Uncertainty propagation in vegetation distribution models based on ensemble classifiers

Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the uncertainty on spatial interpolation of environmental variables and the uncertainty on species clustering into vegetation types, is quantified based on sequential Gaussian simulation and pseudo-randomization tests, respectively. An empirical assessment of the uncertainty propagation to the distribution modelling results indicated a gradual decrease in performance with increasing input uncertainty. The test set error ranged from 30.83% to 52.63% and from 30.83% to 83.62%, when the uncertainty ranges on spatial interpolation and on vegetation clustering, respectively, were fully covered. Shannon’s entropy, which is proposed as a measure for uncertainty of ensemble predictions, revealed a similar increasing trend in prediction uncertainty. The implications of these results in an empirical distribution modelling framework are further discussed with respect to monitoring setup, spatial interpolation and species clustering.     

Quantification of copepod gut content by differential length amplification quantitative PCR (dla-qPCR)

Quantification of feeding rates and selectivity of zooplankton is vital for understanding the mechanisms structuring marine ecosystems. However, methodological limitations have made many of these studies difficult. Recently, molecular based methods have demonstrated that DNA from prey species can be used to identify zooplankton gut contents, and further, quantitative gut content estimates by quantitative PCR (qPCR) assays targeted to the 18S rRNA gene have been used to estimate feeding rates in appendicularians and copepods. However, while standard single primer based qPCR assays were quantitative for the filter feeding appendicularian Oikopleura dioica, feeding rates were consistently underestimated in the copepod Calanus finmarchicus. In this study, we test the hypothesis that prey DNA is rapidly digested after ingestion by copepods and describe a qPCR-based assay, differential length amplification qPCR (dla-qPCR), to account for DNA digestion. The assay utilizes multiple primer sets that amplify different sized fragments of the prey 18S rRNA gene and, based on the differential amplification of these fragments, the degree of digestion is estimated and corrected for. Application of this approach to C. finmarchicus fed Rhodomonas marina significantly improved quantitative feeding estimates compared to standard qPCR. The development of dla-qPCR represents a significant advancement towards a quantitative method for assessing in situ copepod feeding rates without involving cultivation-based manipulation.     

The case for carbon leakage and border adjustments: where do economists stand?

Environmental Economics and Policy Studies - While the EU is working toward the implementation of the world’s first Carbon Border Adjustment (CBA) Mechanism, a gap remains between the ways in...     

Characterization of phosphate rock and phosphogypsum from Gabes phosphate fertilizer factories (SE Tunisia): high mining potential and implications for environmental protection

Environmental Science and Pollution Research - Since the establishment of the coastal industrial complex in Gabes city (Gulf of Gabes, SE Tunisia), hundred million tons of untreated phosphogypsum...     

Evaluation of airborne particulate matter and metals data in personal,indoor and outdoor environments using ED-XRF and ICP-MS and co-located duplicate samples

Factors and sources affecting measurement uncertainty associated with monitoring metals in airborne particulate matter (PM) were investigated as part of the Windsor, Ontario Exposure Assessment Study (WOEAS). The assessment was made using co-located duplicate samples and a comparison of two analytical approaches: ED-XRF and ICP-MS. Sampling variability was estimated using relative percent difference (RPD) of co-located duplicate samples. The comparison of ICP-MS and ED-XRF results yields very good correlations (R² ≥ 0.7) for elements present at concentrations that pass both ICP-MS and ED-XRF detection limits (e.g. Fe, Mn, Zn, Pb and Cu). PM concentration ranges (median, sample number) of 24-h indoor PM₁₀ and personal PM₁₀ filters, and outdoor PM_2.5 filters were determined to be 2.2–40.7 (11.0, n = 48) μg m^?3, 8.0–48.3 (11.9, n = 48) μg m^?3, and 17.1–42.3 (21.6, n = 18) μg m^?3, respectively. The gravimetric analytical results reveal that the variations in PM mass measurements for same-day sampling are insignificant compared to temporal or spatial variations: 92%, 100% and 96% of indoor, outdoor and personal duplicate samples, respectively, pass the quality criteria (RPD ≤ 20%). Uncertainties associated with ED-XRF elemental measurements of S, Ca, Mn, Fe and Zn for 24-h filter samples are low: 78%–100% of the duplicate samples passed the quality criteria. In the case of 24-h filter samples using ICP-MS, more elements passed the quality criteria due to the lower detection limits. These were: Li, Na, K, Ca, Si, Al, V, Fe, Mn, Co, Cu, Mo, Ag, Zn, Pb, As, Mg, Sb, Sn, Sr, Th, Ti, Tl, and U. Low air concentrations of metals (near or below instrumental detection limits) and/or inadvertent introduction of metal contamination are the main causes for excluding elements based on the pass/fail criteria. Uncertainty associated with elemental measurements must be assessed on an element-by-element basis.     

A Global Analysis of Protected Area Management Effectiveness

We compiled details of over 8000 assessments of protected area management effectiveness across the world and developed a method for analyzing results across diverse assessment methodologies and indicators. Data was compiled and analyzed for over 4000 of these sites. Management of these protected areas varied from weak to effective, with about 40% showing major deficiencies. About 14% of the surveyed areas showed significant deficiencies across many management effectiveness indicators and hence lacked basic requirements to operate effectively. Strongest management factors recorded on average related to establishment of protected areas (legal establishment, design, legislation and boundary marking) and to effectiveness of governance; while the weakest aspects of management included community benefit programs, resourcing (funding reliability and adequacy, staff numbers and facility and equipment maintenance) and management effectiveness evaluation. Estimations of management outcomes, including both environmental values conservation and impact on communities, were positive. We conclude that in spite of inadequate funding and management process, there are indications that protected areas are contributing to biodiversity conservation and community well-being.     

Integrating Environmental and Socio-Economic Indicators of a Linked Catchment–Coastal System Using Variable Environmental Intensity

Can we develop land use policy that balances the conflicting views of stakeholders in a catchment while moving toward long term sustainability? Adaptive management provides a strategy for this whereby measures of catchment performance are compared against performance goals in order to progressively improve policy. However, the feedback loop of adaptive management is often slow and irreversible impacts may result before policy has been adapted. In contrast, integrated modelling of future land use policy provides rapid feedback and potentially improves the chance of avoiding unwanted collapse events. Replacing measures of catchment performance with modelled catchment performance has usually required the dynamic linking of many models, both biophysical and socio-economic—and this requires much effort in software development. As an alternative, we propose the use of variable environmental intensity (defined as the ratio of environmental impact over economic output) in a loose coupling of models to provide a sufficient level of integration while avoiding significant effort required for software development. This model construct was applied to the Motueka Catchment of New Zealand where several biophysical (riverine water quantity, sediment, E. coli faecal bacteria, trout numbers, nitrogen transport, marine productivity) models, a socio-economic (gross output, gross margin, job numbers) model, and an agent-based model were linked. An extreme set of land use scenarios (historic, present, and intensive) were applied to this modelling framework. Results suggest that the catchment is presently in a near optimal land use configuration that is unlikely to benefit from further intensification. This would quickly put stress on water quantity (at low flow) and water quality (E. coli). To date, this model evaluation is based on a theoretical test that explores the logical implications of intensification at an unlikely extreme in order to assess the implications of likely growth trajectories from present use. While this has largely been a desktop exercise, it would also be possible to use this framework to model and explore the biophysical and economic impacts of individual or collective catchment visions. We are currently investigating the use of the model in this type of application.     

Evaluating the capabilities of Aerosol-to-Liquid Particle Extraction System (ALPXS)/ICP-MS for monitoring trace metals in indoor air

This study investigates the application of the Aerosol-to-Liquid Particle Extraction System (ALPXS), which uses wet electrostatic precipitation to collect airborne particles, for multi-element indoor stationary monitoring. Optimum conditions are determined for capturing airborne particles for metal determination by inductively coupled plasma–mass spectrometry (ICP-MS), for measuring field blanks, and for calculating limits of detection (LOD) and quantification (LOQ). Due to the relatively high flow rate (300 L min^?1), a sampling duration of 1 hr to 2 hr was adequate to capture airborne particle-bound metals under the investigated experimental conditions. The performance of the ALPXS during a building renovation demonstrated signal-to-noise ratios appropriate for sampling airborne particles in environments with elevated metal concentrations, such as workplace settings. The ALPXS shows promise as a research tool for providing useful information on short-term variations (transient signals) and for trapping particles into aqueous solutions where needed for subsequent characterization. As the ALPXS does not provide size-specific samples, and its efficiency at different flow rates has yet to be quantified, the ALPXS would not replace standard filter-based protocols accepted for regulatory applications (e.g., exposure measurements), but rather would provide additional information if used in conjunction with filter based methods.

ImplicationsThis study investigates the capability of the Aerosol-to-Liquid Particle Extraction System (ALPXS) for stationary sampling of airborne metals in indoor workplace environments, with subsequent analysis by ICP-MS. The high flow rate (300 L/min) permits a short sampling duration (< 2 hr). Results indicated that the ALPXS was capable of monitoring short-term changes in metal emissions during a renovation activity. This portable instrument may prove to be advantageous in occupational settings as a qualitative indicator of elevated concentrations of airborne metals at short time scales.