Improving the representation of forests in hydrological models.

Forests play a critical role in the hydrologic cycle, impacting the surface and groundwater dynamics of watersheds through transpiration, interception, shading, and modification of the atmospheric boundary layer. It is therefore critical that forest dynamics are adequately represented in watershed models, such as the widely applied Soil and Water Assessment Tool (SWAT). SWAT's default parameterization generally produces unrealistic forest growth predictions, which we address here through an improved representation of forest dynamics using species-specific re-parameterizations. We applied this methodology to the two dominant pine species in the southeastern U.S., loblolly pine (Pinus taeda L.) and slash pine (Pinus elliotti). Specifically, we replaced unrealistic parameter values related to tree growth with physically meaningful parameters derived from publicly available remote-sensing products, field measurements, published literature, and expert knowledge. Outputs of the default and re-parameterized models were compared at four pine plantation sites across a range of management, soil, and climate conditions. Results were validated against MODIS-derived leaf area index (LAI) and evapotranspiration (ET), as well as field observations of total biomass. The re-parameterized model outperformed the default model in simulating LAI, biomass accumulation, and ET at all sites. The two parametrizations also resulted in substantially different mean annual water budgets for all sites, with reductions in water yield ranging from 13 to 45% under the new parameterization, highlighting the importance of properly parameterizing forest dynamics in watershed models. Importantly, our re-parameterization methodology does not require alteration to the SWAT code, allowing it to be readily adapted and applied in ongoing and future watershed modeling studies.

Adsorption Kinetics of Glycated Hemoglobin on Aptamer Microarrays with Antifouling Surface Modification.

Aptamers are oligonucleotides that bind with high affinity to target molecules of interest. One such target is glycated hemoglobin (gHb), a biomarker for assessing glycemic control and diabetes diagnosis. By the coupling of aptamers with surface plasmon resonance (SPR) sensing surfaces, a fast, reliable and inexpensive assay for gHb can be developed. In this study, we tested the affinity of SPR-sensing surfaces, composed of aptamers and antifouling self-assembled monolayers (SAMs), to hemoglobin (Hb) and gHb. First, we developed a gHb-targeted aptamer (GHA) through a modified Systematic Evolution of Ligands by EXponential (SELEX) enrichment process and tested its affinity to gHb using the Nano-Affi protocol. GHA was used to produce three distinct SAM-SPR-sensing surfaces: (Type-1) a SAM of GHA directly attached to a sensor surface; (Type-2) GHA attached to a SAM of 11-mercaptoundecanoic acid (11MUA) on a sensor surface; (Type-3) GHA attached to a binary SAM of 11MUA and 3,6-dioxa-8-mercaptooctan-1-ol (DMOL) on a sensor surface. Type-2 and Type-3 surfaces were characterized by cyclic voltammetry and electrochemical impedance spectroscopy to confirm that GHA bound to the underlying SAMs. The adsorption kinetics for Hb and gHb interacting with each SPR sensing surface were used to quantify their respective affinities. The Type-1 surface without antifouling modification had a dissociation constant ratio (KD,Hb/KD,gHb) of 9.7, as compared to 809.3 for the Type-3 surface, demonstrating a higher association of GHA to gHb for sensor surfaces with antifouling modifications than those without. The enhanced selectivity of GHA to gHb can likely be attributed to the inclusion of DMOL in the SAM-modified surface, which reduced interference from nonspecific adsorption of proteins. Results suggest that pairing aptamers with antifouling SAMs can significantly improve their target affinity, potentially allowing for the development of novel, low cost, and fast assays.