Increasing aridity threatens the sexual regeneration of Quercus ilex(holm oak) in Mediterranean ecosystems

Knowledge of the recruitment of dominant forest species is a key aspect for forest conservation and the ecosystem services they provide. In this paper, we address how the simultaneous action of climate change and the intensity of land use in the past influence the recruitment of a forest species that depends on the provision of nurse plants to recruit. We compared the number of saplings (up to 15 years old) and juveniles (16 to 50 years old) of Quercus ilex in 17, 5.3 ha plots in the Iberian System (eastern Spain). We used a gradient of past deforestation intensity crossed with two levels of average annual precipitation, one of them at the lower limit of the species'' precipitation niche (semi-arid) and the other at the optimum (sub-humid). We also examined the association between recruits and nurse plants and the effect on this association of plot-scale factors, such as seed abundance (reproductive Q. ilex), microsites (nurse species and soil availability), and large herbivores. The increase in aridity in the last decades has drastically reduced the recruitment of new individuals in the forests of Q. ilex located in the lower limit of their precipitation niche, regardless of the intensity of past deforestation that they suffered. Recruitment in these climatic conditions depends almost exclusively on large trees and shrubs whose abundance may also be limited by aridity. The lack of regeneration questions the future of these populations, as the number of individuals will decrease over time despite the strong resistance of adult trees to disturbance and drought

Evidence of Tree Species’ Range Shifts in a Complex Landscape

Climate change is expected to change the distribution of species. For long-lived, sessile species such as trees, tracking the warming climate depends on seedling colonization of newly favorable areas. We compare the distribution of seedlings and mature trees for all but the rarest tree species in California, Oregon and Washington, United States of America, a large, environmentally diverse region. Across 46 species, the mean annual temperature of the range of seedlings was 0.120°C colder than that of the range of trees (95% confidence interval from 0.096 to 0.144°C). The extremes of the seedling distributions also shifted towards colder temperature than those of mature trees, but the change was less pronounced. Although the mean elevation and mean latitude of the range of seedlings was higher than and north of those of the range of mature trees, elevational and latitudinal shifts run in opposite directions for the majority of the species, reflecting the lack of a direct biological relationship between species’ distributions and those variables. The broad scale, environmental diversity and variety of disturbance regimes and land uses of the study area, the large number and exhaustive sampling of tree species, and the direct causal relationship between the temperature response and a warming climate, provide strong evidence to attribute the observed shifts to climate change

Using an epiphytic moss to identify previously unknown sources of atmospheric cadmium pollution

Urban networks of air-quality monitors are often too widely spaced to identify sources of air pollutants, especially if they do not disperse far from emission sources. The objectives of this study were to test the use of moss bioindicators to develop a fine-scale map of atmospherically-derived cadmium and to identify the sources of cadmium in a complex urban setting.We collected 346 samples of the moss Orthotrichum lyellii from deciduous trees in December, 2013 using a modified randomized grid-based sampling strategy across Portland, Oregon.We estimated a spatial linear model of moss cadmium levels and predicted cadmium on a 50 m grid across the city. Cadmium levels in moss were positively correlated with proximity to two stained-glass manufacturers, proximity to the Oregon– Washington border, and percent industrial land in a 500 m buffer, and negatively correlated with percent residential land in a 500 m buffer. The maps showed very high concentrations of cadmium around the two stained-glass manufacturers, neither of which were known to environmental regulators as cadmium emitters. In addition, in response to our findings, the Oregon Department of Environmental Quality placed an instrumental monitor 120 m from the larger stained-glass manufacturer in October, 2015. The monthly average atmospheric cadmium concentration was 29.4 ng/m3,which is 49 times higher than Oregon\u27s benchmark of 0.6 ng/m3, and high enough to pose a health risk from even short-term exposure. Both stained-glass manufacturers voluntarily stopped using cadmium after the monitoring results were made public, and the monthly average cadmium levels precipitously dropped to 1.1 ng/m3 for stained-glass manufacturer #1 and 0.67 ng/m3 for stained-glass manufacturer #2

Relating Forest Attributes with Area- and Tree-Based Light Detection and Ranging Metrics for Western Oregon

Three sets of linear models were developed to predict several forest attributes, using stand-level and single-tree remote sensing (STRS) light detection and ranging (LiDAR) metrics as predictor variables. The first used only area-level metrics (ALM) associated with first-return height distribution, percentage of cover, and canopy transparency. The second alternative included metrics of first-return LiDAR intensity. The third alternative used area-level variables derived from STRS LiDAR metrics. The ALM model for Lorey’s height did not change with inclusion of intensity and yielded the best results in terms of both model fit (adjusted R² = 0.93) and cross-validated relative root mean squared error (RRMSE = 8.1%). The ALM model for density (stems per hectare) had the poorest precision initially (RRMSE = 39.3%), but it improved dramatically (RRMSE = 27.2%) when intensity metrics were included. The resulting RRMSE values of the ALM models excluding intensity for basal area, quadratic mean diameter, cubic stem volume, and average crown width were 20.7, 19.9, 30.7, and 17.1%, respectively. The STRS model for Lorey’s height showed a 3% improvement in RRMSE over the ALM models. The STRS basal area and density models significantly underperformed compared with the ALM models, with RRMSE values of 31.6 and 47.2%, respectively. The performance of STRS models for crown width, volume, and quadratic mean diameter was comparable to that of the ALM models.Keywords: single-tree remote sensing, area-level metrics, LiDAR intensity, georeferenceKeywords: single-tree remote sensing, area-level metrics, LiDAR intensity, georeferenc

A comparison of small-area estimation techniques to estimate selected stand attributes using LiDAR-derived auxiliary variables

One of the challenges often faced in forestry is the estimation of forest attributes for smaller areas of interest within a larger population. Small-area estimation (SAE) is a set of techniques well suited to estimation of forest attributes for small areas in which the existing sample size is small and auxiliary information is available. Selected SAE methods were compared for estimating a variety of forest attributes for small areas using ground data and light detection and ranging (LiDAR) derived auxiliary information. The small areas of interest consisted of delineated stands within a larger forested population. Four different estimation methods were compared for predicting forest density (number of trees/ha), quadratic mean diameter (cm), basal area (m2/ha), top height (m), and cubic stem volume (m3/ha). The precision and bias of the estimation methods (synthetic prediction (SP), multiple linear regression based composite prediction (CP), empirical best linear unbiased prediction (EBLUP) via Fay–Herriot models, and most similar neighbor (MSN) imputation) are documented. For the indirect estimators, MSN was superior to SP in terms of both precision and bias for all attributes. For the composite estimators, EBLUP was generally superior to direct estimation (DE) and CP, with the exception of forest density

Using an epiphytic moss to identify previously unknown sources of atmospheric cadmium pollution

Urban networks of air-quality monitors are often too widely spaced to identify sources of air pollutants, especially if they do not disperse far from emission sources. The objectives of this study were to test the use of moss bioindicators to develop a fine-scale map of atmospherically-derived cadmium and to identify the sources of cadmium in a complex urban setting.We collected 346 samples of the moss Orthotrichum lyellii from deciduous trees in December, 2013 using a modified randomized grid-based sampling strategy across Portland, Oregon.We estimated a spatial linear model of moss cadmium levels and predicted cadmium on a 50 m grid across the city. Cadmium levels in moss were positively correlated with proximity to two stained-glass manufacturers, proximity to the Oregon– Washington border, and percent industrial land in a 500 m buffer, and negatively correlated with percent residential land in a 500 m buffer. The maps showed very high concentrations of cadmium around the two stained-glass manufacturers, neither of which were known to environmental regulators as cadmium emitters. In addition, in response to our findings, the Oregon Department of Environmental Quality placed an instrumental monitor 120 m from the larger stained-glass manufacturer in October, 2015. The monthly average atmospheric cadmium concentration was 29.4 ng/m3,which is 49 times higher than Oregon\u27s benchmark of 0.6 ng/m3, and high enough to pose a health risk from even short-term exposure. Both stained-glass manufacturers voluntarily stopped using cadmium after the monitoring results were made public, and the monthly average cadmium levels precipitously dropped to 1.1 ng/m3 for stained-glass manufacturer #1 and 0.67 ng/m3 for stained-glass manufacturer #2

Triple-negative breast cancer: Present challenges and new perspectives

Contains fulltext : 83751.pdf (publisher's version ) (Open Access)21 p

Deciphering the role of histone modifications in uterine leiomyoma: acetylation of H3K27 regulates the expression of genes involved in proliferation, cell signaling, cell transport, angiogenesis and extracellular matrix formation

Uterine leiomyoma (UL) is a benign tumor arising from myometrium (MM) with a high prevalence and unclear pathology. Histone modifications are altered in tumors, particularly via histone acetylation which is correlated with gene activation. To identify if the acetylation of H3K27 is involved in UL pathogenesis and if its reversion may be a therapeutic option, we performed a prospective study integrating RNA-seq (n = 48) and CHIP-seq for H3K27ac (n = 19) in UL vs MM tissue, together with qRT-PCR of SAHA-treated UL cells (n = 10). CHIP-seq showed lower levels of H3K27ac in UL versus MM (p-value < 2.2 × 10−16). From 922 DEGs found in UL vs. MM (FDR < 0.01), 482 presented H3K27ac. A differential acetylation (FDR < 0.05) was discovered in 82 of these genes (29 hyperacetylated/upregulated, 53 hypoacetylated/downregulated). Hyperacetylation/upregulation of oncogenes (NDP,HOXA13,COL24A1,IGFL3) and hypoacetylation/downregulation of tumor suppressor genes (CD40,GIMAP8,IL15,GPX3,DPT) altered the immune system, the metabolism, TGFβ3 and the Wnt/β-catenin pathway. Functional enrichment analysis revealed deregulation of proliferation, cell signaling, transport, angiogenesis and extracellular matrix. Inhibition of histone deacetylases by SAHA increased expression of hypoacetylated/downregulated genes in UL cells (p < 0.05). Conclusively, H3K27ac regulates genes involved in UL onset and maintenance. Histone deacetylation reversion upregulates the expression of tumor suppressor genes in UL cells, suggesting targeting histone modifications as a therapeutic approach for UL