Bayesian Mixing Model Research Articles

Bubble blasts! An adaptation for buoyancy regulation in shallow foraging gray whales.

Foraging efficiency is key to animal fitness. Consequently, animals evolved a variety of kinematic, morphological, physiological, and behavioral adaptations for efficient locomotion to reduce energy expenditure while moving to find, capture, and consume prey. Often suited to specific habitat and prey types, these adaptations correspond to the terrain or substrate the animal moves through. In aquatic systems, adaptations focus on overcoming drag, buoyancy, and hydrostatic forces. Buoyancy both benefits and hinders diving animals; in particular, shallow divers constantly contend with the costs of overcoming buoyancy to dive and maintain position. Pacific Coast Feeding Group (PCFG) gray whales forage in shallow habitats where they work against buoyancy to dive and feed using various foraging tactics. Bubble blasts (underwater exhalations) have been observed during several foraging tactics performed by PCFG whales. As exhalations aid buoyancy regulation in other diving animals, we hypothesize that bubble blasts are performed by longer, more buoyant whales in shallower water and that bubble blasts increase dive duration while accounting for size and tactic. We test our hypotheses using Bayesian linear mixed effects models and a 7-year dataset of drone footage containing concurrent individual morphological and behavioral data. We find that while headstanding - a stationary, head-down tactic - bubble blasts are performed by longer, more buoyant whales and extend the dive duration, whereas whales using forward-swimming tactics are less likely to bubble blast. Our results suggest that PCFG gray whales may use bubble blasts as a behavioral adaption to mitigate the cost of energetically expensive tactics in their shallow habitat foraging niche.

Changes in Water Utilization Characteristics of Trees in Forests across a Successional Gradient in Southern China

Elucidating the water utilization strategy of trees during forest succession is a prerequisite for predicting the direction of forest succession. However, the water utilization characteristics of trees in forests across a successional gradient remain unclear. Here, we utilized the hydrogen and oxygen stable isotopes combined with the Bayesian mixed model (MixSIAR) to analyze the water utilization of dominant trees (Pinus massoniana, Castanea henryi, and Schima superba) in forests along a successional gradient in the Dinghushan Biosphere Reserve of China. Furthermore, we determined the primary factor affecting the water utilization of various trees based on variation partitioning analysis and a random forest model. Our results illustrated that in the early-successional forest, the water utilization ratios from shallow soil layers by P. massoniana were significantly lower than that in the mid-successional forest (51.3%–61.7% vs. 75.3%–81.4%), while its water utilization ratios from deep soil layers exhibited the opposite pattern (26.1%–30.1% vs. 9.0%–15.0%). Similarly, the ratios of water utilization from shallow soil layers by C. henryi (18.9%–29.5% vs. 32.4%–45.9%) and S. superba (10.0%–25.7% vs. 29.2%–66.4%) in the mid-successional forest were relatively lower than in the late-successional forest, whereas their water utilization ratios from deep soil layers showed the contrary tendency. Moreover, our results demonstrated that the diverse water utilization of each tree in different successional forests was mainly attributed to their distinct plant properties. Our findings highlight the increased percentage of water utilization of trees from shallow soil layers with forest succession, providing new insights for predicting the direction of forest succession under changing environments.

Characterizing water solubility of fresh and aged secondary organic aerosol in PM2.5 with the stable carbon isotope technique

Abstract. The investigation of the water-soluble characteristics of secondary organic carbon (SOC) is essential for a more comprehensive understanding of its climate effects. However, due to the limitations of the existing source apportionment methods, the water solubility of different types of SOC remains uncertain. This study analyzed stable carbon isotope and mass spectral signatures of total carbon (TC) and water-soluble organic carbon (WSOC) in ambient PM2.5 samples for 1 year and established stable carbon isotope profiles of fresh and aged SOC. Furthermore, a Bayesian stable isotope mixing (BSIM) model was employed to reveal the water solubility characteristics of fresh and aged SOC in a coastal megacity of China. WSOC was dominated by secondary sources, with fresh and aged SOC contributing 28.1 % and 45.2 %, respectively. Water-insoluble organic carbon (WIOC) was dominated by primary sources, to which fresh and aged SOC contributed 23.2 % and 13.4 %. We also found that the aging degree of SOC has considerable impacts on its water solubility due to the much higher water-soluble fraction of aged SOC (76.5 %) compared to fresh SOC (54.2 %). Findings of this study may provide a new perspective for further investigation of the hygroscopicity effects of SOC with different aging degrees on light extinction and climate change.

Trophic ecology and habitat use of an overexploited commercial snapper (Lutjanus jocu) in a tropical nursery estuary elucidated by stable isotopes

Despite the economic importance and susceptibility to overfishing of the dog snapper Lutjanus jocu, information on their first life stages and the use of nursery habitats remains scarce. Herein, we assessed the seasonal and ontogenetic changes on trophic ecology and habitat use of juveniles in a tropical estuary. Trophic position, prey assimilation, and trophic connectivity across dry and wet seasons and different size classes (< 100 and > 100 mm of total length – TL) were investigated using stable isotope analysis. A total of 57 individuals of 101.8 ± 51.9 mm (mean ± SD) of TL, ranging from 29 mm to 245 mm, had their trophic ecology and habitat use analyzed using dorsal muscle’s carbon (δ13C) and nitrogen (δ15N) stable isotope ratios. Significant differences were observed for δ13C according to the season (ANOVA, p < 0.001), but this pattern was not observed for δ15N (ANOVA, p = 0.471). In contrast, significant differences were observed for δ13C (ANOVA, p = 0.045) and δ15N (ANOVA, p < 0.001) according to the size classes. Trophic position increased according to body size (from 3.01 ± 0.09 to 3.57 ± 0.08 in smaller and larger individuals, respectively), although it remained similar between wet and dry seasons. Mangrove crab (Goniopsis cruentata) was the most assimilated prey across seasons, with a shift towards shrimps for the larger dog snappers. Our Bayesian mixing models revealed that juvenile dog snappers depend predominantly on trophic sources from sheltered estuarine habitats. However, smaller individuals have an isotopic composition more similar to marine sources, therefore, suggesting their recent ingression into the estuarine nursery habitat. In conclusion, our findings may serve as a basis for conservation plans, reinforcing the critical importance of preserving habitat connectivity during the early stages of fish species that use estuaries as nursery grounds and face threats from overexploitation.

Seasonal variability in the feeding ecology of an oceanic predator

Complementary approaches (stomach contents, DNA barcoding, and stable isotopes) were used to examine seasonal shifts in the feeding ecology of an oceanic predator, yellowfin tuna (Thunnus albacares, n = 577), in the northern Gulf of Mexico. DNA barcoding greatly enhanced dietary resolution and seasonally distinct prey assemblages were observed for both sub-adults and adults. In general, diet was characterized by ommastrephid squids and exocoetids in spring, juvenile fishes (i.e., carangids and scombrids) in summer, migratory coastal fishes during fall, and an increased consumption of planktonic prey (e.g., amphipods) in winter. Seasonal variability in bulk stable isotope values (δ13C, δ15N, and δ34S) was also observed, with low δ15N values and high δ34S values during late summer/early fall and high δ15N values (low δ34S) during late winter/early spring. Bayesian stable isotope mixing models corroborated seasonal diet shifts, highlighting the importance of oceanic nekton in spring/summer, coastal nekton during fall, and oceanic plankton during winter. Seasonal shifts in diet appeared to be influenced by prey reproductive cycles, habitat associations, and environmental conditions. Findings highlight the complex food web dynamics supporting an opportunistic oceanic predator and the importance of seasonal cycles in prey availability to predator resource utilization in open-ocean ecosystems.

Isotopic analysis (δ13C and δ2H) of lignin methoxy groups in forest soils to identify and quantify lignin sources

The relative apportion of above and below ground carbon sources is known to be an important factor in soil organic matter formation. Although lignin is the most abundant aromatic plant material in the terrestrial biosphere, our understanding of lignin source contributions to soil organic matter (SOM) is limited due to the complex molecular structure and analysis of lignin. In this study, we novelly apply the dual isotopic analysis (δ13C and δ2H values) of lignin methoxy groups (LMeO) with the Bayesian mixing model, MixSIAR, to apportion lignin sources in two contrasting soil types, a podzol and a stagnosol. Results of the isotopic analysis of LMeO demonstrate the ability of δ2H LMeO values to discriminate between above and below ground lignin sources, while δ13C LMeO values discriminated between photosynthesising and non-photosynthesising tissues. In the stagnosol subsurface horizons, a decreasing proportion of the leaf litter lignin was observed with increasing organic matter degradation, cumulating in the Ah horizon being dominated by lignin from roots. The podzol sites indicated a similar reduction in leaf litter lignin with an increase in organic matter degradation and depth. However, the Ah horizon was shown to accumulate lignin from the above ground woody material. Furthermore, given the significant abundance of LMeO groups in the terrestrial biosphere and the extremely depleted δ13C LMeO values in leaf litter, we employed a mass balance approach to determine the extent in which the 13C bulk enrichment generally associated with isotopic fractionation during organic matter decomposition can be attributed to the shift in lignin sources. Analysis reveals that 14 % and 11 % of bulk 13C enrichment can be attributed to the transition in LMeO sources from leaf litter to roots in the stagnosol and podzol, respectively. Thus, models relying on 13C enrichment with depth as an indicator of carbon turnover may be partially overestimating rates.

Longitudinal analysis of cortisol changes during pubertal development in indigenous Qom girls.

Pubertal research has primarily focused on hypothalamic-pituitary-gonadal axis (HPG) regulation of puberty, though the hypothalamic-pituitary-adrenal axis (HPA) is increasingly considered critical. Heightened HPA function proxied by increasing cortisol levels may play a role in accelerated pubertal timing. However, the extent to which cortisol varies across ages and its relation to pubertal changes in linear growth are less well substantiated. We explored relationships between age, linear growth, adiposity, C-peptide (proxy for insulin), and cortisol across puberty, and we tested whether higher cortisol levels are associated with earlier ages at menarche and peak height velocity. We utilize longitudinal data (n = 777 urine samples) from Qom females ages 7-14 (n = 46) and test our pre-registered analysis using Bayesian longitudinal mixed effects models and joint modeling techniques. We find limited evidence supporting the overarching hypothesis that HPA upregulation is associated with pubertal maturation or timing. We find some evidence that HPA upregulation, as proxied by cortisol, may be more clearly related to differences in relative linear growth at early-mid puberty, as measured by height-for-age z-scores. Transdisciplinary perspectives on puberty, including the assumption that stressors acting via cortisol accelerate pubertal development, are discussed.

Resource utilisation and trophic niche overlap of coralline intertidal benthic amphipods: an isotopic perspective.

Benthic amphipod feeding groups are a well-established trophic classification that is mostly based on field observations and laboratory tests and are used in ecological studies to monitor the ecological state of benthic ecosystems. Globally, carbon and nitrogen stable isotope ratio investigations have provided confirmation of, and novel insights into, the trophic ecology of benthic animals, such as polychaetes. However, stable isotopic examinations of benthic amphipods have been limited. Here, we used microgram samples to compare the species-specific dietary sources, trophic positions, and isotopic niche overlap of selected benthic amphipods from the Gulf of Kachchh, Marine National Park, using elemental analyser-isotopic ratio mass spectrometry (EA-IRMS) of carbon and nitrogen. Overall, all primary carbon sources presented wide variation in the isotopic values of δ13C (6.3‰) and δ15N (greater than 13‰). Conversely, the amphipod taxa displayed relatively narrow range for δ13C (3.9‰) and wider range for δ15N (more than 10‰). The results of the Bayesian mixing model revealed that the benthic amphipods had species-specific feeding preferences. However, the predominant carbon source was organic matter in sediment which reinforced benthic pathways for energy flow for most species. According to the estimated trophic level values (1.62-3.39), these species play a significant role as primary and secondary consumers serving as crucial trophic intermediaries in the food chain, connecting the base to the top consumers. High overlapping ecological niche amongst species was detected by SIBER analysis which indicated co-existence of the benthic amphipods in their respective microhabitats. This signifies wider utilisation of resources and inter-specific feeding preferences with minimal competition amongst amphipod species.

Unveiling nitrate origins in semiarid aquifers: A comparative analysis of Bayesian isotope mixing models using nitrate and boron isotopes and a Positive Matrix Factorization model

Nitrate contamination of groundwater is a pressing global concern, affecting over 80 million people worldwide, with agricultural activities being the primary contributor to nitrogen inputs into aquifers. The primary objective of this study was to identify the predominant sources of nitrate pollution and biogeochemical transformations in the semiarid region of the Meoqui-Delicias aquifer, Mexico. In this region, the uncontrolled use of chemical fertilizers and manure leads to excessive nutrient input, which accelerates the deterioration of groundwater quality. This study introduces an innovative dual-model approach (δ15NNO3 vs. δ11B) to compare the Bayesian Isotope Mixing Model (BIMM) with Positive Matrix Factorization (PMF) for nuanced source apportionment. This approach enhanced the differentiation between manure and sewage as nitrate sources. Results from the δ15NNO3 vs. δ11B model revealed that manure (52.4%) was the most significant source of nitrate pollution in the aquifer, followed by soil (37.4%), chemical fertilizers (5.5%), and sewage (4.7%). The PMF model corroborated this finding and indicated that 60.2% of the NO3–-N pollution in the aquifer was attributed to manure and sewage, confirming the superior performance of the proposed BIMM in source differentiation. Our findings enhance the understanding of nitrate dynamics in semi-arid regions and can serve as a scientific evidence base for targeted interventions in nutrient management in the study area and elsewhere.

Partitioning the sources of sediment organic carbon in South African seagrass meadows

In the sediments of seagrass meadows, allochthonous carbon sources can account for 50–90% of sediment organic carbon (SOC), in which non-seagrass carbon is derived from external organic matter advected into the meadow’s sediments or trapped by the seagrass canopy. Identifying the SOC origin is essential to accurately estimate the climate change mitigation potential of seagrass ecosystems, yet the ratio of allochthonous to autochthonous SOC in South African seagrass populations has not been investigated. In this study, we measured the SOC and carbon isotope ratio (δ13C) in Zostera capensis seagrass meadows in the Berg River and Breede River estuaries and applied Bayesian mixing models to disentangle the SOC contributory sources. Sediment organic carbon differed not only between estuaries, but also showed variability within each estuary, with autochthonous carbon accounting for between ∼35% (SD 0.23) and ∼42.3% (SD 0.18) of total meadow SOC. Other sources of SOC included macroalgae, salt marsh and seagrass species. Our work highlights the importance of accounting for allochthonous carbon in disentangling the drivers of high variability of carbon stocks in estuarine environments and contributes to improving the accuracy of South African seagrass carbon stock estimates.

Multi-method characterization of groundwater nitrate and sulfate contamination by karst mines in southwest China

Groundwater contamination by nitrate and sulfate in mining areas is a significant challenge. Consequently, the inputs sources of these contaminants and their evolution have received considerable attention, with the knowledge gained critical for improved management of water quality. This study integrated data on multiple stable isotopes and water chemistry data and a Bayesian isotope mixing model to investigate the relative contributions of inputs sources of sulfate and nitrate sources to bodies of water in a karst mining area in southwest China. The outcomes indicated that hydrochemical component in the water bodies of the study area is mainly derived from the dissolution of silicate rocks, carbonate rocks and sulfate minerals as well as the oxidation of sulfides. The human and agricultural wastewater, soil nitrogen, and fertilizers were the predominant inputs sources of nitrate to the mine water environment; the predominant inputs sources of sulfide were mineral oxidation, evaporite dissolution, atmospheric deposition, and sewage. Groundwater is mainly recharged from atmospheric precipitation, and surface water is closely hydraulically connected to groundwater. Nitrogen and oxygen isotope composition and water chemistry indicative of nitrification dominate the nitrogen cycle in the study area. The oxidation of pyrite and bacterial sulfate reduction (SRB) had no significant impact on the stable isotopes of groundwater. The results of this study demonstrate the inputs of different sources to nitrate and sulfate in karst mines and associated transformation processes. The results of this study can assist in the conservation of groundwater quality in mining areas and can act as a reference for future related studies.

Memory Retrieval in Online Sentence Parsing: Empirical Evidence, Computational Modelling, and Simulations

This paper reports two experiments (Experiments 1 and 2) and computational simulations designed to investigate and model memory retrieval processes during real-time sentence processing. Central to this study is the hypothesis that linguistic information serves as a cue to retrieve target representations from memory during dependency formation. The basis for this cue-based memory retrieval stems from research showing that non-target representations that match a set of retrieval cues interfere with target retrieval. The susceptibility to this similarity-based interference has been debated in the sentence processing literature, and various hypotheses and models have been formulated and developed. This issue is addressed empirically in Experiments 1 and 2, which investigated similarity-based interference in sentences with a floating quantifier. Bayesian linear mixed models and Bayes factor analyses suggested similarity-based interference. However, the patterns of interference were not consistent with existing theories and models. To reconcile these findings within the framework of cue-based memory retrieval, this paper implements the Revision Integrated Cue-Based (RICB) model based on the ACT–R architecture. This model assumes that structural information is heavily weighted and incorporates the notions of initial retrieval and revision. The results of the simulations indicate that the RICB model successfully predicts the observed data, highlighting the central role of structural information and revision in memory retrieval during real-time sentence processing.

Distinct Mindfulness States Produce Dissociable Effects on Neural Markers of Emotion Processing: Evidence From the Late Positive Potential

BackgroundMindfulness has long been theorized to benefit emotion regulation, but despite the ubiquity of the claim, there is little empirical evidence demonstrating how mindfulness modulates the neurophysiology of emotion processing. The current study aimed to fill this gap in knowledge by leveraging a novel research approach capable of discretizing mindfulness into distinct states of open monitoring (OM) and focused attention (FA) to distinguish their influence on multimodal subjective and objective measures of emotion processing. MethodsUtilizing a fully within-participant picture viewing state induction protocol (N = 30), we compared the effects of OM and FA, rigorously contrasted against an active control, on the visually evoked late positive potential (LPP), a neural index of motivated attention. Bayesian mixed modeling was used to distinguish OM versus FA effects on the early and late sustained LPP while evaluating the influence of subjective arousal ratings as a within-participant moderator of the state inductions. ResultsWhen negative picture trials were retrospectively rated as more subjectively arousing, the OM induction reduced the late sustained LPP response, whereas the FA induction enhanced the LPP. ConclusionsAcute manipulation of OM and FA states may reduce and enhance motivated attention to aversive stimuli during conditions of high subjective arousal, respectively. Functional distinctions between different mindfulness states on emotion processing may be most dissociable after accounting for within-participant variability in how stimuli are appraised. These results support the future potential of the state induction protocol for parsing the neural affective mechanisms that underlie mindfulness training programs and interventions.

Associations of cholinergic system integrity with cognitive decline in GBA1 and LRRK2 mutation carriers

In Parkinson’s disease (PD), GBA1- and LRRK2-mutations are associated with different clinical phenotypes which might be related to differential involvement of the cholinergic system. We investigated cholinergic integrity in 149 asymptomatic GBA1 and 169 asymptomatic LRRK2 mutation carriers, 112 LRRK2 and 60 GBA1 carriers with PD, 492 idiopathic PD, and 180 controls from the PPMI cohort. Basal forebrain volumes were extracted and white matter pathways from nucleus basalis of Meynert (NBM) to cortex and from pedunculopontine nucleus (PPN) to thalamus were assessed with a free water-corrected DTI model. Bayesian ANCOVAs were conducted for group comparisons and Bayesian linear mixed models to assess associations with cognitive decline. Basal forebrain volumes were increased in asymptomatic GBA1 (Bayes Factor against the null hypothesis (BF10) = 75.2) and asymptomatic LRRK2 (BF10 = 57.0) compared to controls. Basal forebrain volumes were increased in LRRK2- compared to GBA1-PD (BF10 = 14.5) and idiopathic PD (BF10 = 3.6*107), with no difference between idiopathic PD and PD-GBA1 (BF10 = 0.25). Mean diffusivity along the medial NBM pathway was decreased in asymptomatic GBA1 compared to controls (BF10 = 30.3). Over 5 years, idiopathic PD and PD-GBA1 declined across all cognitive domains whereas PD-LRRK2 patients only declined in processing speed. We found an interaction between basal forebrain volume and time in predicting multiple cognitive domains in idiopathic PD and PD-GBA1, but not in PD-LRRK2. While LRRK2 and GBA1 mutations are both associated with increased basal forebrain volume at asymptomatic stages, this increase persists at the symptomatic PD stage only in LRRK2 and might be related to slower cognitive decline in these patients.

Farm dam enhancement significantly improves water quality

Artificial water bodies in agricultural landscapes (hereafter ‘farm dams’) are established primarily to support livestock and crop production but also provide habitats for a wide range of native species. Managing water quality in farm dams is essential to animal production and biodiversity. Farm dam enhancement, which includes restricting direct access of stock to dams, can improve water quality in farm dams, by reducing soil erosion and direct faecal contamination, as well as reducing the trampling, grazing, and browsing of vegetation in the immediate catchment. We tested farm dam enhancement as a tool to improve and maintain water quality in 109 farm dams across 34 farms over three years in the sheep-wheat belt of southeast Australia. Using Bayesian Linear Mixed Models, we found that farm dam enhancement significantly reduced levels of phosphorus, nitrogen, turbidity, thermotolerant coliforms, Escherichia coli, and pH. Furthermore, our study revealed links between dam enhancement, increases in vegetation cover, and improved water quality. Our results show that restoration efforts in the surrounds of dams can have positive results on water quality. They highlight the importance of restoration in agricultural landscapes to both agricultural production and biodiversity.

Multi-isotopes (δD, δ18Owater, 87Sr/86Sr, δ34S and δ18Osulfate) as indicators for groundwater salinization genesis and evolution of a large agricultural drainage lake basin in Inner Mongolia, Northwest China

Groundwater salinization, a major eco-environmental problem in arid and semi-arid areas, can accelerate soil salinization, reducing crop productivity and imbalances in ecosystem diversity. This study classified water samples collected from the Ulansuhai Lake basin into five clusters using self-organizing maps (SOM). On this basis, multiple isotopes (δ18Owater, δD, 87Sr/86Sr, δ18Osulfate and δ34S) and isotopic models (Rayleigh fractionation and Bayesian isotope mixing models) were used to identify and quantify the genesis and evolution of groundwater salinization. The results showed that the samples were brackish or saline water, and the hydrochemical types were dominated by Na + K-Cl (SO4). It has been proved that the processes associated with groundwater salinization in the Ulansuhai Lake basin were dominated by water-rock interaction and human inputs. Among them, evaporite dissolution contributed substantially to groundwater salinity. Furthermore, salt inputs from human activities cannot be negligible. Based on the model calculations, evaporite dissolution accounted for the most significant proportion of all sources, with a mean value of 53 %. In addition, human inputs from regular agricultural activities (28 % from sewage and manure and 8 % from fertilizers) constituted another vital source of groundwater salinization associated with extensive agricultural activities in the study area. This study's results can deepen our understanding of the genesis of groundwater salinization and the evolution of the agricultural drainage lake basin. This knowledge will assist the Environmental Protection Department in developing effective policies for groundwater management in the Yellow River Basin.

The isotopic composition of the world’s highest river basins: Role of hydrological mixing ratios and transit time

Hydrological mixing models rely on assumptions governing the rate and timing of mixing proportions, the degree to which isotope ratios conserve the mixing ratios and the estimation of the prior behaviour of meteoric reservoirs. However, these models only describe the integrated catchment response based on different sources having unique and constant isotopic compositions as opposed to location-specific information. Erroneous projection of the hydrological budget can have severe repercussions on climate and eco-hydrological studies, estimation of freshwater availability, and civil and engineering work. Consequently, we design a real-time, multi-parameter, hydrometeorological-constrained, Bayesian-mixing model that can relate meteoric reservoirs to streamflow, and temporal and spatial behaviour of flow paths. Developed for pan-Himalayan catchments (up to 5200 m), with four end-members and pre/post-monsoon seasonality, the isotopic analysis reveals distinct δ18O values: stream water (–9 ± 2.6 ‰), snowpack (–10.7 ± 8.1 ‰), lake water (–12.2 ± 2.5 ‰), and groundwater (–8.4 ± 1.6 ‰). Initial results based on the isotope-enabled, flux-weighted mixing didn’t fully capture spatiotemporal isotopic heterogeneity, affecting hydrograph separation. A revised model, considering the transit time of meteoric reservoirs before their mixing with river discharge, was developed. The revised model illustrates that isotope-enabled mixing models must also consider the hydrometeorological properties of individual reservoirs, the high probability of intermixing between the various reservoirs, and the variable transit time of different meteoric waters in a catchment. With implications for isotope-enabled hydrology, this work describes a novel method applicable to high-mountain hydrology, separating them from other montane or lowland geographies.

Comparison of isotope-based linear and Bayesian mixing models in determining moisture recycling ratio

Comparison of isotope-based linear and Bayesian mixing models in determining moisture recycling ratio

Exploring Co-labeling Strategies in Local Food Markets: Insights from a Choice Experiment on Southern Buyers’ Preferences for Cherry Tomatoes

Labeling strategies are often discussed in the context of local food purchase. Substantial research has been undertaken to discern buyers’ preferences for different labeling strategies associated with a production practice or a geographic location. Some studies have also emphasized the substitution or complementarity effects that may occur across these different labels. Using a large choice experiment with 1820 respondents across six US southern states, this research evaluates buyers’ preferences for co-labeling strategies, focusing on the association of a production practice and certifications (USDA Organic and Certified Naturally Grown) alongside six different production locations, ranging from local to imported sources. We focus on pint baskets of cherry tomatoes, chosen due to their popularity among purchasers of fresh produce. Based on the results provided by a Bayesian Mixed Logit model, we derived the respondent-specific posterior distribution of the partworths associated with each production location and regressed each of those against demographic indicators. Our findings highlight that most buyers substitute between USDA Organic and Certified Naturally Grown (CNG), and a minority consistently opt for the same production practice option. In addition, we underscore that price, or an indication of origin predominantly guides nearly half of buyers’ choices. We find that the premium for CNG is slightly superior to the organic one. Last, older respondents and respondents with a higher degree of education value produce grown within their state over neighboring states and more distant origins.

Bayesian mixed model for survival data with semicompeting risks based on the Clayton copula

Bayesian mixed model for survival data with semicompeting risks based on the Clayton copula