Site-specific Relationships Research Articles

Estimation of potato yield using a semi-mechanistic model developed by proximal remote sensing and environmental variables

Timely monitoring of potato yield status is crucial for guiding field management and ensuring the sustainability of food trade. In recent years, non-destructive remote sensing techniques have emerged as one of the most promising methods for crop yield monitoring. However, most existing potato yield estimation models have primarily been tested at specific growth stages within a single ecosystem, highlighting the urgent need for a model that can be applied across different ecological environments. In this study, we developed a semi-physical model based on hierarchical linear modeling (HLM) to automatically correct yield estimation based on remotely sensed vegetation indices using environmentally relevant variables such as net solar radiation at the surface (ssr), air temperature at 2 m above the surface (t2m), and soil water content in the root zone (swvl). The accuracy and transferability of the model were further evaluated by comparing it with aboveground destructive sampling methods, conventional empirical models, and machine learning approaches. The results demonstrated that site-specific relationships exist between aboveground agronomic traits parameters like biomass and leaf area index (LAI) with respect to yield estimation. Conventional linear statistical and machine learning methods faced challenges in transferring their constructed yield estimation models across regions and years. However, the HLM approach exhibited excellent generalization ability across all trial samples. In the middle and later stages of potato growth, the standardized LAI determining index proved to be the most effective vegetation for predicting yield, while ssr, sktmax, and shallow swvl were identified as key environmental variables affecting yield. By integrating these variables using HLM modeling techniques, we achieved optimal generalization performance (R2 = 0.57, RMSE = 7.65 t/ha, NRMSE = 25.02 % during tuber growth stage; R2 = 0.60, RMSE = 7.37 t/ha, NRMSE = 24.13 % during starch accumulation stage). This study underscores the importance of considering environmental factors when constructing a reliable model for estimating potato yield at different spatial and temporal scales using remote sensing technology.

Intercomparison of marine tracer and catchment-based submarine groundwater discharge estimates for a karst aquifer

Submarine groundwater discharge (SGD) is a major source of solutes to the ocean. Consequently, the accuracy of estimates of the magnitude and seasonal variability of SGD is critical for the management of coastal marine ecosystems. However, very few intercomparison studies between different conceptual approaches have been made to assess the reliability and consistency of SGD flow estimates while simultaneously gauging the applicability of underlying models and budget assumptions in real-world scenarios. To date, intercomparison efforts have focused on homogeneous aquifers, and less so on highly heterogeneous aquifers such as karst systems. Here we compare the results of tracer-based (salt mass balance, tidal prism and radon mass balances) and catchment-based methods (water balance, semi-distributed karst network model) to assess SGD at a data-rich coastal location. All approaches tested here reveal a positive relationship between SGD fluxes and groundwater level measured close to the preferential groundwater flow pathways in the phreatic karst aquifer (e.g. water-saturated conduits or fracture network). We use this finding to derive site-specific relationships between groundwater level and SGD flow rates. We derive these relationships from least square fitting of Darcian and Non-Darcian models and regression analysis. The relationships validate the findings derived independently from hydraulic/hydrogeological modelling of the complex karst networks. By combining various estimates made with distinct assumptions, this method produces robust estimates of the SGD seasonal variability, essential to develop optimal management strategies of SGD resources in coastal karstic regions. Where direct measurements of SGD are not possible, monitoring of coastal groundwater level close to preferential phreatic groundwater pathways can be thus used as a useful indicator to compare past groundwater flow measurements and derive site-specific relationships, particularly in settings where large flow rate changes are present such as karst aquifers.

Alterations in GLP-1 and PYY release with aging and body mass in the human gut

The lining of our intestinal surface contains an array of hormone-producing cells that are collectively our bodies’ largest endocrine cell reservoir. These “enteroendocrine” (EE) cells reside amongst the billions of absorptive epithelial and other cell types that line our gastrointestinal tract and can sense and respond to the ever-changing internal environment in our gut. EE cells release an array of important signalling molecules that can act as hormones, including glucagon-like peptide (GLP-1) and peptide YY (PYY) which are co-secreted from L cells. While much is known about the effects of these hormones on metabolism, insulin secretion and food intake, less is understood about their secretion from human intestinal tissue. In this study we assess whether GLP-1 and PYY release differs across human small and large intestinal tissue locations within the gastrointestinal tract, and/or by sex, body weight and the age of an individual. We identify that the release of both hormones is greater in more distal regions of the human colon, but is not different between sexes. We observe a negative correlation of GLP-1 and BMI in the small, but not large, intestine. Increased aging correlates with declining secretion of both GLP-1 and PYY in human large, but not small, intestine. When the data for large intestine is isolated by region, this relationship with age remains significant for GLP-1 in the ascending and descending colon and in the descending colon for PYY. This is the first demonstration that site-specific differences in GLP-1 and PYY release occur in human gut, as do site-specific relationships of L cell secretion with aging and body mass.

Bone-cartilage crosstalk informed by aging mouse bone transcriptomics and human osteoarthritis genome-wide association studies

Subchondral bone participates in crosstalk with articular cartilage to maintain joint homeostasis, and disruption of either tissue results in overall joint degeneration. Among the subchondral bone changes observed in osteoarthritis (OA), subchondral bone plate (SBP) thickening has a time-dependent relationship with cartilage degeneration and has recently been shown to be regulated by osteocytes. Here, we evaluate the effect of age on SBP thickness and cartilage degeneration in aging mice. We find that SBP thickness significantly increases by 18-months of age, corresponding temporally with increased cartilage degeneration. To identify factors in subchondral bone that may participate in bone cartilage crosstalk or OA, we leveraged mouse transcriptomic data from one joint tissue compartment – osteocyte-enriched bone – to search for enrichment with human OA in UK Biobank and Arthritis Research UK Osteoarthritis Genetics (arcOGEN) GWAS using the mouse2human (M2H, www.mouse2human.org) strategy. Genes differentially expressed in aging mouse bone are significantly enriched for human OA, showing joint site-specific (knee vs. hip) relationships, exhibit temporal associations with age, and unique gene clusters are implicated in each type of OA. Application of M2H identifies genes with known and unknown functions in osteocytes and OA development that are clinically associated with human OA. Altogether, this work prioritizes genes with a potential role in bone/cartilage crosstalk for further mechanistic study based on their association with human OA in GWAS.

Quantification of soil textural and hydraulic properties in a complex conductivity imaging framework: Results from the Wolfsegg slope

We present an approach that permits to predict hydraulic conductivity from extensive, multi-methodical geophysical data collected on a hillslope affected by landslides in Austria. The objective of the investigation is the spatial characterization of a slope affected by mass movements to derive hydrogeological structures and preferential flow paths. The geophysical data sets presented in this study consists of 24 densely distributed complex conductivity (CC) imaging profiles, collocated to these profiles we also collected 517 transient electromagnetic (TEM) soundings and 10 refraction seismic tomography (RST) profiles. Additionally, we also present well-logging data (namely electrical resistivity, natural gamma logs) collected in five boreholes. Cores recovered during the drilling of the boreholes are used to aid in the interpretation of the geophysical units, while analysis of the sediments was conducted to obtain grain size distributions, cation exchange capacity and mineralogy of the subsurface materials. While all geophysical data was processed initially independently, the final complex conductivity imaging results are based on the incorporation of structural constraints about the electrical units obtained from the TEM soundings. The interpretation of the resolved CC units is then sustained by the RST images and the lithological information from the boreholes. We estimate then the hydraulic conductivity of the subsurface derived from the CC images using a two-step approach. In a first step, we investigated the link between the complex conductivity and the different soil volume fractions of gravel, sand, silt and clay. In a second step, we applied a pedo-transfer function, namely the well-known Rosetta model, that permits to predict the hydraulic conductivity from the estimated grain size volumes. This approach allowed a quantitative interpretation of the geophysical data and thus a 3-dimensional (3D) representation of the grain size distribution and hydraulic conductivity in the investigated slope section. Thereby, we observed well-determined site-specific relationships (R2 > 0.7) from the comparison of the complex resistivity images and grain size analysis. The obtained hydrogeophysical 3D model permits to delineate the geometry of an aquiclude, and, thus, the analysis of preferential water-flow paths. In particular, we can identify a spatial correlation between the aquiclude interface and morphological features.

Environmental harshness mediates the relationship between aboveground and belowground communities in Antarctica

Linkages between aboveground and belowground communities are a key but globally under-researched component of responses to environmental change. Given the logistical complications to studying these relationships, much of our knowledge derives from laboratory experiments and localized field studies which have so far yielded inconsistent results. Because environmental factors may alter relationships between above- and belowground communities, there is a need for broad-scale field studies testing these interactions. The Antarctic Peninsula provides an ideal test setting, given the relatively simple communities both above- and belowground. The Peninsula is also experiencing rapid environmental changes, including alterations in species diversity and distribution both above- and belowground. Thus, an improved understanding of the broad-scale consequences of altered environments and vegetation communities for the soil microbiome is of high priority. To determine the nature and strength of the relationship between in situ plant and soil communities across a broad spatial scale and range of environmental conditions, we sampled soil communities at 9 locations (spanning 60–72°S along the Scotia Arc and Antarctic Peninsula) beneath the major aboveground habitats (moss, grass, lichen, algae and bare soil). We measured a comprehensive suite of soil physicochemical properties, microbial (bacterial and fungal) diversity and composition, and invertebrate abundance and community composition to determine the relationships between plant and soil communities. Our results suggest that, with increased environmental severity, plant cover types become more important for influencing the physicochemical soil environment, and therefore the soil microbial communities. Although we found site-specific relationships, broad-scale patterns reveal significant differences among bare soils and vegetated soils, particularly soils beneath grass and moss. This suggests that expansion of vegetation communities under current climate warming projections will be accompanied by shifts in the soil microbiome, with important implications for the ecosystem functioning with which they are associated.

Site Specific Relationships between COVID-19 Cases and SARS-CoV-2 Viral Load in Wastewater Treatment Plant Influent.

Wastewater based epidemiology (WBE) has become an important tool during the COVID-19 pandemic, however the relationship between SARS-CoV-2 RNA in wastewater treatment plant influent (WWTP) and cases in the community is not well-defined. We report here the development of a national WBE program across 28 WWTPs serving 50% of the population of Scotland, including large conurbations, as well as low-density rural and remote island communities. For each WWTP catchment area, we quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases. Daily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation (ρ > 0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from 25 cases for larger plants to a single case in smaller plants. SARS-CoV-2 viral RNA load can be used to predict the number of cases detected in the WWTP catchment area, with a clear statistically significant relationship observed above site-specific case thresholds.

Quantifying Drivers of Coastal Forest Carbon Decline Highlights Opportunities for Targeted Human Interventions

As coastal land use intensifies and sea levels rise, the fate of coastal forests becomes increasingly uncertain. Synergistic anthropogenic and natural pressures affect the extent and function of coastal forests, threatening valuable ecosystem services such as carbon sequestration and storage. Quantifying the drivers of coastal forest degradation is requisite to effective and targeted adaptation and management. However, disentangling the drivers and their relative contributions at a landscape scale is difficult, due to spatial dependencies and nonstationarity in the socio-spatial processes causing degradation. We used nonspatial and spatial regression approaches to quantify the relative contributions of sea level rise, natural disturbances, and land use activities on coastal forest degradation, as measured by decadal aboveground carbon declines. We measured aboveground carbon declines using time-series analysis of satellite and light detection and ranging (LiDAR) imagery between 2001 and 2014 in a low-lying coastal region experiencing synergistic natural and anthropogenic pressures. We used nonspatial (ordinary least squares regression–OLS) and spatial (geographically weighted regression–GWR) models to quantify relationships between drivers and aboveground carbon declines. Using locally specific parameter estimates from GWR, we predicted potential future carbon declines under sea level rise inundation scenarios. From both the spatial and nonspatial regression models, we found that land use activities and natural disturbances had the highest measures of relative importance (together representing 94% of the model’s explanatory power), explaining more variation in carbon declines than sea level rise metrics such as salinity and distance to the estuarine shoreline. However, through the spatial regression approach, we found spatial heterogeneity in the relative contributions to carbon declines, with sea level rise metrics contributing more to carbon declines closer to the shore. Overlaying our aboveground carbon maps with sea level rise inundation models we found associated losses in total aboveground carbon, measured in teragrams of carbon (TgC), ranged from 2.9 ± 0.1 TgC (for a 0.3 m rise in sea level) to 8.6 ± 0.3 TgC (1.8 m rise). Our predictions indicated that on the remaining non-inundated landscape, potential carbon declines increased from 29% to 32% between a 0.3 and 1.8 m rise in sea level. By accounting for spatial nonstationarity in our drivers, we provide information on site-specific relationships at a regional scale, allowing for more targeted management planning and intervention. Accordingly, our regional-scale assessment can inform policy, planning, and adaptation solutions for more effective and targeted management of valuable coastal forests.

Assessment of the Maximum Permissible Load of Pollutant in an opened coastal zone using a water quality model: a case study in Hainan of China

This study aims to estimate the maximum-permissible-loads of pollutant by means of water quality modelling, in order to maintain the concentrations of pollutions below prescribed water quality targets. Modelling of water quality used the Mike21 HD and ecolab modules, while the assessment of maximum-permissible-loads of pollution used the method of response factor coefficient. This research is descriptive quantitative parameters of COD. A scenario assessment was carried out by the flows from various point sources to understand the site-specific relationships between pollution sources and water quality conditions, as well as calculating the maximum-permissible-loads to determine the pollution point source discharge.

Bacterial and archaeal community structure in benthic sediments from glacial lakes at the Múlajökull Glacier, central Iceland

Glacial lakes and their sediments are highly sensitive temporal markers of environmental variability. The combination of particular geographical conditions with climate changes makes the Mulajokull lakes an appropriate model for revealing some site-specific and common relationships in psychrophilic microbial ecology. The aim of this study was to evaluate the taxonomic and functional diversity of microbial community structures in five glacial lake sediments situated at different distances from the glacier, i.e., 50 m to 1750 m from the ice margin. The Shannon diversity indices varied in the range from 1.99 to 2.94 (with the lowest in C sample) tested by EcoPlates™ and from 1.69 to 1.89 at the phylum level (with the lowest in A sample) tested by the shotgun metagenomic sequencing, respectively. An inter-sample comparison was also conducted. Overall, six bacteria phyla (Proteobacteria, Cyanobacteria, Bacteroidetes, Actinobacteria, Verrucomicrobia and Planctomycetes) and one microalgae phyla (Bacillariophyta) were detected in five lake sediments tested at abundancy that exceeded 1%. Obtained data brings new knowledge related to the cold biosphere on the local and global Earth systems.

An epidemiologic approach to environmental monitoring: cyanobacteria in Australia’s Murray–Darling basin

Risk based management of aquatic resources for ecosystem and public health requires water managers and health professionals to work together. Using an epidemiologic time-series modelling approach, we assess patterns of risk for alert-level cyanobacterial abundance with water temperature. We focus on six sites along the Murray–Darling Drainage Basin, using the longest continuous record of algal abundance in Australia. Alert-level cyanobacterial abundance showed a non-linear and lagged response to water temperature across all six sites, after controlling for relative water discharge. For three sites there was a positive relationship of high-water temperature with the risk of alert-level abundance. These three sites also showed a substantial lagged effect, with the risk remaining high at a lag of 1 month following high water temperatures. The higher than average risk of alert-level cyanobacterial abundance with extreme water temperature and the persistence of this effect for 1 month highlight the applicability of these models to understand non-linear and time-dependent relationships in complex systems which are managed for ecosystem and population health. The site-specific relationships provide guidance for local authorities to develop water quality-related environmental and public health responses to a variable climate.

Bed-Sediment Transport Conditions along the Sagavanirktok River in Northern Alaska, USA

This manuscript presents a study in predicting bed-sediment transport rates along the Sagavanirktok River in Alaska. Extensive field activities took place to accomplish this goal: four hydro-meteorological stations were installed in a 150 km reach along the river in summer 2015. During the same year, pits were excavated near the stations, and in subsequent summers, the pits were surveyed multiple times in conjunction with taking discharge measurements. Water slope was measured and bed sediment was characterized. Site-specific relationships between water levels and cross-section water depths were developed. Volume change between consecutive surveys was calculated, and main flood events between surveys were identified. Finally, the first bed-sediment transport equations valid for the Sagavanirktok River were developed. Considering the intrinsic error in sediment transport predictions, the agreement between predicted and measured sediment transport values is good. These equations could be used by resource managers when predicting the expected time for an excavated material site in the Sagavanirktok River to refill.

Ecoregional or site-specific lake nutrient criteria? Evidence from ecological fallacy

Abstract Ecoregional nutrient criteria are widely used but their validity has rarely been verified competed with site-specific criteria. In this study, we introduced ecological fallacy, which describes phenomenon that site-specific stressor-response relationships cannot be deducted from ecoregional relationship and vice versa, to explore the spatial scale of nutrient criteria. A long-term and nationwide water quality dataset of lakes and reservoirs was used to determine if ecological fallacy existed or not. Ecoregional and site-specific nutrient-Chlorophyll a relationships were built employing Bayesian linear model and hierarchical model, respectively. By comparing ecoregional and site-specific relationships, we found that ecological fallacy existed in each ecoregion. Ecoregional relationship may misidentify limiting nutrient or miscalculate the nutrient effect direction or magnitude. We found huge differences between estimated Chlorophyll a concentrations deduced from regional and site-specific relationships conditioning average TN or TP concentrations. Based on these results, we determined that lake nutrient criteria should be site-specific, primarily to avoid ecological fallacy rather than to improve their accuracy. These findings could guide the future nutrient criteria development. We further recommended partial pooling of data to develop stressor-response relationship facing with intensive environmental and ecological data.

Groundwater contamination risks from conservative point source pollutants in a future climate

ABSTRACT The groundwater contamination risk in future climates was investigated at three locations in Sweden. Solute transport penetration depths were simulated using the HYDRUS-1D model using historical data and an ensemble of climate projections including two global climate models (GCMs), three emission scenarios and one regional climate model. Most projections indicated increasing precipitation and evapotranspiration until mid-century with a further increase at end-century. Results showed both increasing and decreasing groundwater contamination risks depending on emission scenario and GCM. Generally, the groundwater contamination risk is likely to be unchanged until mid-century, but higher at the end of the century. Soil and site specific relationships between Δ(P – PET) (i.e. change in the difference between precipitation, P, and potential evapotranspiration, PET) and changes in solute transport depths were determined. Using this, changes in solute transport depths for other climate projections can be assessed.

Assessment of difference in the atmospheric surface layer turbulence characteristics during thunderstorm and clear weather days over a tropical station

The present study analyses the atmospheric surface layer characteristics (non-dimensionalised standard deviation of temperature and wind) during days of thunderstorm (DT) and clear weather days (CWD) during the months of pre-monsoon for years 2007, 2009 and 2010 at a tropical station Kharagpur (22°30′N, 87o20′E), India using the data sets collected by a 50-m instrumented tower. The study proposes site-specific relationships for thermal and mechanical characteristics of turbulence concerning atmospheric stability during DT and CWD during the pre-monsoon season. Although the analysis has not considered the data during the thunderstorm events (removed due to quality check), the relationships are different in CWD and DT cases. It is observed that during unstable stratification of CWD, values are less dispersed compared to the unstable region of DT. The study also reveals differences for stable stratification of DT and CWD days; even the thunderstorms are occurring during an unstable regime. The turbulence intensity for wind obeys the 1/3 power law, whereas for the unstable (stable) region of the temperature the − 1/3 (− 1) slope exists.

Site-Specific Relationships between Bedrock Depth and HVSR Fundamental Resonance Frequency Using KiK-NET Data from Japan

It is commonly accepted that the horizontal-to-vertical spectral ratio (HVSR) technique enables the detection of the fundamental resonance frequency ($$f_{\text{HVSR}}$$) of a given site. The utility of this $$f_{\text{HVSR}}$$ is analyzed using the nonlinear regression relationships between $$f_{\text{HVSR}}$$ and bedrock depth ($$h$$). The derived relationships are mostly site-specific, so that the present paper consists of two main parts. The first is a literature review for the available empirical relationships between $$f_{\text{HVSR}}$$ and $$h$$. The aim of this part is to highlight the practical limitations of these established relationships and to make fair comparisons. The second is to generate new relationships, taking advantage of the very wide range of available lithological, geophysical, and geotechnical borehole drilling data of the 697 KiK-NET seismic stations in Japan. For this purpose, HVSR are calculated using 10,000 weak earthquakes or linear events recorded at KiK-NET stations to determine the $$f_{\text{HVSR}}$$ and correlate it with the corresponding $$h$$. The overlying layers/bedrock interface falling within sedimentary, igneous, or metamorphic layers significantly affect the derived frequency–depth relationships. In addition, these relationships are strongly reproduced by the $$V_{\text{p}} /V_{\text{s}}$$ ratio of the bedrock in the range of 1.6–2.2. Interestingly, it is found that $$f_{\text{HVSR}}$$ less than 1 Hz corresponding to $$h$$ more than 100 m leads the trend of the overall frequency–depth relationship.

Bog breathing: the extent of peat shrinkage and expansion on blanket bogs in relation to water table, heather management and dominant vegetation and its implications for carbon stock assessments

Peatlands represent a globally important carbon stock. Peat soil carbon stock assessments rely on measurements of carbon concentration, bulk density and soil depth. However, peat surface levels - and thus soil depths - change (“bog breathing”) largely as a response to peat shrinkage and expansion in relation to water table changes. This study assessed the magnitude of and potential for this mechanism to influence carbon stock calculations under field and laboratory conditions. In the UK, most peatlands are upland blanket bogs, of which a large proportion are managed as ‘grouse moors’. This currently involves rotational burning, although alternative management is increasingly considered. Peat depth and water tables were investigated on three grouse moors on blanket bog in northern England, comparing changes under different heather management interventions (burning, mowing and uncut). One site also allowed investigation of changes in relation to slope and under the three major bog vegetation types (ling heather, cottongrass and Sphagnum moss), which were compared to observed changes in peat cores under controlled laboratory conditions simulating periods of drought and rewetting. Changes in depth and bulk density were recorded and the potential implications for carbon stock estimates were calculated. Results highlight site specific relationships as potential habitat condition indicators and demonstrate that previously reported surface peat carbon losses resulting from enhanced decomposition under rising temperatures might also be explained by apparent changes due to peat shrinkage and expansion. It is recommended to accurately record bulk density and total peat depth measurements as part of peat carbon stock assessments.

SAT-528 BMI and Relationship to Prior Fracture in the Super Obese

Background: Super obesity, defined as BMI ≥ 50 kg/m2, comprises approximately 1.4% percent of the adult U.S. population and has been rising significantly over the past two decades. While obesity is considered to be protective against fracture, existing literature suggests that obesity affects fracture risk in a site-specific manner. In particular, higher risk of fracture has been observed at the lower leg/ankle and upper arm/shoulder, while lower risk of fracture has been observed at the hip, wrist, and spine. It is not clear if these site-specific relationships continue indefinitely as BMI reaches the super obese levels. Thus, the purpose of this study was to examine associations of BMI and history of fracture in a large academic center with a high rate of super obesity. Methods: Subjects at least 40 years old with BMI ≥50 were selected using the electronic medical record (EMR). History of prior fracture was identified via ICD codes and reviewed for accuracy. Comorbid conditions were also derived from ICD codes and used to derive the Charlson Comorbidity Index (Quan Modification) as a composite comorbidity index. Subjects with history of bariatric surgery were excluded. Clavicle fractures were excluded in multivariate modeling due to small number. Results: Of 6,181 subjects with super obesity, 145 subjects (2.3%) were identified as having prior history of fracture. These 145 subjects were of similar age, gender, and race-ethnicity, but lower BMI (53.3±4.1 vs. 54.2±5.2, p=0.039) than those without fracture history. Among these 145 subjects, a total of 172 fractures were identified. Lower leg/ankle fractures were most prevalent (30.2%), followed by forearm (15.7%), upper arm/shoulder (13.4%), and foot (11.6%). Of the 161 fractures where information regarding trauma severity was available, 62.7% were from minimal trauma (e.g. fall from standing height), 18.6% were from minor trauma (e.g. fall from multiple steps), and 18.6% were from major trauma (e.g. MVA, assault). In a multivariate model of lower leg and upper arm fractures only (controlling for age, gender, and race), higher BMI showed no association with prior fracture (OR 1.00 per 5 kg/m2, p=0.98, 95% CI 0.78-1.26). Interestingly, subjects with a higher comorbidity index had increased odds of prior fracture (OR 1.23 per 1 point increase, p<0.001, 95% CI 1.12-1.36). Conversely, at all other fracture sites, higher BMI was found to be strongly associated with lower odds of prior fracture (OR 0.57 per 5 kg/m2, p=0.002, 95% CI 0.40-0.81). Conclusion: In a large, super obese population, prior fracture occurred most frequently at the lower leg/ankle, forearm, and upper arm/shoulder and was due to minimal trauma. Higher BMI within the super obese range was not related to prior fracture of the lower leg and upper arm, but was still strongly associated with fewer fractures at other sites.

Field scale recalibration of the sap flow thermal dissipation method in a Mediterranean vineyard

The measurement of transpiration at plant level is a challenging topic in crop water requirements research, e.g. for irrigation scheduling and for the partitioning of plant transpiration and soil evaporation in modelling crop evapotranspiration process. The thermal dissipation method (TD) is widely applied for transpiration estimates of tree species, however some studies reported underestimations of transpiration measurements performed with the TD method when using the equation proposed by Granier. In particular, large underestimation of transpiration flux was reported in vineyards. The underestimation is ascribed to the equation, and its parameters, used to calculate the sapwood flux density from the heat transfer equations in the original Granier’s model and site-specific calibration is required. In this study, using measurements performed in a 2-year field experiment, the TD method was recalibrated at field scale in a vineyard cultivated in a Mediterranean region (Sicily, southern Italy), comparing transpiration flux determined by the TD method with transpiration calculated by the partitioning flux-variance similarity (FVS) method. FVS is a relatively new and innovative method for partitioning water fluxes in transpiration and evaporation through EC data. In this study, transpiration calculated through the equation proposed by Granier was, on average, 26% lower than transpiration determined by FVS. The results show that a new exponential function to calculate the sapwood flux density performed better than the power function in the original equation proposed by Granier. The results also showed that species and site-specific relationships are needed to accurately determine transpiration through the TD method. The ratio T/ET when T is calculated by the recalibrated TD function was equal to 0.77.

Near shore distributions of phytoplankton and bacteria in relation to submarine groundwater discharge-fed fishponds, Kona coast, Hawai‘i, USA

Phytoplankton are important components of coastal marine ecosystems that are strongly influenced by freshwater inputs from land, including submarine groundwater discharge (SGD). Although SGD generates sharp onshore – offshore gradients in physical and chemical conditions at several locations around Hawaii Island little is known about the biotic responses of water column microbes to these conditions. We studied the distributions of phytoplankton and bacteria at two contrasting sites with SGD-fed fishponds, Kiholo and Kaloko Bay, including the full range of salinity extending from the fishponds to the coastal ocean. We addressed the hypotheses that (1) SGD-fed fishponds support a higher biomass and different composition of phytoplankton than the adjacent ocean, and (2) phytoplankton biomass and composition are related to SGD-driven salinity gradients in the coastal ocean. Phytoplankton biomass in fishponds was elevated (10–100-fold) and accompanied by higher average cell size pico- and nano-phytoplankton (2–6 μm) relative to sites outside the fishpond. General additive models (GAMs) showed elevated biomass and average cell size at mid-range salinities and declining biomass at salinity < 20 outside the fishponds. Multivariate RDA showed significant, site-specific relationships between surface phytoplankton biomass (Chl a), cell counts, and environmental parameters. Analysis of surface vs. deep samples from outside the fishponds showed elevated phytoplankton biomass at the surface, except in Kiholo lagoon where phytoplankton was elevated beneath the SGD-driven pycnocline. This study shows structuring of coastal phytoplankton through SGD inputs and suggest that changes in SGD due to coastal development or climate change can impact coastal marine ecosystems through effects on phytoplankton communities.