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

\ua9 2023 The Authors. Ecology published by Wiley Periodicals LLC on behalf of The Ecological Society of America.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 nonsampled 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, quasirandomization, poststratification, superpopulation modeling, a “doubly robust” procedure, and multilevel regression and poststratification—to a simple two-part biodiversity monitoring problem. The first part was to estimate the 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 with 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

Are reintroductions an effective way of mitigating against plant extinctions? CEE review 07-008 (SR32)

Re-introductions are considered by some conservation practitioners to be a controversial management option for mitigating threatened plant declines. The use of translocations (including re-introductions) has been criticised for the lack of monitoring and central recording, inappropriateness of the action due to genetic considerations, a lack of knowledge of the demography of the donor populations and inadequate information on the habitat requirements of the species. Despite these arguably justified criticisms, re-introductions are growing in use as practitioners see no other option for meeting management plan targets. Re-introductions have been proposed as options for overcoming habitat loss, habitat fragmentation and reproductive isolation. An extension of this increasingly interventionist approach, often termed assisted colonisation, is being considered as a potential method for preventing extinctions due to climatic shifts too rapid to allow corresponding species‟ distribution changes. This review evaluates the effectiveness of re-introductions as a conservation tool by using the available evidence to determine in what context plant translocations have improved the status of threatened species

Development of a baseline-temperature correction methodology for electrochemical sensors and its implications for long-term stability

Recent studies have shown that (three-electrode) electrochemical sensors can be utilised for air quality monitoring and exposure assessment. The long-term performance of these sensors is however, often limited by the effects of ambient meteorological parameters on the sensor baseline, in particular temperature. If electrochemical (EC) sensors are to be adopted for air quality measurement over extended periods (months), this effect must be accounted for. Recent long-term, ambient measurements of CO, NO and NO$_2$ using EC sensors have revealed that temperature (and relative humidity (RH)) had an effect on the baseline which was more pronounced in the case of NO sensors with coefficient of determination, $R^2$ of 0.9 when compared to CO and NO$_2$ with $R^2$ < 0.2. In this paper we present a correction methodology that quantifies this effect (referred to here as fitted baseline), implementing these correction on the EC measurements. We found that EC sensors corrected for baseline-temperature effect using the method describe in this paper show good agreement when compared with traditional reference instrument. The coefficient of determination $R^2$ of 0.7-0.8 and gradient of 0.9 was observed for baseline-temperature corrected NO compared to $R^2$ = 0.02 prior to baseline-temperature correction. Furthermore, the correction methodology was validated by comparing the temperature-baseline with proxy temperature compensating measurements obtained from the fourth electrode of a set of novel four-electrode electrochemical sensors. A good agreement (R$^2$ = 0.9, with gradients = 0.7-1.08 for NO and 0.5 < R$^2$ < 0.73 for CO) was observed between temperature fitted baselines and outputs from the fourth electrodes (also known non-sensing/auxiliary electrode). Meanwhile, the long-term stability (calibrated signal output) of temperature-corrected data was evaluated by comparing the change in sensor gain to meteorological parameters including temperature, relative humidity, wind speed and wind direction. The results showed that there was no statistically significant change in sensitivity (two-sided $t$-test, p = 0.34) of the temperature-corrected electrochemical sensor with respect to these parameters (over several months). This work demonstrates that using the baseline-temperature correction methodology described in this paper, electrochemical sensors can be used for long-term (months), quantitative measurements of air quality gases at the parts per billion volume (ppb) mixing ratio level typical of ambient conditions in the urban environment.The authors would like to thank Cambridge Commonwealth Trust & Cambridge Overseas Trust and Dorothy Hodgkin Studentship for the PhD studentship awarded to Olalekan Popoola. We will like to thank NERC for funding the SNAQ Heathrow project as well as DfT and EPSRC for funding the MESSAGE project

Source attribution of air pollution by spatial scale separation using high spatial density networks of low cost air quality sensors

To carry out detailed source attribution for air quality assessment it is necessary to distinguish pollutant contributions that arise from local emissions from those attributable to non-local or regional emission sources. Frequently this requires the use of complex models and inversion methods, prior knowledge or assumptions regarding the pollution environment. In this paper we demonstrate how high spatial density and fast response measurements from low-cost sensor networks may facilitate this separation. A purely measurement-based approach to extract underlying pollution levels (baselines) from the measurements is presented exploiting the different relative frequencies of local and background pollution variations. This paper shows that if high spatial and temporal coverage of air quality measurements are available, the different contributions to the total pollution levels, namely the regional signal as well as near and far field local sources, can be quantified. The advantage of using high spatial resolution observations, as can be provided by low-cost sensor networks, lies in the fact that no prior assumptions about pollution levels at individual deployment sites are required. The methodology we present here, utilising measurements of carbon monoxide (CO), has wide applicability, including additional gas phase species and measurements obtained using reference networks. While similar studies have been performed, this is the first study using networks at this density, or using low cost sensor networks.The authors thank EPSRC (EP/E001912/1) for funding for the Message project. IH thanks the German National Academic Foundation for funding of MPhil degree.This is the final published version. It first appeared at http://www.sciencedirect.com/science/article/pii/S1352231015300583#

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

The use of electrochemical sensors for monitoring urban air quality in low-cost, high-density networks

Measurements at appropriate spatial and temporal scales are essential for understanding and monitoring spatially heterogeneous environments with complex and highly variable emission sources, such as in urban areas. However, the costs and complexity of conventional air quality measurement methods means that measurement networks are generally extremely sparse. In this paper we show that miniature, low-cost electrochemical gas sensors, traditionally used for sensing at parts-per-million (ppm) mixing ratios can, when suitably configured and operated, be used for parts-per-billion (ppb) level studies for gases relevant to urban air quality. Sensor nodes, in this case consisting of multiple individual electrochemical sensors, can be low-cost and highly portable, thus allowing the deployment of scalable high-density air quality sensor networks at fine spatial and temporal scales, and in both static and mobile configurations.This work was supported by EPSRC (grant number EP/E002102/1) and the Department for Transport

Comparative prebiotic activity of mixtures of cereal grain polysaccharides

The main components of the non-starch polysaccharide (NSP) fraction of wheat flour are arabinoxylan (AX) and β-glucan. These are also present in other cereal grains, but their proportions vary with AX being the major component in wheat and rye and β-glucan in barley and oats. Therefore, it was hypothesised that these NSPs could act synergistically when fermented in vitro at the ratios present in the major foods consumed, resulting in increased prebiotic activity. AX and β-glucan were therefore tested in in vitro fermentation studies to assess their prebiotic activity when used individually and/or in different ratios. Short-chain fatty-acids (SCFAs) produced from in vitro fermentation were measured using HPLC and bacterial populations were measured using flow cytometry with fluorescence in situ hybridisation (Flow-FISH). Fermentation of AX alone resulted in a significant bifidogenic activity and increased concentrations of SCFAs, mainly acetate, after 8-24 h of fermentation, however β-glucan alone did not show prebiotic activity. The greatest prebiotic activity, based on concentration of total SCFAs and increases in total bacteria as well as beneficial Bifidobacterium and Clostridium coccoides/Eubacterium groups, was observed when AX and β-glucan were combined at a 3:1 ratio, which corresponds to their ratios in wheat flour which is major source of cereal fibre in the diet. This indicates that the population of bacteria in the human GI tract may be modulated by the composition of the fibre in the diet, to maximise the prebiotic potential

How large should whales be?

The evolution and distribution of species body sizes for terrestrial mammals is well-explained by a macroevolutionary tradeoff between short-term selective advantages and long-term extinction risks from increased species body size, unfolding above the 2g minimum size induced by thermoregulation in air. Here, we consider whether this same tradeoff, formalized as a constrained convection-reaction-diffusion system, can also explain the sizes of fully aquatic mammals, which have not previously been considered. By replacing the terrestrial minimum with a pelagic one, at roughly 7000g, the terrestrial mammal tradeoff model accurately predicts, with no tunable parameters, the observed body masses of all extant cetacean species, including the 175,000,000g Blue Whale. This strong agreement between theory and data suggests that a universal macroevolutionary tradeoff governs body size evolution for all mammals, regardless of their habitat. The dramatic sizes of cetaceans can thus be attributed mainly to the increased convective heat loss is water, which shifts the species size distribution upward and pushes its right tail into ranges inaccessible to terrestrial mammals. Under this macroevolutionary tradeoff, the largest expected species occurs where the rate at which smaller-bodied species move up into large-bodied niches approximately equals the rate at which extinction removes them.Comment: 7 pages, 3 figures, 2 data table

Co-opetition models for governing professional football

In recent years, models for co-creating value in a business-to-business context have often been examined with the aim of studying the strategies implemented by and among organisations for competitive and co-operative purposes. The traditional concepts of competition and co-operation between businesses have now evolved, both in terms of the sector in which the businesses operate and in terms of the type of goods they produce. Many researchers have, in recent times, investigated the determinants that can influence the way in which the model of co-opetition can be applied to the football world. Research interest lies in the particular features of what makes a good football. In this paper, the aim is to conduct an analysis of the rules governing the “football system”, while also looking at the determinants of the demand function within football entertainment. This entails applying to football match management the co-opetition model, a recognised model that combines competition and co-operation with the view of creating and distributing value. It can, therefore, be said that, for a spectator, watching sport is an experience of high suspense, and this suspense, in turn, depends upon the degree of uncertainty in the outcome. It follows that the rules ensuring that both these elements can be satisfied are a fertile ground for co-operation between clubs, as it is in the interest of all stakeholders to offer increasingly more attractive football, in comparison with other competing products. Our end purpose is to understand how co-opetition can be achieved within professional football

Prior Mating Experience Modulates the Dispersal of Drosophila in Males More Than in Females

Cues from both an animal’s internal physiological state and its local environment may influence its decision to disperse. However, identifying and quantifying the causative factors underlying the initiation of dispersal is difficult in uncontrolled natural settings. In this study, we automatically monitored the movement of fruit flies and examined the influence of food availability, sex, and reproductive status on their dispersal between laboratory environments. In general, flies with mating experience behave as if they are hungrier than virgin flies, leaving at a greater rate when food is unavailable and staying longer when it is available. Males dispersed at a higher rate and were more active than females when food was unavailable, but tended to stay longer in environments containing food than did females. We found no significant relationship between weight and activity, suggesting the behavioral differences between males and females are caused by an intrinsic factor relating to the sex of a fly and not simply its body size. Finally, we observed a significant difference between the dispersal of the natural isolate used throughout this study and the widely-used laboratory strain, Canton-S, and show that the difference cannot be explained by allelic differences in the foraging gene