Model simulations of dissolved oxygen characteristics of Minnesota lakes: Past and future

A deterministic, one-dimensional, unsteady numerical model has been developed, tested, and applied to simulate mean daily dissolved oxygen (DO) characteristics in 27 lake classes in the state of Minnesota. Reaeration and photosynthesis are the oxygen sources, while respiration, sedimentary, and biochemical water column oxygen demand are the sinks of oxygen in the model. The lake classes are differentiated by surface area (A _s), maximum depth (H _max), and trophic status expressed as Secchi depth (Z _s). Because lake stratification is most important to lake oxygen dynamics, simulated DO characteristics are plotted in terms of a stratification parameterA _s/H _max ^0.25 and Secchi depthZ _s. Simulations provide DO profiles on a daily time scale. Specific DO characteristics of ecological and environmental interest are epilimnetic DO, hypolimnetic DO, DO gradient from surface to bottom, and DO minima and maxima. Specific results are as follows: Simulated mean daily and weekly DO values in the epilimnion of all lakes for both past and future climate scenarios are near saturation over the summer season. Hypolimnetic DO values depend strongly on lake morphometry, trophic status, and time throughout the summer season. Future climate conditions are specified as the historical records from 1955 to 1979, adjusted (monthly) by the 2 × CO₂ GISS model output to account for doubling of atmospheric CO₂. With this climate change, weekly averaged epilimnetic DO is projected to drop by less than 2 mg/liter, and will remain above 7 mg/liter throughout the open water season. The hypolimnetic DO reductions after climate change are on the order of 2–8 mg/liter. Periods of anoxia are longer by as much as 80 days. Those changes would alter water quality dynamics in lakes and have a profound effect on lake ecosystems including indigenous fishes. The results presented are useful for evaluating environmental management options.     

STREAM TEMPERATURE ESTIMATION FROM AIR TEMPERATURE1

ABSTRACT: Air temperatures are sometimes used as substitutes for stream temperatures. To examine the errors associated with this procedure, linear relationships between stream temperatures, T, and air temperatures, T_a, recorded for 11 streams in the central U.S. (Mississippi River basin) were analyzed. Weather stations were an average 42 miles (range 0 to 144 miles) from the rivers. The general equations, T_w= 5.0 + 0.75 T_a and T_w= 2.9 + 0.86 T_a with temperatures in °C, were derived for daily and weekly water temperatures, respectively, for the 11 streams studied. The simulations had a standard deviation between measurements and predictions of 2.7°C (daily) and 2.1°C (weekly). Equations derived for each specific stream individually gave lower standard deviations, i.e., 2.1°C and 1.4°C, respectively. Small, shallow streams had smaller deviations than large, deep rivers. The measured water temperatures follow the air temperatures closely with some time lag. time lags ranged from hours to days, increasing with stream depth. Taking into account these time lags improved the daily temperature predictions slightly. Periods of ice cover were excluded from the analysis.     

Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.     

The Effects of Long Time Conservation of Heavily Grazed Shrubland: A Case Study in the Northern Negev,Israel

One of the major reasons for desertification is unrestricted grazing leading to vegetation depletion, soil erosion and degradation, phenomena often considered irreversible in the short term. Here, we compare soil and biological parameters of degraded and conserved, recently rehabilitated arid shrubland in the Northern Negev, Israel. The study area was restored by conservation efforts including a strictly controlled grazing regime initiated in 1992. The visually recognizable improvement in the ecology of the restored shrubland is reflected in significant improvement in all examined biotic (herbaceous biomass, shrub patch density, and insect activity), and soil parameters (nutrients, organic matter content, moisture, and water infiltration). The difference is created predominantly by restoration of large biological patches composed of shrubs and other perennial plants often associated with ant or termite nests, where the most significant increases in productivity and soil quality were observed. In the conserved shrubland such patches covered 35 or 25 % of the area (in a normal and a drought year, respectively). In the degraded shrubland 5 % or less of the area was occupied by such patches that were much smaller and of lower biological complexity. With respect to plant biodiversity, six plant species were found only—and 18 others became significantly more common—in the rehabilitated area. The results of this article indicate that functional arid drylands can be restored within <16 years relying on strict conservation management with reduced grazing intensity.     

Ethological farm programs and the “market” for animal welfare

Ethological farm programs as they exist in Switzerland are compared with environmental farm programs in respect of demand and supply. Because animal welfare is not a public good but rather a relation that causes psychological externalities, the demand for animal welfare has a different standing in economic theory than the demand for a clean environment. The supply of animal welfare by farmers, however, largely follows the patterns known from the delivery of environmental goods. Farm size, age and education, and also family size and capital intensity are influencing variables. The paper concludes that the design of ethological farm programs should be based on broad public discussions as described by deliberation theorists rather than willingness-to-pay studies.