Correction to: Keeping pace with forestry: Multi-scale conservation in a changing production forest matrix

Ambio - In the original published article, the sentence “Nevertheless, semi-natural forest remnants continue to be harvested and fragmented (Svensson et al. 2018; Jonsson et al. 2019), and...     

Outsourcing,trade, technology,and greenhouse gas emissions

Environmental Economics and Policy Studies - U.S. output has steadily outpaced the rise in greenhouse gas (GHG) emissions over the past several decades. The decoupling of these two trends...     

Determinants of CO2 emissions in upper middle-income group countries: an empirical investigation

Environmental Science and Pollution Research - This study investigates the kinked exponential growth, degree of association, and causation between economic growth, energy consumption, population,...     

Point Sampling Digital Imagery with ‘Samplepoint’

Measuring percent occurrence of objects from digital images can save time and expense relative to conventional field measurements. However, the accuracy of image analysis had, until now, not reached the level of the best conventional field measurements. Additionally, most image-analysis software programs require advanced user training to successfully analyze images. Here we present a new software program, ‘SamplePoint,’ that provides the user a single-pixel sample point and the ability to view and identify the pixel context. We found SamplePoint to allow accuracy comparable with the most accurate field-methods for ground-cover measurements. Expert use of the program requires minimal training and its ease of use allows rapid measurements from image data. We recommend SamplePoint for calibrating the threshold-detection level of image-analysis software or for making direct measurements of percent occurrence from digital images.     

Can we gain precision by sampling with probabilities proportional to size in surveying recent landscape changes in the Netherlands?

Seventy-two squares of 100 ha were selected by stratified random sampling with probabilities proportional to size (pps) to survey landscape changes in the period 1996–2003. The area of the plots times the urbanization pressure was used as a size measure. The central question of this study is whether the sampling with probabilities proportional to size leads to gain in precision compared to equal probability sampling. On average 1.03 isolated buildings per 100 ha have been built, while 0.90 buildings per 100 ha have been removed, leading to a net change of 0.13 building per 100 ha. The area with unspoiled natural relief has been reduced by 2.3 ha per 100 ha, and the length of linear relicts by 137 m per 100 ha. On average 74 m of linear green elements have been planted per 100 ha, while 106 m have been removed, leading to a net change of −31 m per 100 ha. For the state variables ‘unspoiled natural relief', ‘ linear relicts', ‘removed linear green elements', and ‘new – removed linear green elements' there is a gain in precision due to the pps-sampling. For the remaining state variables there is no gain or even a loss of precision (`new buildings', ‘removed buildings', ‘new – removed buildings', ‘new linear green elements'). Therefore, if many state variables must be monitored or when interest is not only in the change but also in the current totals, we recommend to keep things simple, and to select plots with equal probability.     

Fine-resolution mapping of wildfire fuel types for Canada: Fuzzy logic modeling for an Alberta pilot area

The Canadian Forest Fire Danger Rating System (CFFDRS) is used daily across Canada for evaluating forest fire danger. Fuel-type information is one of the inputs required by the models used in the CFFDRS. In this project, three fuel-type maps with a 25 m resolution were produced for a pilot study area located in Alberta using land cover only; land cover and biomass; and, land cover, biomass and leaf area index data derived from satellite imagery. The relationships between inputs and fuel types were determined mainly by the opinions of forest fire scientists and incorporated into a computer program using fuzzy set methodology. Not all the CFFDRS fuel types could be distinguished using these inputs; three of the coniferous types had to be grouped into one common fuel type. Overall accuracy was between 74 and 83% based on ground-truth comparisons. The most accurate map resulted from land cover and biomass data. Detailed accuracy assessment indicated that the overall accuracy increased up to 86% if ambiguous fuel type identification was considered. No combination of inputs was able to define a fuel type with absolute certainty, which is a reflection of differing expert opinions and the small number of inputs used to produce the maps.     

An Experimental Methodology for Monitoring Contaminant Transport Through Geotechnical Centrifuge Models

In this paper, an attempt has been made to highlight an experimental methodology for monitoring contaminant transport through locally available silty soil and commercially available clay in geotechnical centrifuge models, for different compaction states. Use of multiple depth sensors to determine depth distribution of sodium chloride in the soil column has been detailed. The obtained results have been compared with argentometric method. To validate the centrifuge modelling, modelling of models has been used. The test setup developed can simulate contaminant transport mechanisms through the soil mass, which is approximately 10 m deep, over a period of 600 days. R _e and P _e are found to be N times higher in the centrifuge models. These numbers are found to be several orders less than unity. This indicates that laminar flow prevails and the dominating Cl⁻ transport mechanism in centrifuge is diffusion. The study also highlights the fact that the geotechnical centrifuge modelling can be used as a viable alternative to field scale experimentation.     

Characterization of Benthic Communities and Physical Habitat in the Stanislaus, Tuolumne, and Merced Rivers, California

The primary goal of this study was to characterize physical habitat and benthic communities (macroinvertebrates) in the Stanislaus, Tuolumne and Merced Rivers in California’s San Joaquin Valley in 2003. These rivers have been listed as impaired water bodies (303 (d) list) by the State of California due to the presence of organophosphate (OP) insecticides chlorpyrifos and diazinon, Group A pesticides (i.e., organochlorine pesticides), mercury, or unknown toxicity. Based on 10 instream and riparian physical habitat metrics, total physical habitat scores in the Stanislaus River ranged from 124 to 188 (maximum possible total score is 200). The highest total habitat score was reported at the upstream site. Tuolumne River physical habitat scores ranged from 86 to 167. Various Tuolumne River physical habitat metrics, including total habitat score, increased from downstream to upstream in this river. Merced River physical habitat scores ranged from 121 to 170 with a significant increase in various physical habitat metrics, including total habitat score, reported from downstream to upstream. Channel flow (an instream metric) and bank stability (a riparian metric) were the most important physical habitat metrics influencing the various benthic metrics for all three rivers. Abundance measures of benthic macroinvertebrates (5,100 to 5,400 individuals) were similar among the three rivers in the San Joaquin watershed. Benthic communities in all three rivers were generally dominated by: (1) Baetidae species (mayflies) which are a component of EPT taxa generally considered sensitive to environmental degradation; (2) Chironomidae (midges) which can be either tolerant or sensitive to environmental stressors depending on the species; (3) Ephemerellidae (mayflies) which are considered sensitive to pollution stress; and (4) Naididae (aquatic worms) which are generally considered tolerant to environmental stressors. The presence of 117 taxa in the Stanislaus River, 114 taxa in the Tuolumne River and 96 taxa in the Merced River implies that the benthic communities in these streams are fairly diverse but without a clear definition of benthic community expectations it is unknown if these water bodies are actually impaired.     

Assessing Respiratory Morbidity Through Pollution Status and Meteorological Conditions for Delhi

The study focuses on assessing the status of respiratory morbidity in Delhi over a four years period from 2000–2003. An attempt was made to investigate the role of important pollutants (SO₂, NO₂, SPM and RSPM) and various meteorological factors (temperature minimum & maximum, relative humidity at 0830 and 1730 hrs. and wind speed) in being responsible for respiratory admissions on account of COPD, asthma and emphysema. The study showed that winter months had greater exposure risk as pollutants often get trapped in the lower layers of atmosphere resulting in high concentrations. Statistical analysis revealed that two pollutants have significant positive correlation with the number of COPD cases viz., SPM (r = 0.474; p < 0.01) and RSPM (r = 0.353; p < 0.05), while a meteorological factor temperature (minimum) has a significant negative correlation (r = −0.318; p < 0.05) with COPD. Stepwise multiple regression analysis was performed for COPD as dependent variable and R² value of 0.33 was obtained indicating that SPM and RH(1730) were able to explain 33 percent variability in COPD. The partial correlation of SPM and RH(1730) on COPD was higher than any other combination and therefore they can be regarded as important contributing variables on COPD.     

Spatial and Temporal Variations in Trace Metal Concentrations in the Cockle, Austrovenus Stutchburyi from Otago, New Zealand

This is the first comprehensive study of sources of variation in metal concentrations within the whole tissues of a shallow burrowing, filter-feeding intertidal clam, Austrovenus stutchburyi. Samples were collected from 12 sites in April, August, November and February in 1993–1994 in the vicinity of Otago Harbour and Peninsula, New Zealand. Total tissue trace metal concentrations (μg g⁻¹ dry weight) were measured in individual animals for the essential metals : Mn, Cu, Zn, Ni and the non-essential Cr using trace-metal clean acid-digestion and ICP-OAES techniques. Average metal concentrations were 3–60 μg g⁻¹ for Cu, 40–118 μg g⁻¹ for Zn, 2–12 μg g⁻¹ for Mn, 5–35 μg g⁻¹ for Ni and 1–44 μg g⁻¹ for Cr. These levels decreased with body weight and differed amongst sites except for Cr in February (mid-summer). Highest concentrations occurred at sites close to a city (Dunedin) and within the central harbour region although the Cu, Zn, Ni and Cr concentrations did not correlate with the environmental gradient or season. At one coastal site, samples of both the blue mussel Mytilus galloprovincialis and cockles gave similar trends in trace metal levels. These results suggest that the cockle could be a useful trace metal biomonitor within NZ estuaries.