Abhishek Chaudhary

Quantifying Land Use Impacts on Biodiversity: Combining Species–Area Models and Vulnerability Indicators

Habitat degradation and subsequent biodiversity damage often take place far from the place of consumption because of globalization and the increasing level of international trade. Informing consumers and policy makers about the biodiversity impacts hidden in the life cycle of imported products is an important step toward achieving sustainable consumption patterns. Spatially explicit methods are needed in life cycle assessment to accurately quantify biodiversity impacts of products and processes. We use the Countryside species-area relationship (SAR) to quantify regional species loss due to land occupation and transformation for five taxa and six land use types in 804 terrestrial ecoregions. Further, we calculate vulnerability scores for each ecoregion based on the fraction of each species geographic range (endemic richness) hosted by the ecoregion and the IUCN assigned threat level of each species. Vulnerability scores are multiplied with SAR-predicted regional species loss to estimate potential global extinctions per unit of land use. As a case study, we assess the land use biodiversity impacts of 1 kg of bioethanol produced using six different feed stocks in different parts of the world. Results show that the regions with highest biodiversity impacts differed markedly when the vulnerability of species was included.

Impact of Forest Management on Species Richness: Global Meta-Analysis and Economic Trade-Offs

Forests managed for timber have an important role to play in conserving global biodiversity. We evaluated the most common timber production systems worldwide in terms of their impact on local species richness by conducting a categorical meta-analysis. We reviewed 287 published studies containing 1008 comparisons of species richness in managed and unmanaged forests and derived management, taxon, and continent specific effect sizes. We show that in terms of local species richness loss, forest management types can be ranked, from best to worse, as follows: selection and retention systems, reduced impact logging, conventional selective logging, clear-cutting, agroforestry, timber plantations, fuelwood plantations. Next, we calculated the economic profitability in terms of the net present value of timber harvesting from 10 hypothetical wood-producing Forest Management Units (FMU) from around the globe. The ranking of management types is altered when the species loss per unit profit generated from the FMU is considered. This is due to differences in yield, timber species prices, rotation cycle length and production costs. We thus conclude that it would be erroneous to dismiss or prioritize timber production regimes, based solely on their ranking of alpha diversity impacts.

Harmonizing the Assessment of Biodiversity Effects from Land and Water Use within LCA

Addressing biodiversity impacts in life cycle assessment (LCA) has recently been significantly improved. Advances include the consideration of several taxa, consideration of vulnerability of species and ecosystems, global coverage and spatial differentiation. To allow a comparison of biodiversity impacts of different stressors (e.g., land and water use), consistent approaches for assessing and aggregating biodiversity impacts across taxa are needed. We propose four different options for aggregating impacts across taxa and stressors: equal weight for species, equal weight for taxa and two options with special consideration of species vulnerability. We apply the aggregation options to a case study of coffee, tea and sugarcane production in Kenya for the production of 1 kg of crop. The ranking between stressors (land vs water use) within each crop and also of the overall impact between crops (coffee>sugarcane>tea) remained the same when applying the different aggregation options. Inclusion of the vulnerability of species had significant influence on the magnitude of results, and potentially also on the spatial distribution of impacts, and should be considered.

Including Indoor Offgassed Emissions in the Life Cycle Inventories of Wood Products

Volatile organic compounds (VOCs) that negatively affect human health are emitted from wood products used indoors. However, the existing life cycle inventories of these products only document the emissions occurring during production and disposal phases. Consequently, the life cycle assessment (LCA) of indoor wooden products conducted using these inventories neglect the use-phase impacts from exposure to offgassed VOCs and therefore underestimate the products total environmental impact. This study demonstrates a methodology to calculate the use phase inventory and the corresponding human health impacts resulting from indoor use of any VOC emitting product. For the five most commonly used types of boards used in indoor wood products, the mass of each VOC emitted into the indoor compartment over their service life was calculated by statistically analyzing data from 50 published chamber testing studies. Uncertainty was assessed using Monte Carlo simulations. The calculated inventory data were used in a case study to calculate and compare the health impacts of five different wooden floorings made of above materials. The results show that the use-phase human-toxicity impacts are an order of magnitude higher than those occurring during the rest of the floorings life cycle. The factors influencing the offgassing of VOCs from wood products and measures to reduce exposure are discussed.

Spatially Explicit Analysis of Biodiversity Loss Due to Global Agriculture, Pasture and Forest Land Use from a Producer and Consumer Perspective

Anthropogenic land use to produce commodities for human consumption is the major driver of global biodiversity loss. Synergistic collaboration between producers and consumers in needed to halt this trend. In this study, we calculate species loss on 5 min × 5 min grid level and per country due to global agriculture, pasture and forestry by combining high-resolution land use data with countryside species area relationship for mammals, birds, amphibians, and reptiles. Results show that pasture was the primary driver of biodiversity loss in Madagascar, China and Brazil, while forest land use contributed the most to species loss in DR Congo and Indonesia. Combined with the yield data, we quantified the biodiversity impacts of 1 m(3) of roundwood produced in 139 countries, concluding that tropical countries with low timber yield and a large presence of vulnerable species suffer the highest impact. We also calculated impacts per kg for 160 crops grown in different countries and linked it with FAO food trade data to assess the biodiversity impacts embodied in Swiss food imports. We found that more than 95% of Swiss consumption impacts rest abroad with cocoa, coffee and palm oil imports being responsible for majority of damage.

Multi-indicator sustainability assessment of global food systems

Food systems are at the heart of at least 12 of the 17 Sustainable Development Goals (SDGs). The wide scope of the SDGs call for holistic approaches that integrate previously “siloed” food sustainability assessments. Here we present a first global-scale analysis quantifying the status of national food system performance of 156 countries, employing 25 sustainability indicators across 7 domains as follows: nutrition, environment, food affordability and availability, sociocultural well-being, resilience, food safety, and waste. The results show that different countries have widely varying patterns of performance with unique priorities for improvement. High-income nations score well on most indicators, but poorly on environmental, food waste, and health-sensitive nutrient-intake indicators. Transitioning from animal foods toward plant-based foods would improve indicator scores for most countries. Our nation-specific quantitative results can help policy-makers to set improvement targets on specific areas and adopt new practices, while keeping track of the other aspects of sustainability.The development of sustainable food systems requires an understanding of potential trade-off between various objectives. Here, Chaudhary et al. examine how different nations score on food system performance across several domains, including environment, nutrition, and sociocultural wellbeing.

Bayesian Framework for Water Quality Model Uncertainty Estimation and Risk Management

AbstractA formal Bayesian methodology is presented for integrated model calibration and risk-based water quality management using Bayesian Monte Carlo simulation and maximum likelihood estimation (BMCML). The primary focus is on lucid integration of model calibration with risk-based water quality management and total maximum daily load (TMDL) estimation under conditions of uncertainty. The sources of uncertainty considered in the analysis are modeling errors, observational data errors and fuzziness of the water quality standard. The difference between observed data or transformation thereof and corresponding model response is assumed to follow first-order Markov process, a specific case of which is statistically independent Gaussian errors. The BMCML method starts with sampling parameter sets from prior probability distributions of the model parameters and uses Bayes theorem and the maximum likelihood technique to estimate the triplicate (variance of residual errors, bias and autocorrelation coefficient o...

Bayesian Monte Carlo and maximum likelihood approach for uncertainty estimation and risk management: Application to lake oxygen recovery model

Model uncertainty estimation and risk assessment is essential to environmental management and informed decision making on pollution mitigation strategies. In this study, we apply a probabilistic methodology, which combines Bayesian Monte Carlo simulation and Maximum Likelihood estimation (BMCML) to calibrate a lake oxygen recovery model. We first derive an analytical solution of the differential equation governing lake-averaged oxygen dynamics as a function of time-variable wind speed. Statistical inferences on model parameters and predictive uncertainty are then drawn by Bayesian conditioning of the analytical solution on observed daily wind speed and oxygen concentration data obtained from an earlier study during two recovery periods on a eutrophic lake in upper state New York. The model is calibrated using oxygen recovery data for one year and statistical inferences were validated using recovery data for another year. Compared with essentially two-step, regression and optimization approach, the BMCML results are more comprehensive and performed relatively better in predicting the observed temporal dissolved oxygen levels (DO) in the lake. BMCML also produced comparable calibration and validation results with those obtained using popular Markov Chain Monte Carlo technique (MCMC) and is computationally simpler and easier to implement than the MCMC. Next, using the calibrated model, we derive an optimal relationship between liquid film-transfer coefficient for oxygen and wind speed and associated 95% confidence band, which are shown to be consistent with reported measured values at five different lakes. Finally, we illustrate the robustness of the BMCML to solve risk-based water quality management problems, showing that neglecting cross-correlations between parameters could lead to improper required BOD load reduction to achieve the compliance criteria of 5xa0mg/L.

Evolutionary isolation and phylogenetic diversity loss under random extinction events

The extinction of species at the present leads to the loss of phylogenetic diversity (PD) from the evolutionary tree in which these species lie. Prior to extinction, the total PD present can be divided up among the species in various ways using measures of evolutionary isolation (such as fair proportion and equal splits). However, the loss of PD when certain combinations of species become extinct can be either larger or smaller than the cumulative loss of the isolation values associated with the extinct species. In this paper, we show that for trees generated under neutral evolutionary models, the loss of PD under a null model of random extinction at the present can be predicted from the loss of the cumulative isolation values, by applying a non-linear transformation that is independent of the tree. Moreover, the error in the prediction provably converges to zero as the size of the tree grows, with simulations showing good agreement even for moderate sized trees (n=64).

Linking national wood consumption with global biodiversity and ecosystem service losses

Identifying the global hotspots of forestry driven species, ecosystem services losses and informing the consuming nations of their environmental footprint domestically and abroad is essential to design demand side interventions and induce sustainable production methods. Here we first use countryside species area relationship model to project species extinctions of four vertebrate taxa (mammals, birds, amphibians and reptiles) due to forest land use in 174 countries. We combine the projected extinctions with a global database on the monetary value of ecosystem services provided by different biomes and with bilateral trade data of wood products to calculate species extinctions and ecosystem services losses inflicted by national wood consumption and international wood trade. Results show that globally a total of 485 species are projected to go extinct due to current forest land use. About 32% of this projected loss can be attributed to land use devoted for export production. However, under the counterfactual scenario with the same consumption levels but no international trade of wood products, an additional 334 species are projected to go extinct. Globally, we find that losses of ecosystem services worth