Probabilistic downscaling of remote sensing data with applications for multi-scale biogeochemical flux modeling

Upscaling ecological information to larger scales in space and downscaling remote sensing observations or model simulations to finer scales remain grand challenges in Earth system science. Downscaling often involves inferring subgrid information from coarse-scale data, and such ill-posed problems are classically addressed using regularization. Here, we apply two-dimensional Tikhonov Regularization (2DTR) to simulate subgrid surface patterns for ecological applications. Specifically, we test the ability of 2DTR to simulate the spatial statistics of high-resolution (4 m) remote sensing observations of the normalized difference vegetation index (NDVI) in a tundra landscape. We find that the 2DTR approach as applied here can capture the major mode of spatial variability of the high-resolution information, but not multiple modes of spatial variability, and that the Lagrange multiplier (γ) used to impose the condition of smoothness across space is related to the range of the experimental semivariogram. We used observed and 2DTR-simulated maps of NDVI to estimate landscape-level leaf area index (LAI) and gross primary productivity (GPP). NDVI maps simulated using a γ value that approximates the range of observed NDVI result in a landscape-level GPP estimate that differs by ca 2% from those created using observed NDVI. Following findings that GPP per unit LAI is lower near vegetation patch edges, we simulated vegetation patch edges using multiple approaches and found that simulated GPP declined by up to 12% as a result. 2DTR can generate random landscapes rapidly and can be applied to disaggregate ecological information and compare of spatial observations against simulated landscapes

Genes Involved in the Metabolism of Poly-Unsaturated Fatty-Acids (PUFA) and Risk for Crohn's Disease in Children & Young Adults

Epidemiological evidence for the role of polyunsaturated fatty-acids (PUFA) in Crohn's disease (CD) is unclear, although the key metabolite leucotriene B4 (LTB(4)) is closely linked to the inflammatory process. We hypothesized that inherited variation in key PUFA metabolic enzymes may modify susceptibility for CD.A case-control design was implemented at three pediatric gastroenterology clinics in Canada. Children ≤20 yrs diagnosed with CD and controls were recruited. 19 single nucleotide polymorphisms (SNPs) across the ALOX5 (4) CYP4F3 (5) and CYP4F2 (10) genes, were genotyped. Associations between SNPs/haplotypes and CD were examined. A total of 431 cases and 507 controls were studied. The mean (±SD) age of the cases was 12.4 (±3.3) years. Most cases were male (56.4%), had ileo-colonic disease (L3±L4, 52.7%) and inflammatory behavior (B1±p, 87%) at diagnosis. One genotyped CYP4F3 SNP (rs2683037) not in Hardy-Weinberg Equilibrium was excluded. No associations with the remaining 4 CYP4F3 SNPs with CD were evident. However haplotype analysis revealed associations with a two-marker haplotype (TG) (rs3794987 & rs1290617) (p = 0.02; permuted p = 0.08). CYP4F2 SNPs, rs3093158 (OR (recessive) = 0.56, 95% CI = 0.35-0.89; p = 0.01), rs2074902 (OR (trend) = 1.26, 95% CI = 1.00-1.60; p = 0.05), and rs2108622 (OR (recessive) = 1.6, 95% CI = 1.00-2.57; p = 0.05) were significantly associated whereas rs1272 (OR (recessive) = 0.58, 95% CI = 0.30-1.13; p = 0.10) showed suggestions for associations with CD. A haplotype comprising these 4 SNPs was significantly associated (p = 0.007, permuted p = 0.02) with CD. Associations with SNP rs3780901 in the ALOX5 gene were borderline non-significant (OR (dominant) = 1.29, 95% CI = 0.99-1.67; p = 0.056). A haplotype comprising the 4 ALOX5 SNPs (TCAA, p = 0.036) was associated with CD, but did not withstand corrections for multiple comparisons (permuted p = 0.14).Inherited variation in enzymes involved in the synthesis/metabolism of LTB(4) may be associated with CD. These findings implicate PUFA metabolism as a important pathway in the CD pathogenesis