Scientific opinion on the renewal of the authorisation of Smoke Concentrate 809045 (SF-003) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Smoke Concentrate 809045 (SF-003), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. Product Smoke Concentrate 809045 is obtained by pyrolysis of beech wood. The Panel concluded that the compositional data provided on the Primary Product are adequate. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.1 to 1.5 mg/kg body weight (bw) per day at the mean and from 0.2 to 5.2 mg/kg bw per day at the 95th percentile. The Panel concluded that eleven components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one and benzene-1,2-diol, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for these two components are above the threshold of toxicological concern (TTC) of 0.0025 µg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Scientific opinion on the renewal of the authorisation of Zesti Smoke Code 10 (SF-002) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Zesti Smoke Code 10 (SF-002), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. Zesti Smoke Code 10 is obtained by pyrolysis of hickory and oak woods. Given the limitations of the quantification approach employed by the applicant, the Panel could not judge whether the applied methods meet the legal quality criterion that at least 80% of the volatile fraction shall be identified and quantified. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.02 to 4.6 mg/kg body weight (bw) per day at the mean and from no dietary exposure to 13.0 mg/kg bw per day at the 95th percentile. The Panel concluded that four components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one and benzene-1,2-diol, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for these two components are above the threshold of toxicological concern (TTC) of 0.0025 µg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Scientific opinion on the renewal of the authorisation of Scansmoke SEF7525 (SF-004) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Scansmoke SEF7525 (SF-004), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. Scansmoke SEF7525 is obtained from a tar produced from a mixture of red oak, white oak, maple, beech and hickory. Based on the compositional data, the Panel noted that the identified and quantified proportion of the solvent-free fraction amounts to 32.6 weight (wt)%, thus the applied method does not meet the legal quality criterion that at least 50% of the solvent-free fraction shall be identified and quantified. At the maximum proposed use levels, dietary exposure estimates calculated with Food Additive Intake Model (FAIM) ranged from 0.6 to 3.8 mg/kg body weight (bw) per day at the mean and from 1.1 to 10.1 mg/kg bw per day at the 95th percentile. Based on the available information on genotoxicity on 44 identified components, the Panel concluded that two substances in the Primary Product, styrene and benzofuran, raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. Considering that the exposure estimates for styrene and benzofuran are above the threshold of toxicological concern (TTC) value of 0.0025 kg/kg bw per day for DNA-reactive mutagens and/or carcinogens and since further data are needed to clarify their potential genotoxicity, the Panel concluded that the potential safety concern for genotoxicity of the Primary Product cannot be ruled out.

Scientific opinion on the renewal of the authorisation of Fumokomp (SF-009) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Fumokomp (SF-009), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003 (in the renewal application the Primary Product is reported as 'Fumokomp Conc.'). This opinion refers to an assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. Fumokomp Conc. is produced by pyrolysis of beech and hornbeam woods. Gas chromatography-mass spectrometry (GC-MS) was applied for both identification and quantification of the volatile constituents of the Primary Product. Given the limitations of the method, the Panel cannot judge with confidence whether the applied method meets the legal quality criterion that at least 80% of the volatile fraction shall be identified and quantified. Moreover, the Panel concluded that the absence of furan-2(5H)-one from the Primary Product was not convincingly demonstrated. At the maximum proposed use levels, dietary exposure estimates calculated with FAIM ranged from 0.04 to 0.9 mg/kg body weight (bw) per day at the mean and from 0.1 to 1.5 mg/kg bw per day at the 95th percentile. The information available on the 32 identified components of the Primary Product, although limited, did not indicate a concern for genotoxicity for any of these substances. However, whole mixture testing in an in vitro mouse lymphoma assay gave positive results which would require an adequate in vivo follow-up study. In addition, the potential for aneugenicity of the Primary Product has not been adequately investigated. Accordingly, the potential safety concern for genotoxicity of the Primary Product cannot be ruled out.

Scientific opinion on the renewal of the authorisation of SmokEz C-10 (SF-005) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product SmoKEz C-10 (SF-005), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. SmoKEz C-10 is obtained by pyrolysis of maple, oak, hickory, ash, birch, beech and cherry woods. Given the limitations of the quantification approach employed by the applicant, the Panel could not judge whether the applied methods meet the legal quality criterion that at least 80% of the volatile fraction shall be identified and quantified. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.01 to 5.1 mg/kg body weight (bw) per day at the mean and from no dietary exposure to 18.1 mg/kg bw per day at the 95th percentile. The Panel concluded that five components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one and benzene-1,2-diol, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for these two components are above the threshold of toxicological concern (TTC) of 0.0025 µg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Scientific opinion on the renewal of the authorisation of proFagus Smoke R714 (SF-001) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product proFagus Smoke R714 (SF-001), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. ProFagus Smoke R714 is obtained by pyrolysis of beech and oak woods as main source materials. Based on the compositional data, the Panel noted that the identified and quantified proportion of the solvent-free fraction amounts to 39 weight (wt)%, thus the applied method does not meet the legal quality criterion that at least 50% of the solvent-free fraction shall be identified and quantified. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.7 to 10.9 mg/kg body weight (bw) per day at the mean and from 2.2 to 42.5 mg/kg bw per day at the 95th percentile. The Panel concluded that three components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for this component are above the threshold of toxicological concern (TTC) of 0.0025 µg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Scientific opinion on the renewal of the authorisation of SmokEz Enviro-23 (SF-006) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product SmokEz Enviro-23 (SF-006), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. SmokEz Enviro-23 is obtained by pyrolysis of oak, maple, hickory, ash, birch, beech and cherry woods. Given the limitations of the quantification approach employed by the applicant, the Panel could not judge whether the applied methods meet the legal quality criterion that at least 80% of the volatile fraction shall be identified and quantified. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.01 to 3.2 mg/kg body weight (bw) per day at the mean and from no dietary exposure to 9.5 mg/kg bw per day at the 95th percentile. The Panel concluded that four components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one and benzene-1,2-diol, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for these two components are above the threshold of toxicological concern (TTC) of 0.0025 µg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Scientific opinion on the renewal of the authorisation of proFagus Smoke R709 (SF-008) as a smoke flavouring Primary Product.

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product proFagus Smoke R709 (SF-008), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. ProFagus Smoke R709 is obtained by pyrolysis of beech and oak wood as main source materials. The panel concluded that the compositional data provided on the Primary Product are adequate. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.8 to 12.2 mg/kg body weight (bw) per day at the mean and from 2.3 to 51.4 mg/kg bw per day at the 95th percentile. The Panel concluded that three components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for this component are above the TTC of 0.0025 µg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the panel concluded that the Primary Product raises concern with respect to genotoxicity.

Transcriptional Responses as Biomarkers of General Toxicity: A Systematic Review and Meta-analysis on Metal-Exposed Bivalves.

Through a systematic review and a series of meta-analyses, we evaluated the general responsiveness of putative transcriptional biomarkers of general toxicity and chemical stress. We targeted metal exposures performed on bivalves under controlled laboratory conditions and selected six transcripts associated with general toxicity for evaluation: catalase, glutathione-S-transferase, heat shock proteins 70 and 90, metallothionein, and superoxide dismutase. Transcriptional responses (n = 396) were extracted from published scientific articles (k = 22) and converted to log response ratios (lnRRs). By estimating toxic units, we normalized different metal exposures to a common scale, as a proxy of concentration. Using Bayesian hierarchical random effect models, we then tested the effects of metal exposure on lnRR, both for metal exposure in general and in meta-regressions using toxic unit and exposure time as independent variables. Corresponding analyses were also repeated with transcript and tissue as additional moderators. Observed patterns were similar for general and for transcript- and tissue-specific responses. The expected overall response to arbitrary metal exposure was an lnRR of 0.50, corresponding to a 65% increase relative to a nonexposed control. However, when accounting for publication bias, the estimated "true" response showed no such effect. Furthermore, expected response magnitude increased slightly with exposure time, but there was little support for general monotonic concentration dependence with regard to toxic unit. Altogether, the present study reveals potential limitations that need consideration prior to applying the selected transcripts as biomarkers in environmental risk assessment. Environ Toxicol Chem 2023;42:628-641. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

A model of wild bee populations accounting for spatial heterogeneity and climate-induced temporal variability of food resources at the landscape level.

The viability of wild bee populations and the pollination services that they provide are driven by the availability of food resources during their activity period and within the surroundings of their nesting sites. Changes in climate and land use influence the availability of these resources and are major threats to declining bee populations. Because wild bees may be vulnerable to interactions between these threats, spatially explicit models of population dynamics that capture how bee populations jointly respond to land use at a landscape scale and weather are needed. Here, we developed a spatially and temporally explicit theoretical model of wild bee populations aiming for a middle ground between the existing mapping of visitation rates using foraging equations and more refined agent-based modeling. The model is developed for Bombus sp. and captures within-season colony dynamics. The model describes mechanistically foraging at the colony level and temporal population dynamics for an average colony at the landscape level. Stages in population dynamics are temperature-dependent triggered by a theoretical generalized seasonal progression, which can be informed by growing degree days. The purpose of the LandscapePhenoBee model is to evaluate the impact of system changes and within-season variability in resources on bee population sizes and crop visitation rates. In a simulation study, we used the model to evaluate the impact of the shortage of food resources in the landscape arising from extreme drought events in different types of landscapes (ranging from different proportions of semi-natural habitats and early and late flowering crops) on bumblebee populations.

A robust Bayesian bias-adjusted random effects model for consideration of uncertainty about bias terms in evidence synthesis.

Meta-analysis is a statistical method used in evidence synthesis for combining, analyzing and summarizing studies that have the same target endpoint and aims to derive a pooled quantitative estimate using fixed and random effects models or network models. Differences among included studies depend on variations in target populations (ie, heterogeneity) and variations in study quality due to study design and execution (ie, bias). The risk of bias is usually assessed qualitatively using critical appraisal, and quantitative bias analysis can be used to evaluate the influence of bias on the quantity of interest. We propose a way to consider ignorance or ambiguity in how to quantify bias terms in a bias analysis by characterizing bias with imprecision (as bounds on probability) and use robust Bayesian analysis to estimate the overall effect. Robust Bayesian analysis is here seen as Bayesian updating performed over a set of coherent probability distributions, where the set emerges from a set of bias terms. We show how the set of bias terms can be specified based on judgments on the relative magnitude of biases (ie, low, unclear, and high risk of bias) in one or several domains of the Cochrane's risk of bias table. For illustration, we apply a robust Bayesian bias-adjusted random effects model to an already published meta-analysis on the effect of Rituximab for rheumatoid arthritis from the Cochrane Database of Systematic Reviews.

A suggestion for the quantification of precise and bounded probability to quantify epistemic uncertainty in scientific assessments.

An honest communication of uncertainty about quantities of interest enhances transparency in scientific assessments. To support this communication, risk assessors should choose appropriate ways to evaluate and characterize epistemic uncertainty. A full treatment of uncertainty requires methods that distinguish aleatory from epistemic uncertainty. Quantitative expressions for epistemic uncertainty are advantageous in scientific assessments because they are nonambiguous and enable individual uncertainties to be characterized and combined in a systematic way. Since 2019, the European Food Safety Authority (EFSA) recommends assessors to express epistemic uncertainty in conclusions of scientific assessments quantitatively by subjective probability. A subjective probability can be used to represent an expert judgment, which may or may not be updated using Bayes's rule to integrate evidence available for the assessment and could be either precise or approximate. Approximate (or bounded) probabilities may be enough for decision making and allow experts to reach agreement on certainty when they struggle to specify precise subjective probabilities. The difference between the lower and upper bound on a subjective probability can also be used to reflect someone's strength of knowledge. In this article, we demonstrate how to quantify uncertainty by bounded probability, and explicitly distinguish between epistemic and aleatory uncertainty, by means of robust Bayesian analysis, including standard Bayesian analysis through precise probability as a special case. For illustration, the two analyses are applied to an intake assessment.

Bayesian Network Applications for Sustainable Holistic Water Resources Management: Modeling Opportunities for South Africa.

Anthropogenic transformation of land globally is threatening water resources in terms of quality and availability. Managing water resources to ensure sustainable utilization is important for a semiarid country such as South Africa. Bayesian networks (BNs) are probabilistic graphical models that have been applied globally to a range of water resources management studies; however, there has been very limited application of BNs to similar studies in South Africa. This article explores the benefits and challenges of BN application in the context of water resources management, specifically in relation to South Africa. A brief overview describes BNs, followed by details of some of the possible opportunities for BNs to benefit water resources management. These include the ability to use quantitative and qualitative information, data, and expert knowledge. BN models can be integrated into geographic information systems and predict impact of ecosystem services and sustainability indicators. With additional data and information, BNs can be updated, allowing for integration into an adaptive management process. Challenges in the application of BNs include oversimplification of complex systems, constraints of BNs with categorical nodes for continuous variables, unclear use of expert knowledge, and treatment of uncertainty. BNs have tremendous potential to guide decision making by providing a holistic approach to water resources management.

Correlates of intended COVID-19 vaccine acceptance across time and countries: results from a series of cross-sectional surveys.

OBJECTIVE: Describe demographical, social and psychological correlates of willingness to receive a COVID-19 vaccine. SETTING: Series of online surveys undertaken between March and October 2020. PARTICIPANTS: A total of 25 separate national samples (matched to country population by age and sex) in 12 different countries were recruited through online panel providers (n=25 334). PRIMARY OUTCOME MEASURES: Reported willingness to receive a COVID-19 vaccination. RESULTS: Reported willingness to receive a vaccine varied widely across samples, ranging from 63% to 88%. Multivariate logistic regression analyses reveal sex (female OR=0.59, 95% CI 0.55 to 0.64), trust in medical and scientific experts (OR=1.28, 95% CI 1.22 to 1.34) and worry about the COVID-19 virus (OR=1.47, 95% CI 1.41 to 1.53) as the strongest correlates of stated vaccine acceptance considering pooled data and the most consistent correlates across countries. In a subset of UK samples, we show that these effects are robust after controlling for attitudes towards vaccination in general. CONCLUSIONS: Our results indicate that the burden of trust largely rests on the shoulders of the scientific and medical community, with implications for how future COVID-19 vaccination information should be communicated to maximise uptake.

Robust Decision Analysis under Severe Uncertainty and Ambiguous Tradeoffs: An Invasive Species Case Study.

Bayesian decision analysis is a useful method for risk management decisions, but is limited in its ability to consider severe uncertainty in knowledge, and value ambiguity in management objectives. We study the use of robust Bayesian decision analysis to handle problems where one or both of these issues arise. The robust Bayesian approach models severe uncertainty through bounds on probability distributions, and value ambiguity through bounds on utility functions. To incorporate data, standard Bayesian updating is applied on the entire set of distributions. To elicit our expert's utility representing the value of different management objectives, we use a modified version of the swing weighting procedure that can cope with severe value ambiguity. We demonstrate these methods on an environmental management problem to eradicate an alien invasive marmorkrebs recently discovered in Sweden, which needed a rapid response despite substantial knowledge gaps if the species was still present (i.e., severe uncertainty) and the need for difficult tradeoffs and competing interests (i.e., value ambiguity). We identify that the decision alternatives to drain the system and remove individuals in combination with dredging and sieving with or without a degradable biocide, or increasing pH, are consistently bad under the entire range of probability and utility bounds. This case study shows how robust Bayesian decision analysis provides a transparent methodology for integrating information in risk management problems where little data are available and/or where the tradeoffs are ambiguous.

Scientific Guidance for the preparation of applications on smoke flavouring primary products.

Following a request from the European Commission, EFSA developed updated scientific guidance to assist applicants in the preparation of applications on smoke flavouring primary products. This guidance describes the scientific data to be included in the applications for the authorisation of new smoke flavouring primary products, as well as for the renewal or for the modification of existing authorisations, submitted respectively under Articles 7, 12 and 11 of Regulation (EC) No 2065/2003. Information to be provided in all applications relates to: the characterisation of the primary product, including the description of the source materials, manufacturing process, chemical composition, specifications and stability; the proposed uses and use levels and the assessment of the dietary exposure; the safety data, including information on the genotoxic potential of the identified components and of the unidentified fraction of the primary product, toxicological data other than genotoxicity and information on the safety for the environment. For the toxicological studies a tiered approach is applied, for which the testing requirements, key issues and triggers are described. A description of the standard uncertainties relevant for the evaluation of primary products and how these are considered in the standardised risk assessment procedure is also included. The applicant should generate the data requested in each section to support the safety assessment of the smoke flavouring primary product. On the basis of the submitted data, EFSA will assess the safety of the primary product and conclude whether or not it presents risks to human health and to the environment under the proposed conditions of use.

"This Is What We Don't Know": Treating Epistemic Uncertainty in Bayesian Networks for Risk Assessment.

Failing to communicate current knowledge limitations, that is, epistemic uncertainty, in environmental risk assessment (ERA) may have severe consequences for decision making. Bayesian networks (BNs) have gained popularity in ERA, primarily because they can combine variables from different models and integrate data and expert judgment. This paper highlights potential gaps in the treatment of uncertainty when using BNs for ERA and proposes a consistent framework (and a set of methods) for treating epistemic uncertainty to help close these gaps. The proposed framework describes the treatment of epistemic uncertainty about the model structure, parameters, expert judgment, data, management scenarios, and the assessment's output. We identify issues related to the differentiation between aleatory and epistemic uncertainty and the importance of communicating both uncertainties associated with the assessment predictions (direct uncertainty) and the strength of knowledge supporting the assessment (indirect uncertainty). Probabilities, intervals, or scenarios are expressions of direct epistemic uncertainty. The type of BN determines the treatment of parameter uncertainty: epistemic, aleatory, or predictive. Epistemic BNs are useful for probabilistic reasoning about states of the world in light of evidence. Aleatory BNs are the most relevant for ERA, but they are not sufficient to treat epistemic uncertainty alone because they do not explicitly express parameter uncertainty. For uncertainty analysis, we recommend embedding an aleatory BN into a model for parameter uncertainty. Bayesian networks do not contain information about uncertainty in the model structure, which requires several models. Statistical models (e.g., hierarchical modeling outside the BNs) are required to consider uncertainties and variability associated with data. We highlight the importance of being open about things one does not know and carefully choosing a method to precisely communicate both direct and indirect uncertainty in ERA. Integr Environ Assess Manag 2021;17:221-232. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Estimating effects of arable land use intensity on farmland birds using joint species modeling.

Declines in European farmland birds over past decades have been attributed to the combined effects of agricultural intensification and abandonment. Consequently, aspirations to stop declines should focus attention on reversing these changes through voluntary or policy-driven interventions. The design of such interventions should ideally be informed by scientific knowledge of which aspects of the transformation of agricultural landscapes have contributed to the farmland bird declines. Declines may be associated with loss of natural habitats or the intensification and homogenization of land use management on production land, and furthermore, these changes may interact. Here, we applied an orthogonal design exploiting spatial variation in land use in a major agricultural region of Sweden to seek evidence for benefits to farmland birds of reversing some of the intensifications on and among arable fields and whether effects are modified by the availability of seminatural habitats (pastures and field borders) in the landscape. We accounted for the potentially confounding effect of interactions between species by using a joint species distribution model explicitly controlling for additional variation and covariation among species. We found that interventions aimed specifically at land in production could provide benefits to farmland birds. Landscapes with a higher proportion leys or fallows and/or with a more diverse set of crops held higher abundances of most farmland birds. However, effects were only apparent in landscapes with low availability of seminatural habitats and were sometimes even negative in landscapes with high amounts of such habitats, demonstrating context dependence. Even if we found little evidence of interactions between species, the joint modeling approach provided several benefits. It allowed information to be shared between species making analyses robust to uncertainty due to low abundances and provided direct information about the mean and variability in effects of studied predictors among species. We also found that care needs to be taken regarding prior and distributional assumptions as the importance of species interactions might otherwise be overstated. We conclude that this approach is well suited for evaluating agricultural policies by providing evidence for or against certain interventions or to be linked to policy scenarios of land use change.

Implications of accounting for management intensity on carbon and nitrogen balances of European grasslands.

European managed grasslands are amongst the most productive in the world. Besides temperature and the amount and timing of precipitation, grass production is also highly controlled by applications of nitrogen fertilizers and land management to sustain a high productivity. Since management characteristics of pastures vary greatly across Europe, land-use intensity and their projections are critical input variables in earth system modeling when examining and predicting the effects of increasingly intensified agricultural and livestock systems on the environment. In this study, we aim to improve the representation of pastures in the dynamic global vegetation model LPJ-GUESS. This is done by incorporating daily carbon allocation for grasses as a foundation to further implement daily land management routines and land-use intensity data into the model to discriminate between intensively and extensively used regions. We further compare our new simulations with leaf area index observations, reported regional grassland productivity, and simulations conducted with the vegetation model ORCHIDEE-GM. Additionally, we analyze the implications of including pasture fertilization and daily management compared to the standard version of LPJ-GUESS. Our results demonstrate that grassland productivity cannot be adequately captured without including land-use intensity data in form of nitrogen applications. Using this type of information improved spatial patterns of grassland productivity significantly compared to standard LPJ-GUESS. In general, simulations for net primary productivity, net ecosystem carbon balance and nitrogen leaching were considerably increased in the extended version. Finally, the adapted version of LPJ-GUESS, driven with projections of climate and land-use intensity, simulated an increase in potential grassland productivity until 2050 for several agro-climatic regions, most notably for the Mediterranean North, the Mediterranean South, the Atlantic Central and the Atlantic South.

Pollinator population size and pollination ecosystem service responses to enhancing floral and nesting resources.

Modeling pollination ecosystem services requires a spatially explicit, process-based approach because they depend on both the behavioral responses of pollinators to the amount and spatial arrangement of habitat and on the within- and between-season dynamics of pollinator populations in response to land use. We describe a novel pollinator model predicting flower visitation rates by wild central-place foragers (e.g., nesting bees) in spatially explicit landscapes. The model goes beyond existing approaches by: (1) integrating preferential use of more rewarding floral and nesting resources; (2) considering population growth over time; (3) allowing different dispersal distances for workers and reproductives; (4) providing visitation rates for use in crop pollination models. We use the model to estimate the effect of establishing grassy field margins offering nesting resources and a low quantity of flower resources, and/or late-flowering flower strips offering no nesting resources but abundant flowers, on bumble bee populations and visitation rates to flowers in landscapes that differ in amounts of linear seminatural habitats and early mass-flowering crops. Flower strips were three times more effective in increasing pollinator populations and visitation rates than field margins, and this effect increased over time. Late-blooming flower strips increased early-season visitation rates, but decreased visitation rates in other late-season flowers. Increases in population size over time in response to flower strips and amounts of linear seminatural habitats reduced this apparent competition for pollinators. Our spatially explicit, process-based model generates emergent patterns reflecting empirical observations, such that adding flower resources may have contrasting short- and long-term effects due to apparent competition for pollinators and pollinator population size increase. It allows exploring these effects and comparing effect sizes in ways not possible with other existing models. Future applications include species comparisons, analysis of the sensitivity of predictions to life-history traits, as well as large-scale management intervention and policy assessment.