Trend Patterns of Vegetative Coverage and Their Underlying Causes in the Deserts of Northwest China over 1982 – 2008

<div><p>We identified the spatiotemporal patterns of the Normalized Difference Vegetation Index (NDVI) for the years 1982–2008 in the desert areas of Northwest China and quantified the impacts of climate and non-climate factors on NDVI changes. The results indicate that although the mean NDVI has improved in 24.7% of the study region; 16.3% among the region has been stagnating in recent years and only 8.4% had a significantly increasing trend. Additionally, 45.3% of the region has maintained a stable trend over the study period and 30.0% has declined. A multiple regression model suggests that a wetter climate (quantified by the Palmer Drought Severity Index, PDSI) is associated with higher NDVI in most areas (18.1% of significance) but these historical changes in PDSI only caused an average improvement of approximately 0.4% over the study region. Contrasting the regression results under different trend patterns, no significant differences in PDSI impacts were detected among the four trend patterns. Therefore, we conclude that climate is not the primary driver for vegetative coverage in Northwest China. Future studies will be required to identify the impacts of specific non-climatic factors on vegetative coverage based on high-resolution data, which will be beneficial in creating an effective strategy to combat the recent desertification trend in China.</p></div

Estimated impacts on NDVI by historical trends in PDSI and Year.

<p>All grids were plotted in (a) and (b), and only significant grids were plotted in (c) and (d). The base map is only for illustrative purposes.</p

Impacts on NDVI by historical trends in PDSI and Year grouped by trend patterns.

<p>Impacts on NDVI by historical trends in PDSI and Year grouped by trend patterns.</p

Study region.

<p>Four provinces were included: Xinjiang (XJ), Qinghai (QH), Gansu (GS) and Ningxia (NX). We concentrated on areas with long-term average NDVI values between 0.05 and 0.15. The base map is only for illustrative purposes.</p

Examples of trend patterns of the NDVI.

<p>Increasing (a), stagnation (b), stable (c), and decreasing (d).</p

Summary of the changes in the NDVI for the individual trends of the PDSI and Year, grouped by each trend pattern, over the study period.

<p>^aNeg_Sig/Pos_Sig: proportion of series showing significantly negative and positive regression coefficients (P<0.05).</p><p>^bImpact_avg: average impact on the NDVI by individual PDSIs and Years over the study region; values not sharing the same letter are significantly different (P<0.05).</p><p>Summary of the changes in the NDVI for the individual trends of the PDSI and Year, grouped by each trend pattern, over the study period.</p

The linear time trends of Prcp, PE and PDSI over study period.

<p>The linear time trends of Prcp, PE and PDSI over study period.</p

Histogram of estimated impacts on NDVI by historical trends in PDSI and Year.

<p>All grids were plotted in (a) and (b), and only significant grids were plotted in (c) and (d).</p

Ultrasensitive Silicon Nanowire Sensor Developed by a Special Ag Modification Process for Rapid NH₃ Detection

Surface functionalization is very effective in enhancing sensing properties of a chemiresistive gas sensor. In this work, we develop a novel and cost-effective process to prepare Ag-modified silicon nanowire (SiNW) sensors and further suggest a resistance effect model to clarify the enhanced sensing mechanism of Ag-modified SiNWs. The SiNWs were formed via metal-assisted chemical etching (MACE), and the Ag nanoparticle (NP) modification was achieved in situ based on the MACE-produced Ag dendrites by involving a crucial anisotropic postetching of TMAH. The TMAH etching induces a loose array of needle-like, rough SiNWs (RNWs) with firm attachment of tiny Ag NPs. Comparative investigations for NH₃-sensing properties indicate that the RNWs modified by discrete Ag NPs (Ag@RNWs) display an ∼3-fold enhancement in gas response at room temperature compared with pristine SiNWs. Meanwhile, transient response and ultrafast recovery are observed for the Ag@RNW sensor (<i>t</i>_res ≤ 2 s and <i>t</i>_rec ≤ 9 s to 0.33–10 ppm of NH₃). The study demonstrates the considerable effect and potential of the Ag modification process developed in this work. A resistance effect model was further suggested to clarify the underlying mechanism of the enhanced response and the response saturation characteristic of the Ag@RNWs. The promotion of TMAH etching-induced microstructure modulation to sensing properties was also demonstrated

Analysis of four homologs in reveals new viewpoints of the evolution and functions of this gene family-9

Tters upside of the branch lines show the duplication events as clarified by Wheeler et al. [16] (see discussion for detailed description). It is obvious that all of the Asense proteins are grouped to one clade and the proneural genes are grouped to another within the insect group. Bm-ASH2 and Bm-ASH3 are grouped to a sub-clade parallel the one which Bm-ASH1 is sorted in. Ag-ASH, Achaete-Scute homolog (Genbank: ); Am-ASH,Achaete-Scute homolog (Genbank: ); B-ASH1, Butterfly (Genbank: ) Achaete-Scute homolog 1 (Genbank: ); Bm-ASH1, Achaete-Scute homolog 1 (Genbank: ); Bm-ASH2, Achaete-Scute homolog 2 (Genbank: ); Bm-ASH3, Achaete-Scute homolog 3 (Genbank: ); Cn-ASH, Achaete-Scute homolog (Genbank: ); Cs-ASH1, Achaete-Scute homolog 1 (Genbank: ); Cs-ASH2, Achaete-Scute homolog 2 (Genbank: ); Dm-ac, Achaete (Genbank: ); Dm-sc, Scute (Genbank: ); Dm-l'sc, Lethal of scute (Genbank: ); Pc-ASH1, Achaete-Scute homolog 1 (Genbank: ); Tc-ASH, Achaete-Scute homolog (Genbank: ); Ag-ase, Asense (Genbank: ); Am-ase, Asense (Genbank: ); Bm-ase, Asense (Genbank: ); Dm-ase, Asense (Genbank: ); Tc-ase, Asense (Genbank: ).<p><b>Copyright information:</b></p><p>Taken from "Analysis of four homologs in reveals new viewpoints of the evolution and functions of this gene family"</p><p>http://www.biomedcentral.com/1471-2156/9/24</p><p>BMC Genetics 2008;9():24-24.</p><p>Published online 6 Mar 2008</p><p>PMCID:PMC2315653.</p><p></p