Landscape Pattern Response to Changes in the Pattern Generation Rules: Land-use Legacies in Forestry

The Pacific Northwest of the United States is currently embroiled in an acrimonious debate over the management of federal forest lands. Constructive resolution of this debate will require better information on a broad range of forest management issues. This study focuses on one such issue: the development of landscape pattern in response to alternative forest cutting plans and the degree to which established landscape patterns can be changed. Dispersed cutting has been conducted on federal lands in the western United States for \u3e40 yr, but alternative cutting plans are now being considered. To assess the effects of different disturbance processes on the development of landscape pattern, we compare dispersed- and aggregated-cutting plans using a simple, rule-based simulation model that incorporates realistic regulatory and logistic constraints. Our results indicate that, once established, the landscape pattern created by dispersed disturbances is difficult to erase without a substantial reduction in the disturbance rate or a reduction in the minimum stand age eligible for disturbance. Change in landscape pattern can lag substan­tially behind change in the rules governing pattern generation

Multi Scale Habitat Relationships of Martes americana in Northern Idaho, U.S.A

We used bivariate scaling and logistic regression to investigate multiple-scale habitat selection by American marten (Martes americana). Bivariate scaling reveals dramatic differences in the apparent nature and strength of relationships between marten occupancy and a number of habitat variables across a range of spatial scales. These differences include reversals in the direction of an observed association from positive to negative and frequent dramatic changes in the apparent importance of a habitat variable as a predictor of marten occurrence. Logistic regression on the optimally scaled input variables suggests that at the scale of home ranges, marten select landscapes with high average canopy closure and low fragmentation. Within these low fragmented landscapes, marten select foraging habitat at a fine scale within late-seral, middle-elevation mesic forests. In northern Idaho, optimum American marten habitat, therefore, consists of landscapes with low road density, low density of non-forest patches with high canopy closure, and large areas of middle-elevation, late successional mesic forest. Comparison of current landscape conditions to those expected under the historic range of variability indicates that road building and timber harvest in the past century may have substantially reduced the amount of suitable marten habitat in northern Idaho. Our results are generally consistent with previous research in the Rocky Mountains, with additional insights related to the relative importance, functional form, and scale at which each habitat variable has the largest influence on marten occurrence

Characterization of an Unmanned Aerial System for Detection of Wetland Methane Emission Hotspots

Undergraduate Honors research project using low-cost methane gas sensors mounted on an unmanned aerial vehicle for remote sensing of gas emissions from wetlands. The report also includes experimental calibration work done to improve upon sensor accuracy

Uncertain R&D Outcomes and Cooperation in R&D

The present paper provides a brief survey of some of the papers dealing with R&D uncertainty. This helps us identify which factors are more favorable for cooperative R&D and which factors are not. The paper provides the analysis under a unified framework. We take the classic paper by Marjit (1991) as the benchmark case, and then proceeds to examine whether, or to what extent, Marjit result will undergo a change with respect to different assumptions related to R&D investment

Landscape-level Analysis of Mountain Goat Population Connectivity in Washington and Southern British Columbia

Habitat fragmentation and habitat loss diminish population connectivity, reducing genetic diversity and increasing extinction risk over time. Improving connectivity is widely recommended to preserve the long-term viability of populations, but this requires accurate knowledge of how landscapes influence connectivity. Detectability of landscape effects on gene flow is highly dependent on landscape context, and drawing conclusions from single landscape studies may lead to ineffective management strategies. We present a novel approach to elucidate regional variation in the relative importance of landscape variable effects on gene flow. We demonstrate this approach by evaluating gene flow between isolated, genetically impoverished mountain goat (Oreamnos americanus) populations in Washington and much larger, genetically robust populations in southern British Columbia. We used GENELAND to identify steep genetic gradients and then employed individual-based landscape genetics in a causal modeling framework to independently evaluate landscape variables that may be generating each of these genetic gradients. Our results support previous findings that freeways, highways, water, agriculture and urban landcover limit gene flow in this species. Additionally, we found that a previously unsupported landscape variable, distance to escape terrain, also limits gene flow in some contexts. By integrating GENELAND and individual-based methods we effectively identified regional limiting factors that have landscape-level implications for population viability

Estimating Live Forest Carbon Dynamics with a Landsat-based Curve-fitting Approach

Direct estimation of aboveground biomass with spectral reflectance data has proven challenging for high biomass forests of the Pacific Northwestern United States. We present an alternative modeling strategy which uses Landsat’s spatial, spectral and temporal characteristics to predict live forest carbon through integration of stand age and site index maps and locally calibrated Chapman-Richards curves. Predictions from the curve-fit model were evaluated at the local and landscape scales using two periods of field inventory data. At the pixel-level, the curve-fit model had large positive bias statistics and at the landscape scale over-predicted study area carbon for both inventory periods. Despite the over-estimation, the change in forest carbon estimated by the curve-fit model was well within the standard error of the inventory estimates. In addition to validating the curve-fit models carbon predictions we used Landsat data to evaluate the degree to which the field inventory plots captured the forest conditions of the study area. Landsat-based frequency histograms revealed the systematic sample of inventory plots effectively captured the broad range of forest conditions found in the study area, whereas stand age trajectories revealed a temporally punctuated shift in land- use which was not spectrally detected by the inventory sample

Dicer and miRNA in relation to clinicopathological variables in colorectal cancer patients

<p>Abstract</p> <p>Background</p> <p>Dicer is aberrantly expressed in several types of cancers. Applying real-time PCR, we detected the expression of Dicer mRNA in normal mucosa (n = 162), primary colorectal cancer (CRC) (n = 162) and liver metastasis (n = 37), and analysed the relationship between Dicer expression and clinicopathological features. We also correlated the expression of Dicer mRNA to the miRNA expression of miR-141, miR-200a, miR-200b, mir-200c and miR-429 in liver metastases.</p> <p>Methods</p> <p>RT-PCR and qPCR were used to analyse the Dicer expression in normal mucosa, primary tumour and liver metastasis by using the High Capacity cDNA Reverse Transcription Kit and TaqMan™^®Gene Expression assays for <it>Dicer </it>and <it>GAPDH</it>. RT-PCR and qPCR were used to detect miRNA expression in liver metastases by utilizing TaqMan^®MicroRNA Reverse Transcription Kit and TaqMan^®miRNA Assays. Statistical analyses were performed with STATISTICA.</p> <p>Results</p> <p>Dicer expression in rectal cancer (3.146 ± 0.953) was higher than in colon cancer (2.703 ± 1.204, P = 0.018). Furthermore the Dicer expression was increased in primary tumours (3.146 ± 0.952) in comparison to that in normal mucosa from rectal cancer patients (2.816 ± 1.009, P = 0.034) but this is not evident in colon cancer patients. Dicer expression in liver metastases was decreased in comparison to that of either normal mucosa or primary tumour in both colon and rectal cancers (P < 0.05). Patients with a high Dicer expression in normal mucosa had a worse prognosis compared to those with a low Dicer expression, independently of gender, age, tumour site, stage and differentiation (P < 0.001, RR 3.682, 95% CI 1.749 - 7.750). In liver metastases, Dicer was positively related to miR-141 (R = 0.419, P = 0.015).</p> <p>Conclusion</p> <p>Dicer is up-regulated in the early development of rectal cancers. An increased expression of Dicer mRNA in normal mucosa from CRC patients is significantly related to poor survival independently of gender, age, tumour site, stage and differentiation.</p

Embryology and bony malformations of the craniovertebral junction

BACKGROUND: The embryology of the bony craniovertebral junction (CVJ) is reviewed with the purpose of explaining the genesis and unusual configurations of the numerous congenital malformations in this region. Functionally, the bony CVJ can be divided into a central pillar consisting of the basiocciput and dental pivot and a two-tiered ring revolving round the central pivot, comprising the foramen magnum rim and occipital condyles above and the atlantal ring below. Embryologically, the central pillar and the surrounding rings descend from different primordia, and accordingly, developmental anomalies at the CVJ can also be segregated into those affecting the central pillar and those affecting the surrounding rings, respectively. DISCUSSION: A logical classification of this seemingly unwieldy group of malformations is thus possible based on their ontogenetic lineage, morbid anatomy, and clinical relevance. Representative examples of the main constituents of this classification scheme are given, and their surgical treatments are selectively discussed

Consensus coding sequence (CCDS) database: a standardized set of human and mouse protein-coding regions supported by expert curation.

The Consensus Coding Sequence (CCDS) project provides a dataset of protein-coding regions that are identically annotated on the human and mouse reference genome assembly in genome annotations produced independently by NCBI and the Ensembl group at EMBL-EBI. This dataset is the product of an international collaboration that includes NCBI, Ensembl, HUGO Gene Nomenclature Committee, Mouse Genome Informatics and University of California, Santa Cruz. Identically annotated coding regions, which are generated using an automated pipeline and pass multiple quality assurance checks, are assigned a stable and tracked identifier (CCDS ID). Additionally, coordinated manual review by expert curators from the CCDS collaboration helps in maintaining the integrity and high quality of the dataset. The CCDS data are available through an interactive web page (https://www.ncbi.nlm.nih.gov/CCDS/CcdsBrowse.cgi) and an FTP site (ftp://ftp.ncbi.nlm.nih.gov/pub/CCDS/). In this paper, we outline the ongoing work, growth and stability of the CCDS dataset and provide updates on new collaboration members and new features added to the CCDS user interface. We also present expert curation scenarios, with specific examples highlighting the importance of an accurate reference genome assembly and the crucial role played by input from the research community. Nucleic Acids Res 2018 Jan 4; 46(D1):D221-D228