High dimensional land cover inference using remotely sensed MODIS data

Image segmentation persists as a major statistical problem, with the volume and complexity of data expanding alongside new technologies. Land cover classification, one of the most studied problems in Remote Sensing, provides an important example of image segmentation whose needs transcend the choice of a particular classification method. That is, the challenges associated with land cover classification pervade the analysis process from data pre-processing to estimation of a final land cover map. Many of the same challenges also plague the task of land cover change detection. Multispectral, multitemporal data with inherent spatial relationships have hardly received adequate treatment due to the large size of the data and the presence of missing values. In this work we propose a novel, concerted application of methods which provide a unified way to estimate model parameters, impute missing data, reduce dimensionality, classify land cover, and detect land cover changes. This comprehensive analysis adopts a Bayesian approach which incorporates prior knowledge to improve the interpretability, efficiency, and versatility of land cover classification and change detection. We explore a parsimonious, parametric model that allows for a natural application of principal components analysis to isolate important spectral characteristics while preserving temporal information. Moreover, it allows us to impute missing data and estimate parameters via expectation-maximization (EM). A significant byproduct of our framework includes a suite of training data assessment tools. To classify land cover, we employ a spanning tree approximation to a lattice Potts prior to incorporate spatial relationships in a judicious way and more efficiently access the posterior distribution of pixel labels. We then achieve exact inference of the labels via the centroid estimator. To detect land cover changes, we develop a new EM algorithm based on the same parametric model. We perform simulation studies to validate our models and methods, and conduct an extensive continental scale case study using MODIS data. The results show that we successfully classify land cover and recover the spatial patterns present in large scale data. Application of our change point method to an area in the Amazon successfully identifies the progression of deforestation through portions of the region

Participation in collaborative fisheries research improves the perceptions of recreational anglers towards marine protected areas

Collaborative fisheries research programs engage stakeholders in data collection efforts, often with the benefit of increasing transparency about the status and management of natural resources. These programs are particularly important in marine systems, where management of recreational and commercial fisheries have historically been contentious. One such program is the California Collaborative Fisheries Research Program (CCFRP), which was designed in 2006 to engage recreational anglers in the scientific process and evaluate the efficacy of California’s network of marine protected areas. CCFRP began on the Central Coast of California and expanded statewide in 2017 to include six partner institutions in three regions: Northern, Central, and Southern California. To date, over 2,000 volunteer anglers have participated in the program, with many anglers volunteering for multiple years. However, the impacts of outreach, education, and collaborative research on those anglers at the statewide scale are currently unknown. Thus, the objective of the current study was to survey the statewide pool of volunteer anglers to assess the degree to which participation in CCFRP has influenced angler perceptions of MPAs, fisheries management, and conservation. We received 259 completed surveys out of a pool of 1,386 active anglers, equating to an 18.7% response rate. Participation in CCFRP resulted in a significant, positive impact on anglers’ attitudes towards MPAs in California across all regions. Anglers who participated in six or more CCFRP fishing trips had a more positive perception of MPAs than those who participated in fewer trips. Volunteer anglers across all regions perceived that they caught larger fishes, a higher abundance of fishes, and a greater diversity of species inside MPAs, consistent with the ecological findings of the program. These results highlight the benefits of involving community members in collaborative scientific research. Collaboration between researchers and the broader community increases transparency and trust between stakeholders, and results in greater understanding of natural resource dynamics, ultimately producing better management outcomes

Participation in collaborative fisheries research improves the perceptions of recreational anglers towards marine protected areas

Collaborative fisheries research programs engage stakeholders in data collection efforts, often with the benefit of increasing transparency about the status and management of natural resources. These programs are particularly important in marine systems, where management of recreational and commercial fisheries have historically been contentious. One such program is the California Collaborative Fisheries Research Program (CCFRP), which was designed in 2006 to engage recreational anglers in the scientific process and evaluate the efficacy of California’s network of marine protected areas. CCFRP began on the Central Coast of California and expanded statewide in 2017 to include six partner institutions in three regions: Northern, Central, and Southern California. To date, over 2,000 volunteer anglers have participated in the program, with many anglers volunteering for multiple years. However, the impacts of outreach, education, and collaborative research on those anglers at the statewide scale are currently unknown. Thus, the objective of the current study was to survey the statewide pool of volunteer anglers to assess the degree to which participation in CCFRP has influenced angler perceptions of MPAs, fisheries management, and conservation. We received 259 completed surveys out of a pool of 1,386 active anglers, equating to an 18.7% response rate. Participation in CCFRP resulted in a significant, positive impact on anglers’ attitudes towards MPAs in California across all regions. Anglers who participated in six or more CCFRP fishing trips had a more positive perception of MPAs than those who participated in fewer trips. Volunteer anglers across all regions perceived that they caught larger fishes, a higher abundance of fishes, and a greater diversity of species inside MPAs, consistent with the ecological findings of the program. These results highlight the benefits of involving community members in collaborative scientific research. Collaboration between researchers and the broader community increases transparency and trust between stakeholders, and results in greater understanding of natural resource dynamics, ultimately producing better management outcomes

Olive- and Coconut-Oil-Enriched Diets Decreased Secondary Bile Acids and Regulated Metabolic and Transcriptomic Markers of Brain Injury in the Frontal Cortexes of NAFLD Pigs

The objective of this study was to investigate the effect of dietary fatty acid (FA) saturation and carbon chain length on brain bile acid (BA) metabolism and neuronal number in a pig model of pediatric NAFLD. Thirty 20-day-old Iberian pigs, pair-housed in pens, were randomly assigned to receive one of three hypercaloric diets for 10 weeks: (1) lard-enriched (LAR; n = 5 pens), (2) olive-oil-enriched (OLI, n = 5), and (3) coconut-oil-enriched (COC; n = 5). Pig behavior and activity were analyzed throughout the study. All animals were euthanized on week 10 and frontal cortex (FC) samples were collected for immunohistochemistry, metabolomic, and transcriptomic analyses. Data were analyzed by multivariate and univariate statistics. No differences were observed in relative brain weight, neuronal number, or cognitive functioning between diets. Pig activity and FC levels of neuroprotective secondary BAs and betaine decreased in the COC and OLI groups compared with LAR, and paralleled the severity of NAFLD. In addition, OLI-fed pigs showed downregulation of genes involved in neurotransmission, synaptic transmission, and nervous tissue development. Similarly, COC-fed pigs showed upregulation of neurogenesis and myelin repair genes, which caused the accumulation of medium-chain acylcarnitines in brain tissue. In conclusion, our results indicate that secondary BA levels in the FCs of NAFLD pigs are affected by dietary FA composition and are associated with metabolic and transcriptomic markers of brain injury. Dietary interventions that aim to replace saturated FAs by medium-chain or monounsaturated FAs in high-fat hypercaloric diets may have a negative effect on brain health in NAFLD patients