A perceived gap between invasive species research and stakeholder priorities

Information from research has an important role to play in shaping policy and management responses to biological invasions but concern has been raised that research focuses more on furthering knowledge than on delivering practical solutions. We collated 449 priority areas for science and management from 160 stakeholders including practitioners, researchers and policy makers or advisors working with invasive species, and then compared them to the topics of 789 papers published in eight journals over the same time period (2009–2010). Whilst research papers addressed most of the priority areas identified by stakeholders, there was a difference in geographic and biological scales between the two, with individual studies addressing multiple priority areas but focusing on specific species and locations. We hypothesise that this difference in focal scales, combined with a lack of literature relating directly to management, contributes to the perception that invasive species research is not sufficiently geared towards delivering practical solutions. By emphasising the practical applications of applied research, and ensuring that pure research is translated or synthesised so that the implications are better understood, both the management of invasive species and the theoretical science of invasion biology can be enhanced

Consumer attitudes towards production diseases in intensive production systems

Many members of the public and important stakeholders operating at the upper end of the food chain, may be unfamiliar with how food is produced, including within modern animal production systems. The intensification of production is becoming increasingly common in modern farming. However, intensive systems are particularly susceptible to production diseases, with potentially negative consequences for farm animal welfare (FAW). Previous research has demonstrated that the public are concerned about FAW, yet there has been little research into attitudes towards production diseases, and their approval of interventions to reduce these. This research explores the public’s attitudes towards, and preferences for, FAW interventions in five European countries (Finland, Germany, Poland, Spain and the UK). An online survey was conducted for broilers (n = 789), layers (n = 790) and pigs (n = 751). Data were analysed by means of Kruskal-Wallis ANOVA, exploratory factor analysis and structural equation modelling. The results suggest that the public have concerns regarding intensive production systems, in relation to FAW, naturalness and the use of antibiotics. The most preferred interventions were the most “proactive” interventions, namely improved housing and hygiene measures. The least preferred interventions were medicine-based, which raised humane animal care and food safety concerns amongst respondents. The results highlighted the influence of the identified concerns, perceived risks and benefits on attitudes and subsequent behavioural intention, and the importance of supply chain stakeholders addressing these concerns in the subsequent communications with the public

Towards a unified approach to formal risk of bias assessments for causal and descriptive inference

Statistics is sometimes described as the science of reasoning under uncertainty. Statistical models provide one view of this uncertainty, but what is frequently neglected is the invisible portion of uncertainty: that assumed not to exist once a model has been fitted to some data. Systematic errors, i.e. bias, in data relative to some model and inferential goal can seriously undermine research conclusions, and qualitative and quantitative techniques have been created across several disciplines to quantify and generally appraise such potential biases. Perhaps best known are so-called risk of bias assessment instruments used to investigate the likely quality of randomised controlled trials in medical research. However, the logic of assessing the risks caused by various types of systematic error to statistical arguments applies far more widely. This logic applies even when statistical adjustment strategies for potential biases are used, as these frequently make assumptions (e.g. data missing at random) that can never be guaranteed in finite samples. Mounting concern about such situations can be seen in the increasing calls for greater consideration of biases caused by nonprobability sampling in descriptive inference (i.e. survey sampling), and the statistical generalisability of in-sample causal effect estimates in causal inference; both of which relate to the consideration of model-based and wider uncertainty when presenting research conclusions from models. Given that model-based adjustments are never perfect, we argue that qualitative risk of bias reporting frameworks for both descriptive and causal inferential arguments should be further developed and made mandatory by journals and funders. It is only through clear statements of the limits to statistical arguments that consumers of research can fully judge their value for any specific application.Comment: 12 page

Food waste reduction in supply chains through innovations: a review

Purpose – Agri-food supply chains are facing a number of challenges, which cause inefficiencies resulting in the waste of natural and economic resources, and in negative environmental and social impacts. Food waste (FW) is a result of such inefficiencies and supply chain actors search for economically viable innovations to prevent and reduce it. This study aims to analyse the drivers and the barriers that affect the decision of supply chain operators to adopt innovations (technological – TI, organisational – OI and marketing – MI) to reduce FW. Design/methodology/approach – The analysis was carried out using a four-step approach that included: a literature review to identify factors affecting the decision to adopt innovations; analysis of FW drivers and reduction possibilities along agri-food supply chains through innovations; mapping the results of Steps 1 and 2 and deriving conclusions regarding the factors affecting the adoption of innovations to reduce and prevent FWFindings Results show that different types of innovations have a high potential in reducing and preventing FW along the supply chain; however, they still must be economically feasible to be adopted by decision makers in the food supply chain. TI, OI and MI are often interrelated and can trigger each other. When it comes to a combination of different types of innovation to reduce and prevent FW, a good example of combining TI, OI and MI may be observed in the retail sector in Europe. Here, innovative smartphone apps (TI) to promote the sale of products nearing their expiration dates (OI in terms of organising the sales differently and MI in terms of marketing it differently) were developed and adopted via different retailing channels, leading to the creation of a new business model. Practical implications This study analyses the drivers of FW generation together with the factors affecting the decision to adopt innovations to reduce it and provides solutions to supply chain operators to prevent and reduce FW through different types of innovations. Originality/value Literature has not systematically addressed innovations aiming at the reduction of FW yet. This paper provides a comprehensive literature review of the determinants of innovation adoption and offers a novel view on the problem of FW reduction by means of innovation, by linking factors affecting the decision to innovate with FW drivers. Supply chain, Food waste, Technological innovation, Organisational innovation, Marketing innovationpublishedVersio

Intrareef variations in Li/Mg and Sr/Ca sea surface temperature proxies in the Caribbean reef‐building coral Siderastrea siderea

Caribbean sea surface temperatures (SSTs) have increased at a rate of 0.2°C per decade since 1971, a rate double that of the mean global change. Recent investigations of the coral Siderastrea siderea on the Belize Mesoamerican Barrier Reef System (MBRS) have demonstrated that warming over the last 30 years has had a detrimental impact on calcification. Instrumental temperature records in this region are sparse, making it necessary to reconstruct longer SST records indirectly through geochemical temperature proxies. Here we investigate the skeletal Sr/Ca and Li/Mg ratios of S. siderea from two distinct reef zones (forereef and backreef) of the MBRS. Our field calibrations of S. siderea show that Li/Mg and Sr/Ca ratios are well correlated with temperature, although both ratios are 3 times more sensitive to temperature change in the forereef than in the backreef. These differences suggest that a secondary parameter also influences these SST proxies, highlighting the importance for site‐ and species‐specific SST calibrations. Application of these paleothermometers to downcore samples reveals highly uncertain reconstructed temperatures in backreef coral, but well‐matched reconstructed temperatures in forereef coral, both between Sr/Ca‐SSTs and Li/Mg‐SSTs, and in comparison to the Hadley Centre Sea Ice and Sea Surface Temperature record. Reconstructions generated from a combined Sr/Ca and Li/Mg multiproxy calibration improve the precision of these SST reconstructions. This result confirms that there are circumstances in which both Li/Mg and Sr/Ca are reliable as stand‐alone and combined proxies of sea surface temperature. However, the results also highlight that high‐precision, site‐specific calibrations remain critical for reconstructing accurate SSTs from coral‐based elemental proxies

A systematic review of phenotypic responses to between-population outbreeding

This work was supported by the UK Population Biology Network, through funding from the Natural Environment Research Council and Natural England. We thank Jack Brodie, Helen Hipperson, Marie Chadburn and Sophie Allen for assistance with literature searching, article assessment and data extraction. We also thank our review group for constructive criticism on the scope, development and structure of this review, and two peer reviewers for useful feedback on the review protocol. Finally we thank three peer reviewers who each provided constructive comments on this systematic review report.Peer reviewedPublisher PD

From social interactions to private environmental behaviours: The case of consumer food waste

Consumer food waste, like many environmental behaviours, takes place in private, and is not directly subject to social monitoring. Nevertheless, social interactions can affect private opinions and behaviours. This paper builds an agent-based model of interactions between consumers heterogeneous in their sociability, their initial opinions and behaviours related to food waste, and their willingness to consider different opinions, in order to assess how social interactions can affect private behaviours. Compared to existing models of opinion dynamics, we innovate by including a range of “cognitive dissonance” between stated opinions and actual behaviours that consumers are willing to accept before changing one of the two. We calibrate the model using questionnaire data on household food waste in Italy. We find that a limited degree of mixing between different socio-demographic groups, namely adult and young consumers, is enough to trigger change, but a certain openness of mind is required from more wasteful individuals. Equally, a small group of environmentally committed consumers can attract a sizeable share of the population towards low-waste behaviours if they show a certain variability of opinions and are willing to compromise with individuals in their close neighbourhood in terms of opinions. These findings can help design effective interventions to promote pro-environmental behaviours, taking advantage of the beneficial network effects while anticipating negative externalities

Descriptive inference using large, unrepresentative nonprobability samples: an introduction for ecologists

Biodiversity monitoring usually involves drawing inferences about some variable of interest across a defined landscape from observations made at a sample of locations within that landscape. If the variable of interest differs between sampled and non-sampled locations, and no mitigating action is taken, then the sample is unrepresentative and inferences drawn from it will be biased. It is possible to adjust unrepresentative samples so that they more closely resemble the wider landscape in terms of “auxiliary variables”. A good auxiliary variable is a common cause of sample inclusion and the variable of interest, and if it explains an appreciable portion of the variance in both, then inferences drawn from the adjusted sample will be closer to the truth. We applied six types of survey sample adjustment—subsampling, quasi-randomisation, poststratification, superpopulation modelling, a “doubly robust” procedure, and multilevel regression and poststratification—to a simple two-part biodiversity monitoring problem. The first part was to estimate mean occupancy of the plant Calluna vulgaris in Great Britain in two time-periods (1987-1999 and 2010-2019); the second was to estimate the difference between the two (i.e. the trend). We estimated the means and trend using large, but (originally) unrepresentative, samples from a citizen science dataset. Compared to the unadjusted estimates, the means and trends estimated using most adjustment methods were more accurate, although standard uncertainty intervals generally did not cover the true values. Completely unbiased inference is not possible from an unrepresentative sample without knowing and having data on all relevant auxiliary variables. Adjustments can reduce the bias if auxiliary variables are available and selected carefully, but the potential for residual bias should be acknowledged and reported

Intrareef variations in Li/Mg and Sr/Ca sea surface temperature proxies in the Caribbean reef-building coral Siderastrea siderea

Caribbean sea surface temperatures (SSTs) have increased at a rate of 0.2°C per decade since 1971, a rate double that of the mean global change. Recent investigations of the coral Siderastrea siderea on the Belize Mesoamerican Barrier Reef System (MBRS) have demonstrated that warming over the last 30 years has had a detrimental impact on calcification. Instrumental temperature records in this region are sparse, making it necessary to reconstruct longer SST records indirectly through geochemical temperature proxies. Here we investigate the skeletal Sr/Ca and Li/Mg ratios of S. siderea from two distinct reef zones (forereef and backreef) of the MBRS. Our field calibrations of S. siderea show that Li/Mg and Sr/Ca ratios are well correlated with temperature, although both ratios are 3 times more sensitive to temperature change in the forereef than in the backreef. These differences suggest that a secondary parameter also influences these SST proxies, highlighting the importance for site‐ and species‐specific SST calibrations. Application of these paleothermometers to downcore samples reveals highly uncertain reconstructed temperatures in backreef coral, but well‐matched reconstructed temperatures in forereef coral, both between Sr/Ca‐SSTs and Li/Mg‐SSTs, and in comparison to the Hadley Centre Sea Ice and Sea Surface Temperature record. Reconstructions generated from a combined Sr/Ca and Li/Mg multiproxy calibration improve the precision of these SST reconstructions. This result confirms that there are circumstances in which both Li/Mg and Sr/Ca are reliable as stand‐alone and combined proxies of sea surface temperature. However, the results also highlight that high‐precision, site‐specific calibrations remain critical for reconstructing accurate SSTs from coral‐based elemental proxies