Do Cross-Latitude and Local Studies Give Similar Predictions of Phytoplankton Responses to Warming? An Analysis of Monitoring Data from 504 Danish Lakes

Cross-latitude studies on lakes have a potential to predict how global warming may cause major changes in phytoplankton biomass and composition, e.g., the development of favourable conditions for cyanobacteria dominance. However, results from these studies may be influenced by biogeographical factors, and the conclusions may, therefore, not hold when considering local response patterns. We used monthly monitoring data from 504 lakes in Denmark—a small and homogeneous geographical region—to establish empirical relationships between key phytoplankton groups and a set of explanatory variables including total phosphorus (TP), total nitrogen (TN), lake mean depth (DEP) and water temperature (TEMP). All variables had strong effects on phytoplankton biomass and composition, but their contributions varied over the seasons, with TEMP being particularly important in June–October. We found dominance of cyanobacteria in terms of biomass and also an increase in dinophytes biomass at higher TEMP, while diatoms and chlorophytes became less important. In May, however, the TEMP effect on total phytoplankton biomass was negative, likely reflecting intensified zooplankton grazing. Our results suggest that biogeographical effects are of minor importance for the response patterns of phytoplankton to temperature and that substantial concentration reductions of TN and TP are needed in eutrophic lakes to counteract the effect of the climate change-induced increase in TEMP.

A New Material-Oriented TES for Land Surface Temperature and SUHI Retrieval in Urban Areas: Case Study over Madrid in the Framework of the Future TRISHNA Mission

The monitoring of the Land Surface Temperature (LST) by remote sensing in urban areas is of great interest to study the Surface Urban Heat Island (SUHI) effect. Thus, it is one of the goals of the future spaceborne mission TRISHNA, which will carry a thermal radiometer onboard with four bands at a 60-m spatial resolution, acquiring daytime and nighttime. In this study, TRISHNA-like data are simulated from Airborne Hyperspectral Scanner (AHS) data over the Madrid urban area at 4-m resolution. To retrieve the LST, the Temperature and Emissivity Separation (TES) algorithm is applied with four spectral bands considering two main original approaches compared with the classical TES algorithm. First, calibration and validation datasets with a large number of artificial materials are considered (called urban-oriented database), contrary to most of the previous studies that do not use a large number of artificial material spectra during the calibration step, thus impacting the LST retrieval over these materials. This approach produces one TES algorithm with one empirical relationship, called 1MMD TES. Second, two empirical relationships are used, one for the artificial materials and the other for the natural ones. These relationships are defined thanks to two calibration datasets (artificial-surface-oriented database and natural-surface-oriented database, respectively), one containing mainly artificial materials and the other mainly natural ones. Finally, in order to use two empirical relationships, a ground cover classification map is given to the TES algorithm to separate artificial pixels from natural ones. This approach produces one material-oriented TES algorithm with two empirical relationships, called 2MMD TES. In order to perform a complete comparison of these two addenda in the TES algorithm and their impact on the LST retrieval, both AHS and TRISHNA spatial resolutions are studied, i.e., 4-m and 60-m resolutions, respectively. Relative to the calibration of the TES algorithm, we conclude that (1) the urban-oriented database is more representative of the urban areas than previous databases from the state-of-the-art, and (2) using two databases (artificial-surface-oriented and natural-surface-oriented) instead of one prevents the overestimation of the LST over natural materials and the underestimation over artificial ones. Thus, for both studied spatial resolutions (AHS and TRISHNA), we find that the 2MMD TES outperforms the 1MMD TES. This difference is especially important for artificial materials, corroborating the above conclusion. Furthermore, the comparison with ground measurements shows that, on 4-m spatial resolution images, the 2MMD TES outperforms both the 1MMD TES and the TES from the state-of-the-art used in this study. Finally, we conclude that the 2MMD TES method, with only four spectral bands, better retrieves the LST over artificial and natural materials and that the future TRISHNA sensor is suited for the monitoring of the LST over urban areas and the SUHI effect.

Effect of channel slope and roughness on hydraulic jump in open channel flow

An experimental study is conducted on hydraulic jump characteristics for understanding the impact of slope in an open channel flume. Hydraulic jump on different channel characteristics (horizontal smooth & rough and sloping smooth & rough) were analysed. The measured characteristics of hydraulic jump with different channel roughness and different slope were compared. The results showed that the sequent depth ratio (y2/y1 ) increases with the increase in Froude number (Fr1 ) for smooth horizontal bed and horizontal rough bed. It was also observed that with an increase in Fr1 , a decrease in y2/y1 in smooth sloping bed condition and decreases for rough sloping bed. New empirical relationships were also developed with the experimental data and results were found similar with the observed hydraulic characteristics data.

30-year record of Himalaya mass-wasting reveals landscape perturbations by extreme events

In mountainous environments, quantifying the drivers of mass-wasting is fundamental for understanding landscape evolution and improving hazard management. Here, we quantify the magnitudes of mass-wasting caused by the Asia Summer Monsoon, extreme rainfall, and earthquakes in the Nepal Himalaya. Using a newly compiled 30-year mass-wasting inventory, we establish empirical relationships between monsoon-triggered mass-wasting and monsoon precipitation, before quantifying how other mass-wasting drivers perturb this relationship. We find that perturbations up to 5 times greater than that expected from the monsoon alone are caused by rainfall events with 5-to-30-year return periods and short-term (< 2 year) earthquake-induced landscape preconditioning. In 2015, the landscape preconditioning is strongly controlled by the topographic signature of the Gorkha earthquake, whereby high Peak Ground Accelerations coincident with high excess topography (rock volume above a landscape threshold angle) amplifies landscape damage. Furthermore, earlier earthquakes in 1934, 1988 and 2011 are not found to influence 2015 mass-wasting.

Feasibility in Estimating the Dry Leaf Mass and Specific Leaf Area of 50 Bamboo Species Based on Nondestructive Measurements

Specific leaf area (SLA) is a good predictor of aboveground net primary productivity. However, the SLA of bamboo species is generally estimated on the basis of destructive measurements rather than the cost-effective and recyclable nondestructive measurements using easily accessible leaf traits such as leaf length (L) and width (W). Considering the strong empirical relationships between leaf area (LA) and leaf structural parameters of bamboo species that were developed by previous studies, this study explores the feasibility of estimating the leaf dry mass (LDM) and SLA of 50 bamboo species using L and W. The results show that the Montgomery equation and its similar forms precisely estimated LA of the 50 bamboo species at both leaf scale (R2 > 0.96 and MAE% < 4.67%) and the canopy scale (R2 > 0.99 and RMSE < 0.09); the LDM of the 50 bamboo species could also be estimated using L and W at both leaf scale (R2 > 0.52 and MAE% < 26.35%) and the canopy scale (R2 > 0.99 and RMSE < 0.003), and the estimated mean SLA of each of the 50 bamboo species had good agreement with the measured values (R2 > 0.99 and RMSE < 1.88) because of the precisely estimated mean LA and mean LDM at the canopy scale, indicating the feasibility of estimating SLA of the 50 bamboo species at the canopy scale based on nondestructive measurements. However, the empirical relationships used for mean SLA estimations are not suitable for SLA estimations at the leaf scale because of the uncertainties in the estimated LDM at the leaf scale.

Thermal conductivity factor for beef of NOR and DFD grades at the subcryoscopic temperatures

Thermal conductivity factor and specific isobaric heat capacity of food products are currently the most important parameters in the development of mathematical models for food freezing and thawing and in improving production technology. There is significant variance among the existing experimental data for the thermal conductivity factor in meat. Most of the modern calculated relationships are based on the nutritional approach, which favorably differs by the ability to calculate the thermophysical characteristics of any food products. However, the calculation error at the subcryoscopic temperatures may be 15% to 20%. The development of superchilling as a way of storing meat requires high accuracy of freezing time calculation, including vacuumpacked boneless meat. In the presented article, the authors investigated hydrogen index, cryoscopic temperature, frozen moisture proportion and thermal conductivity factor for beef M. longissimus dorsi samples of NOR and DFD grades. It was found that DFD beef is characterized by 10% to 12% higher values of thermal conductivity factor in comparison with NOR grade. Using the method of regression analysis, the authors developed empirical relationships for calculating the thermal conductivity factor of meat depending on its temperature and pH level. Unlike cryoscopic temperature and frozen moisture proportion, pH is easy to measure and may be easily used on a conveyor belt for more accurate assessment of meat thermophysical properties. With an increase in pH from 5.3 to 7, an increase in cryoscopic temperature is observed from minus 0.94 °C to minus 0.72 °C. It has been shown that one of the factors for the higher cryoscopic temperature and higher pH level of DFD beef is higher water-holding capacity with less strongly bound moisture.

Georeferencing Oblique Aerial Wildfire Photographs: An Untapped Source of Fire Behaviour Data

In this study, we investigate a novel application of the photogrammetric monoplotting technique for assessing wildfires. We demonstrate the use of the software program WSL Monoplotting Tool (MPT) to georeference operational oblique aerial wildfire photographs taken during airtanker response in the early stages of fire growth. We located the position of the fire front in georeferenced pairs of photos from five fires taken 31–118 min apart, and calculated the head fire spread distance and head fire rate of spread (HROS). Our example photos were taken 0.7 to 4.7 km from fire fronts, with camera angles of incidence from −19 to −50° to image centre. Using high quality images with detailed landscape features, it is possible to identify fire front positions with high precision; in our example data, the mean 3D error was 0.533 m and the maximum 3D error for individual fire runs was less than 3 m. This resulted in a maximum HROS error due to monoplotting of only ~0.5%. We then compared HROS estimates with predictions from the Canadian Fire Behavior Prediction System, with differences mainly attributed to model error or uncertainty in weather and fuel inputs. This method can be used to obtain observations to validate fire spread models or create new empirical relationships where databases of such wildfire photos exist. Our initial work suggests that monophotogrammetry can provide reproducible estimates of fire front position, spread distance and rate of spread with high accuracy, and could potentially be used to characterize other fire features such as flame and smoke plume dimensions and spotting.