelwood shortages are still occurring, as evidenced by the losses in the tall tree height class in the high extraction rangeland. Loss of large trees and gain in subcanopy shrubs could result in a structurally simple landscape with reduced functional capacity. This research demonstrates that intensive harvesting can, paradoxically, increase biomass and this has implications for the sustainability of ecosystem service provision. The structural implications of biomass increases in communal rangelands could be misinterpreted as woodland recovery in the absence of three-dimensional, subcanopy information.
The small number of hematopoietic stem and progenitor cells in cord blood units limits their widespread use in human transplant protocols. We identified a family of chemically related small molecules that stimulates the expansion ex vivo of human cord blood cells capable of reconstituting human hematopoiesis for at least 6 months in immunocompromised mice. The potent activity of these newly identified compounds, UM171 being the prototype, is independent of suppression of the aryl hydrocarbon receptor, which targets cells with more-limited regenerative potential. The properties of UM171 make it a potential candidate for hematopoietic stem cell transplantation and gene therapy.
Field studies in Amazonia have found a relationship at continental scales between soil fertility and broad trends in forest structure and function. Little is known at regional scales, however, about how discrete patterns in forest structure or functional attributes map onto underlying edaphic or geological patterns. We collected airborne LiDAR (Light Detection and Ranging) data and VSWIR (Visible to Shortwave Infrared) imaging spectroscopy measurements over 600 km2 of northwestern Amazonian lowland forests. We also established 83 inventories of plant species composition and soil properties, distributed between two widespread geological formations. Using these data, we mapped forest structure and canopy reflectance, and compared them to patterns in plant species composition, soils, and underlying geology. We found that variations in soils and species composition explained up to 70% of variation in canopy height, and corresponded to profound changes in forest vertical profiles. We further found that soils and plant species composition explained more than 90% of the variation in canopy reflectance as measured by imaging spectroscopy, indicating edaphic and compositional control of canopy chemical properties. We last found that soils explained between 30% and 70% of the variation in gap frequency in these forests, depending on the height threshold used to define gaps. Our findings indicate that a relatively small number of edaphic and compositional variables, corresponding to underlying geology, may be responsible for variations in canopy structure and chemistry over large expanses of Amazonian forest.
Genomic and phenotypic analyses indicate extensive intra- as well as intertumoral heterogeneity in primary human malignant cell populations despite their clonal origin. Cellular DNA barcoding offers a powerful and unbiased alternative to track the number and size of multiple subclones within a single human tumour xenograft and their response to continued in vivo passaging. Using this approach we find clone-initiating cell frequencies that vary from ~1/10 to ~1/10,000 cells transplanted for two human breast cancer cell lines and breast cancer xenografts derived from three different patients. For the cell lines, these frequencies are negatively affected in transplants of more than 20,000 cells. Serial transplants reveal five clonal growth patterns (unchanging, expanding, diminishing, fluctuating or of delayed onset), whose predominance is highly variable both between and within original samples. This study thus demonstrates the high growth potential and diverse growth properties of xenografted human breast cancer cells.
Cancer cells within the same tumour are heterogeneous in their tumorigenic potential, differentiation status and sensitivity to treatments. Here Nguyen et al. use a sensitive DNA barcoding method to characterize the diversity of clonal growth behaviour within human breast tumours.
Disrupted IKAROS activity is a recurrent feature of some human leukemias, but effects on normal human hematopoietic cells are largely unknown. Here, we used lentivirally mediated expression of a dominant-negative isoform of IKAROS (IK6) to block normal IKAROS activity in primitive human cord blood cells and their progeny. This produced a marked (10-fold) increase in serially transplantable multipotent IK6+ cells as well as increased outputs of normally differentiating B cells and granulocytes in transplanted immunodeficient mice, without producing leukemia. Accompanying T/natural killer (NK) cell outputs were unaltered, and erythroid and platelet production was reduced. Mechanistically, IK6 specifically increased human granulopoietic progenitor sensitivity to two growth factors and activated CREB and its targets (c-FOS and Cyclin B1). In more primitive human cells, IK6 prematurely initiated a B cell transcriptional program without affecting the hematopoietic stem cell-associated gene expression profile. Some of these effects were species specific, thus identifying novel roles of IKAROS in regulating normal human hematopoietic cells.
•IKAROS protein is abundantly expressed in primitive human hematopoietic cells•IK6 enhances human blood stem cell expansion in vivo without causing leukemia•IK6 has a unique profile of lineage-specific effects on human hematopoietic cells•IK6 activates B-lineage transcripts prematurely in human blood stem cells
This study reveals a role for IKAROS in the regulation of normal human hematopoietic stem cells (HSCs). In this report, Eaves and colleagues demonstrate that disruption of IKAROS activity expands human HSCs and enhances their outputs of normally differentiating granulocytic and B-lineage cells, without inducing leukemic transformation.
Next generation, “deep”, sequencing has increasing applications both clinically and in disparate fields of research. This study investigates the accuracy and reproducibility of “deep” sequencing as applied to co-receptor prediction using the V3 loop of Human Immunodeficiency Virus-1. Despite increasing use in HIV co-receptor prediction, the accuracy and reproducibility of deep sequencing technology, and the factors which can affect it, have received only a limited level of investigation. To accomplish this, repeated deep sequencing results were generated using the Roche GS-FLX (454) from a number of sources including a non-homogeneous clinical sample (N = 47 replicates over 18 deep sequencing runs), and a large clinical cohort from the MOTIVATE and A400129 studies (N = 1521). For repeated measurements of a non-homogeneous clinical sample, increasing input copy number both decreased variance in the measured proportion of non-R5 using virus (p<<0.001 and 0.02 for single replicates and triplicates respectively) and increased measured viral diversity (p<0.001; multiple measures). Detection of sequences with a mean abundance less than 1% abundance showed a 2 fold increase in median coefficient of variation (CV) in repeated measurements of a non-homogeneous clinical sample, and a 2.7 fold increase in CV in the MOTIVATE/A400129 dataset compared to sequences with ≥1% abundance. An unexpected source of error included read position, with low accuracy reads occurring more frequently towards the edge of sequencing regions (p<<0.001). Overall, the primary source of variability was sampling error caused by low input copy number/minority species prevalence, though other sources of error including sequence intrinsic, temporal, and read-position related errors were detected.
HIV patients on suppressive antiretroviral therapy have undetectable viremia making it impossible to screen plasma HIV tropism if regimen change is required during suppression. We investigated the prevalence and predictors of tropism switch from CCR5-using (“R5”) to non-CCR5-using (“non-R5”) before and after viral suppression in the initially therapy-naïve HOMER cohort from British Columbia, Canada.
We compared pre-therapy and post-suppression viral genotypic tropism in patients who initiated on PI/NNRTI-based antiretroviral regimens between 1996-1999 (n = 462). Virologic suppression was defined as having two consecutive viral loads of <500 copies/mL, which was the sensitivity limit of most viral load assays at the time. Viral tropism was inferred by V3-loop-population-sequencing and geno2pheno[coreceptor] with cutoff at 5.75% false positive rate (FPR).
When virologic suppression was defined as two-consecutive viral loads <500 copies/mL, 34 (9%) of the 397 patients with pre-therapy R5-virus switched to non-R5 at viral load rebound after a median of 19 months (IQR 8–41 months) of undetectable viremia. Duration of viral load suppression was not a predictor of switch, but lower CD4 count during suppression (median 400 versus 250 cells/mL) and an increased prevalence of pre-therapy non-R5 HIV by “deep” sequencing (median 0.2% versus 3.2%) were independently associated with switch (p = 0.03 and p<0.0001, respectively).
R5-to-non-R5 tropism switches in plasma virus after undetectable viremia were relatively rare events especially among patients with higher CD4 counts during virologic suppression. Our study supports the use of pre-suppression tropism results if maraviroc is being considered during virologic suppression in this subgroup of patients.
Hematopoietic stem cells (HSCs) are identified by their ability to sustain prolonged blood cell production in vivo, although recent evidence suggests that durable self-renewal (DSR) is shared by HSC subtypes with distinct self-perpetuating differentiation programs. Net expansions of DSR-HSCs occur in vivo, but molecularly defined conditions that support similar responses in vitro are lacking. We hypothesized that this might require a combination of factors that differentially promote HSC viability, proliferation, and self-renewal. We now demonstrate that HSC survival and maintenance of DSR potential are variably supported by different Steel factor (SF)-containing cocktails with similar HSC-mitogenic activities. In addition, stromal cells produce other factors, including nerve growth factor and collagen 1, that can antagonize the apoptosis of initially quiescent adult HSCs and, in combination with SF and interleukin-11, produce >15-fold net expansions of DSR-HSCs ex vivo within 7 days. These findings point to the molecular basis of HSC control and expansion.
•HSC viability, mitogenesis, and self-renewal are differentially controlled•Stromal cells produce nonmitogenic factors that directly sustain HSC viability•More adult bone marrow cells can produce HSCs than display HSC activity directly•Nerve growth factor and collagen 1 promote serially transplantable HSCs
Wohrer et al. now show that different factors secreted by stromal cells separately control the survival, proliferation, and self-renewal of hematopoietic stem cells. These factors are thus required in combination to stimulate net expansions of these cells with full retention of their original stem cell properties.
Accurate and spatially-explicit maps of tropical forest carbon stocks are needed to implement carbon offset mechanisms such as REDD+ (Reduced Deforestation and Degradation Plus). The Random Forest machine learning algorithm may aid carbon mapping applications using remotely-sensed data. However, Random Forest has never been compared to traditional and potentially more reliable techniques such as regionally stratified sampling and upscaling, and it has rarely been employed with spatial data. Here, we evaluated the performance of Random Forest in upscaling airborne LiDAR (Light Detection and Ranging)-based carbon estimates compared to the stratification approach over a 16-million hectare focal area of the Western Amazon. We considered two runs of Random Forest, both with and without spatial contextual modeling by including—in the latter case—x, and y position directly in the model. In each case, we set aside 8 million hectares (i.e., half of the focal area) for validation; this rigorous test of Random Forest went above and beyond the internal validation normally compiled by the algorithm (i.e., called “out-of-bag”), which proved insufficient for this spatial application. In this heterogeneous region of Northern Peru, the model with spatial context was the best preforming run of Random Forest, and explained 59% of LiDAR-based carbon estimates within the validation area, compared to 37% for stratification or 43% by Random Forest without spatial context. With the 60% improvement in explained variation, RMSE against validation LiDAR samples improved from 33 to 26 Mg C ha−1 when using Random Forest with spatial context. Our results suggest that spatial context should be considered when using Random Forest, and that doing so may result in substantially improved carbon stock modeling for purposes of climate change mitigation.
Mouse fetal mammary cells display greater regenerative activity than do adult mammary cells when stimulated to proliferate in a new system that supports the production of transplantable mammary stem cells ex vivo.
Many normal adult tissues contain rare stem cells with extensive self-maintaining regenerative potential. During development, the stem cells of the hematopoietic and neural systems undergo intrinsically specified changes in their self-renewal potential. In the mouse, mammary stem cells with transplantable regenerative activity are first detectable a few days before birth. They share some phenotypic properties with their adult counterparts but are enriched in a subpopulation that displays a distinct gene expression profile. Here we show that fetal mammary epithelial cells have a greater direct and inducible growth potential than their adult counterparts. The latter feature is revealed in a novel culture system that enables large numbers of in vitro clonogenic progenitors as well as mammary stem cells with serially transplantable activity to be produced within 7 days from single fetal or adult input cells. We further show that these responses are highly dependent on novel factors produced by fibroblasts. These findings provide new avenues for elucidating mechanisms that regulate normal mammary epithelial stem cell properties at the single-cell level, how these change during development, and how their perturbation may contribute to transformation.
Many adult tissues are maintained by a rare subset of undifferentiated stem cells that can self-renew and give rise to specialized daughter cells that have a more limited regenerative ability. The recent identification of cells in the fetal and adult mammary gland that display the properties of stem cells provides a foundation for investigating their self-renewal and differentiation control. We now show that these stem cell properties can be elicited from single mouse mammary cells placed in 3D cultures if novel factors produced by fibroblasts are present. Moreover, a comparison of the clonal outputs of fetal and adult mammary cells in this in vitro system shows that the fetal mammary cells have superior regenerative activity relative to their adult counterparts. The ability to activate and quantify the regenerative capacity of single mouse mammary epithelial cells in vitro sets the stage for further investigations of the timing and mechanisms that alter their stem cell properties during development, the potential relevance of these events to other normal epithelial tissues, and how these processes might be involved in the genesis of breast cancer.
Human immunodeficiency virus type 1 (HIV-1) V3 loop sequence can be used to infer viral coreceptor use. The effect of input copy number on population-based sequencing of the V3 loop of HIV-1 was examined through replicate deep and population-based sequencing of samples with known tropism, a heterogeneous clinical sample (624 population-based sequences and 47 deep-sequencing replicates), and a large cohort of clinical samples from phase III clinical trials of maraviroc including the MOTIVATE/A4001029 studies (n = 1,521). Proviral DNA from two independent samples from each of 101 patients from the MOTIVATE/A4001029 studies was also analyzed. Cumulative technical error occurred at a rate of 3 × 10−4 mismatches/bp, without observed effect on inferred tropism. Increasing PCR replication increased minority species detection with an ∼10% minority population detected in 18% of cases using a single replicate at a viral load of 1,072 copies/ml and in 44% of cases using three replicates. The nucleotide prevalence detected by population-based and deep sequencing were highly correlated (Spearman's ρ, 0.73), and the accuracy increased with increasing input copy number (P < 0.001). Triplicate sequencing was able to predict tropism changes in the MOTIVATE/A4001029 studies for both low (P = 0.05) and high (P = 0.02) viral loads. Sequences derived from independently extracted and processed samples of proviral DNA for the same patient were equivalent to replicates from the same extraction (P = 0.45) and had correlated position-specific scoring matrix scores (Spearman's ρ, 0.75; P ≪ 0.001); however, concordance in tropism inference was only 83%. Input copy number and PCR replication are important factors in minority species detection in samples with significant heterogeneity.
The Malaysian states of Sabah and Sarawak are global hotspots of forest loss and degradation due to timber and oil palm industries; however, the rates and patterns of change have remained poorly measured by conventional field or satellite approaches. Using 30 m resolution optical imagery acquired since 1990, forest cover and logging roads were mapped throughout Malaysian Borneo and Brunei using the Carnegie Landsat Analysis System. We uncovered ∼364,000 km of roads constructed through the forests of this region. We estimated that in 2009 there were at most 45,400 km2 of intact forest ecosystems in Malaysian Borneo and Brunei. Critically, we found that nearly 80% of the land surface of Sabah and Sarawak was impacted by previously undocumented, high-impact logging or clearing operations from 1990 to 2009. This contrasted strongly with neighbouring Brunei, where 54% of the land area remained covered by unlogged forest. Overall, only 8% and 3% of land area in Sabah and Sarawak, respectively, was covered by intact forests under designated protected areas. Our assessment shows that very few forest ecosystems remain intact in Sabah or Sarawak, but that Brunei, by largely excluding industrial logging from its borders, has been comparatively successful in protecting its forests.
High fidelity carbon mapping has the potential to greatly advance national resource management and to encourage international action toward climate change mitigation. However, carbon inventories based on field plots alone cannot capture the heterogeneity of carbon stocks, and thus remote sensing-assisted approaches are critically important to carbon mapping at regional to global scales. We advanced a high-resolution, national-scale carbon mapping approach applied to the Republic of Panama – one of the first UN REDD + partner countries.
Integrating measurements of vegetation structure collected by airborne Light Detection and Ranging (LiDAR) with field inventory plots, we report LiDAR-estimated aboveground carbon stock errors of ~10% on any 1-ha land parcel across a wide range of ecological conditions. Critically, this shows that LiDAR provides a highly reliable replacement for inventory plots in areas lacking field data, both in humid tropical forests and among drier tropical vegetation types. We then scale up a systematically aligned LiDAR sampling of Panama using satellite data on topography, rainfall, and vegetation cover to model carbon stocks at 1-ha resolution with estimated average pixel-level uncertainty of 20.5 Mg C ha-1 nationwide.
The national carbon map revealed strong abiotic and human controls over Panamanian carbon stocks, and the new level of detail with estimated uncertainties for every individual hectare in the country sets Panama at the forefront in high-resolution ecosystem management. With this repeatable approach, carbon resource decision-making can be made on a geospatially explicit basis, enhancing human welfare and environmental protection.
Biomass; Carbon stock; Carnegie Airborne Observatory; Deforestation; Forest degradation; Forest inventory; Light Detection and Ranging; Panama
HLA class I-associated polymorphisms identified at the population level mark viral sites under immune pressure by individual HLA alleles. As such, analysis of their distribution, frequency, location, statistical strength, sequence conservation, and other properties offers a unique perspective from which to identify correlates of protective cellular immunity. We analyzed HLA-associated HIV-1 subtype B polymorphisms in 1,888 treatment-naïve, chronically infected individuals using phylogenetically informed methods and identified characteristics of HLA-associated immune pressures that differentiate protective and nonprotective alleles. Over 2,100 HLA-associated HIV-1 polymorphisms were identified, approximately one-third of which occurred inside or within 3 residues of an optimally defined cytotoxic T-lymphocyte (CTL) epitope. Differential CTL escape patterns between closely related HLA alleles were common and increased with greater evolutionary distance between allele group members. Among 9-mer epitopes, mutations at HLA-specific anchor residues represented the most frequently detected escape type: these occurred nearly 2-fold more frequently than expected by chance and were computationally predicted to reduce peptide-HLA binding nearly 10-fold on average. Characteristics associated with protective HLA alleles (defined using hazard ratios for progression to AIDS from natural history cohorts) included the potential to mount broad immune selection pressures across all HIV-1 proteins except Nef, the tendency to drive multisite and/or anchor residue escape mutations within known CTL epitopes, and the ability to strongly select mutations in conserved regions within HIV's structural and functional proteins. Thus, the factors defining protective cellular immune responses may be more complex than simply targeting conserved viral regions. The results provide new information to guide vaccine design and immunogenicity studies.
Canopy gaps express the time-integrated effects of tree failure and mortality as well as regrowth and succession in tropical forests. Quantifying the size and spatial distribution of canopy gaps is requisite to modeling forest functional processes ranging from carbon fluxes to species interactions and biological diversity. Using high-resolution airborne Light Detection and Ranging (LiDAR), we mapped and analyzed 5,877,937 static canopy gaps throughout 125,581 ha of lowland Amazonian forest in Peru. Our LiDAR sampling covered a wide range of forest physiognomies across contrasting geologic and topographic conditions, and on depositional floodplain and erosional terra firme substrates. We used the scaling exponent of the Zeta distribution (λ) as a metric to quantify and compare the negative relationship between canopy gap frequency and size across sites. Despite variable canopy height and forest type, values of λ were highly conservative (λ mean = 1.83, s = 0.09), and little variation was observed regionally among geologic substrates and forest types, or at the landscape level comparing depositional-floodplain and erosional terra firme landscapes. λ-values less than 2.0 indicate that these forests are subjected to large gaps that reset carbon stocks when they occur. Consistency of λ-values strongly suggests similarity in the mechanisms of canopy failure across a diverse array of lowland forests in southwestern Amazonia.
Accurate, high-resolution mapping of aboveground carbon density (ACD, Mg C ha-1) could provide insight into human and environmental controls over ecosystem state and functioning, and could support conservation and climate policy development. However, mapping ACD has proven challenging, particularly in spatially complex regions harboring a mosaic of land use activities, or in remote montane areas that are difficult to access and poorly understood ecologically. Using a combination of field measurements, airborne Light Detection and Ranging (LiDAR) and satellite data, we present the first large-scale, high-resolution estimates of aboveground carbon stocks in Madagascar.
We found that elevation and the fraction of photosynthetic vegetation (PV) cover, analyzed throughout forests of widely varying structure and condition, account for 27-67% of the spatial variation in ACD. This finding facilitated spatial extrapolation of LiDAR-based carbon estimates to a total of 2,372,680 ha using satellite data. Remote, humid sub-montane forests harbored the highest carbon densities, while ACD was suppressed in dry spiny forests and in montane humid ecosystems, as well as in most lowland areas with heightened human activity. Independent of human activity, aboveground carbon stocks were subject to strong physiographic controls expressed through variation in tropical forest canopy structure measured using airborne LiDAR.
High-resolution mapping of carbon stocks is possible in remote regions, with or without human activity, and thus carbon monitoring can be brought to highly endangered Malagasy forests as a climate-change mitigation and biological conservation strategy.
aboveground carbon density; biomass; carbon stocks; Carnegie Airborne Observatory; CLASlite; LiDAR; REDD; tropical forest
Initial in vitro studies of bevirimat resistance failed to observe mutations in the clinically significant QVT motif in SP1 of HIV-1 gag. This study presents a novel screening method involving mixed, clinically derived gag-protease recombinant HIV-1 samples to more accurately mimic the selection of resistance seen in vivo. Bevirimat resistance was investigated via population-based sequencing performed with a large, initially antiretroviral-naïve cohort before (n = 805) and after (n = 355) standard HIV therapy (without bevirimat). The prevalence of any polymorphism in the motif comprising Q, V, and T was ∼6%, 29%, and 12%, respectively, and did not change appreciably over the course of therapy. From these samples, three groups of 10 samples whose bulk sequences were wild type at the QVT motif were used to generate gag-protease recombinant viruses that captured the existing diversity. Groups were mixed and passaged with various bevirimat concentrations for 9 weeks. gag variations were assessed by amplicon-based “deep” sequencing using a GS FLX sequencer (Roche). Unscreened mutations were present in all groups, and a V370A minority not originally detected by bulk sequencing was present in one group. V370A, occurring together with another preexisting, unscreened resistance mutation, was selected in all groups in the presence of a bevirimat concentration above 0.1 μM. For the two groups with V370A levels below consistent detectability by deep sequencing, the initial selection of V370A required 3 to 4 weeks of exposure to a narrow range of bevirimat concentrations, whereas for the group with the V370A minority, selection occurred immediately. This approach provides quasispecies diversity that facilitates the selection of mutations observed in clinical trials and, coupled with deep sequencing, could represent an efficient in vitro screening method for detecting resistance mutations.