Can Social Media Help Us Understand The Impact of Climate Change on Forests in The US?

While social media data are increasingly being used in the study of pressing environmental problems, their ability to monitor environmental changes has scarcely been assessed. Understanding this viability is highly important as climate change increasingly impacts public health, and behavior. We examine social media photographs associated with wildfires in Yellowstone National Park to assess if images and content can adequately capture environmental change associated with large-scale landscape impacts - wildfires - using computer vision, natural language processing and spatiotemporal analysis. We find that social media posts associated with wildfire events rarely capture the fires themselves, while landscape impacts including burnt trees and early succession are more frequently the topic of photography. Furthermore, we find that computer vision has challenges with capturing these phenomena. While capturing wildfires proved difficult, developing multimodal analysis including natural language processing, spatial, trend and computer vision analysis at scale may open opportunities for more general understanding of social media’s efficacy for monitoring environmental change

Social-ecological enabling conditions for payments for ecosystem services

The concept of “enabling conditions” centers on conditions that facilitate approaches to addressing social and ecological challenges. Although multiple fields have independently addressed the concept of enabling conditions, the literature lacks a shared understanding or integration of concepts. We propose a more synthesized understanding of enabling conditions beyond disciplinary boundaries by focusing on the enabling conditions that influence the implementation of a range of environmental policies termed payments for ecosystem services (PES). Through an analysis of key literature from different disciplinary perspectives, we examined how researchers and practitioners refer to and identify enabling conditions within the context of PES. Through our synthesis, we identified 24 distinct enabling conditions organized within 4 broad themes: biophysical, economic, governance, and social-cultural conditions. We found that the literature coalesces around certain enabling conditions, such as strong ecosystem science and existing institutions, regardless of disciplinary background or journal audience. We also observed key differences in how authors perceive the direction of influence for property type, program objectives, and number of actors. Additionally, we noted an emphasis on the importance of the contextual nature of many enabling conditions that may cause certain conditions to have a disproportionate impact on successful implementation in some circumstances. Unraveling the relative importance of specific enabling conditions in diverse contexts remains a research frontier. Ultimately, no single disciplinary perspective is likely to provide all necessary insights for PES creation, and given the intertwined nature of enabling conditions, practitioners need to consider insights from multiple dimensions. Our work suggests opportunities to better connect diverse conversations through integration of concepts, a common vocabulary, and a synthetic framework

Global state and potential scope of investments in watershed services for large cities

Investments in watershed services (IWS) programs, in which downstream water users pay upstream watershed service suppliers for actions that protect drinking water, are increasing in number and scope. IWS programs represent over $170 million of investment in over 4.3 million ha of watersheds, providing water to over 230 million people. It is not yet fully clear what factors contribute to the establishment and sustainability of IWS. We conducted a representative global analysis of 416 of the world’s largest cities, including 59 (14%) with IWS programs. Using random forest ensemble learning methods, we evaluated the relative importance of social and ecological factors as predictors of IWS presence. IWS programs are more likely present in source watersheds with more agricultural land and less protected area than otherwise similar watersheds. Our results suggest potential to expand IWS as a strategy for drinking water protection and also contribute to decisions regarding suitable program locations

Forest ecosystem properties emerge from interactions of structure and disturbance

Forest structural diversity and its spatiotemporal variability are constrained by environmental and biological factors, including species pools, climate, land-use history, and legacies of disturbance regimes. These factors influence forest responses to disturbances and their interactions with structural diversity, potentially creating structurally mediated emergent properties at local to continental spatial scales and over evolutionary time. Here, we present a conceptual framework for exploring the emergent properties that arise from interactions between forest structural diversity and disturbances. We synthesize and present definitions for key terms, including emergent property, disturbance, and resilience, and highlight various types and examples of emergent properties, such as (1) interactions with species composition, (2) interactions with disturbance frequency and intensity, and (3) evolutionary changes to communities. Although emergent properties in forest ecosystems remain poorly understood, we describe a foundation for study and applied management of forest structural diversity to enhance forest restoration and resilience

Integrating team science into interdisciplinary graduate education: an exploration of the SESYNC Graduate Pursuit

Complex socio-environmental challenges require interdisciplinary, team-based research capacity. Graduate students are fundamental to building such capacity, yet formal opportunities for graduate students to develop these capacities and skills are uncommon. This paper presents an assessment of the Graduate Pursuit (GP) program, a formal interdisciplinary team science graduate research and training program administered by the National Socio-Environmental Synthesis Center (SESYNC). Quantitative and qualitative assessment of the program’s first cohort revealed that participants became significantly more comfortable with interdisciplinary research and team science approaches, increased their capacity to work across disciplines, and were enabled to produce tangible research outcomes. Qualitative analysis of four themes—(1) discipline, specialization, and shared purpose, (2) interpersonal skills and personality, (3) communication and teamwork, and (4) perceived costs and benefits—encompass participants’ positive and negative experiences and support findings from past assessments. The findings also identify challenges and benefits related to individual personality traits and team personality orientation, the importance of perceiving a sense of autonomy and independence, and the benefit of graduate training programs independent of the university and graduate program environment

A theoretical framework for the ecological role of three-dimensional structural diversity

The three-dimensional (3D) physical aspects of ecosystems are intrinsically linked to ecological processes. Here, we describe structural diversity as the volumetric capacity, physical arrangement, and identity/traits of biotic components in an ecosystem. Despite being recognized in earlier ecological studies, structural diversity has been largely overlooked due to an absence of not only a theoretical foundation but also effective measurement tools. We present a framework for conceptualizing structural diversity and suggest how to facilitate its broader incorporation into ecological theory and practice. We also discuss how the interplay of genetic and environmental factors underpin structural diversity, allowing for a potentially unique synthetic approach to explain ecosystem function. A practical approach is then proposed in which scientists can test the ecological role of structural diversity at biotic–environmental interfaces, along with examples of structural diversity research and future directions for integrating structural diversity into ecological theory and management across scales

Para-infectious brain injury in COVID-19 persists at follow-up despite attenuated cytokine and autoantibody responses

To understand neurological complications of COVID-19 better both acutely and for recovery, we measured markers of brain injury, inflammatory mediators, and autoantibodies in 203 hospitalised participants; 111 with acute sera (1–11 days post-admission) and 92 convalescent sera (56 with COVID-19-associated neurological diagnoses). Here we show that compared to 60 uninfected controls, tTau, GFAP, NfL, and UCH-L1 are increased with COVID-19 infection at acute timepoints and NfL and GFAP are significantly higher in participants with neurological complications. Inflammatory mediators (IL-6, IL-12p40, HGF, M-CSF, CCL2, and IL-1RA) are associated with both altered consciousness and markers of brain injury. Autoantibodies are more common in COVID-19 than controls and some (including against MYL7, UCH-L1, and GRIN3B) are more frequent with altered consciousness. Additionally, convalescent participants with neurological complications show elevated GFAP and NfL, unrelated to attenuated systemic inflammatory mediators and to autoantibody responses. Overall, neurological complications of COVID-19 are associated with evidence of neuroglial injury in both acute and late disease and these correlate with dysregulated innate and adaptive immune responses acutely

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Causes and Consequences of Tree Growth, Injury, and Decay in Sierra Nevada Forest Ecosystems

In the course of its long life, a tree confronts environmental conditions that range from natural variation in local weather or regional climate to large scale alteration of the earth’s atmosphere. Forest ecosystems are modified and potentially degraded by an array of anthropogenic enterprises, not the least of which is air pollution. Environmental change can alter ecosystem patterns and processes, particularly when effects accumulate over the long term or multiple factors interact. My dissertation research examines two key aspects of forest ecosystem dynamics in response to altered environmental conditions over the long term. First, I examine mortality, and in particular standing dead trees, one of the predominant physical consequences of forest ecosystem stress. This work quantifies the decay patterns of six common species of California’s mixed conifer forests, revealing the role of standing dead trees in forest carbon budgets. Next, my research examines influences on the growth and vitality of live trees in the southern Sierra Nevada, a forested region impacted by chronic ozone pollution. This work encompasses the regional patterns of ecosystem exposure to ozone pollution, long term monitoring of ozone-induced injury to ponderosa and Jeffrey pine trees (Pinus ponderosa and Pinus Jeffreyi), and a description of tree growth responses to pollution in light of their simultaneous responses to climate.Forest mortality is always an important part of ecosystem processes, but in recent years, elevated mortality rates have increased the relative abundance of dead trees in forests across the Western United States. Though the importance of woody debris to ecosystem processes is clear, the structural and biogeochemical contributions of standing dead trees remain largely unknown. The first chapter of my dissertation characterizes the decay patterns and carbon density of standing dead trees in Sierra Nevada mixed conifer forests, examining traits in six dominant species. I used a dimensional analysis to describe the patterns of wood density, carbon concentration, and net carbon density. As decay class advanced, trees showed a progressively lower density and a small increase in carbon concentration. Net carbon density of the most decayed standing dead trees was only 60% that of live trees. The key characteristics that determined these patterns were species, surface to volume ratio, and relative position within each tree. Decay while standing and estimation of deadwood biomass in large scale inventories also have repercussions in greenhouse gas accounting. When the measured changes in carbon density were applied to standing dead carbon stock estimates for California mixed conifer forests, the decay-adjusted estimates were 18% (3.66-3.74 teragrams) lower than estimates that did not incorporate change due to decay. In the second and third chapters, I focus on anthropogenic ozone pollution, a major stressor in southern Sierra Nevada forests. Ozone poses a risk to ecosystems worldwide because of its damaging effects on plant tissues and the carbon fixation they carry out. Ozone is a secondary pollutant formed by the reaction of nitrogen oxides and oxygen in the presence of sunlight and heat. Elevated tropospheric ozone has impacted parts of southern California, the San Joaquin Valley, and the southern Sierra Nevada for more than 40 years. This field-based research relies on data collected in Sequoia and Kings Canyon National Parks and on the Sierra National Forest. Chapter two investigates the connections between ozone exposure and injury to trees. The tools of this study were a long term air quality monitoring network across a regional gradient of ozone concentration and repeat measures of pollution injury in ponderosa and Jeffrey pines. I used these measures to quantify trends in ozone concentration, assess patterns in ozone-caused foliar injury, and understand tree demographic responses to ozone exposure. Since region-wide observations began in 1991, air quality has improved, but across much of the mixed conifer forest, ozone exposure is still high enough to cause permanent damage to ecosystems. Chlorotic mottle, the key symptom of pollution injury in ponderosa and Jeffrey pines, continues to provide evidence of physiological impacts to trees but has also incrementally declined in recent years. Because growth is a leading indicator of tree vitality and forest ecosystem condition, in this study I also remeasured tree diameters to determine the long term relative growth rates of individuals exposed to ozone pollution. Relative to asymptomatic trees, typical ozone-injured trees from the most polluted sites had growth reduced by up to 24%. Over the 20-year study survival of damaged trees was lowest at high pollution levels, but within the range of rates in similar forests. The pollution-injured pines that make up southern Sierra Nevada forests today clearly have the capacity for recovery, but will continue to bear a legacy of anthropogenic impacts. In the third chapter, I examine how Sierra Nevada forest ecosystems respond to climatic conditions and chronic ozone pollution, both individually and interactively. The gradient of pollution exposure on the western slope of the southern Sierra Nevada enabled a comparison of annual tree growth under very low to severe summer ozone levels, across sites with shared climatic conditions. I used the Jeffrey pine tree ring record to characterize growth as shaped by these conditions. First, I found that the temperature and precipitation of the preceding winter and summer have an important influence on annual growth. Building on this understanding of climatic dependency, analysis showed that trees exposed to elevated ozone had slower annual growth rates than their counterparts in relatively unpolluted locations. Annual growth rates in severely polluted sites were 8.4-23% lower than predicted growth under conditions that meet current air quality standards. Although the isolated effects of both ozone and water limitation are negative, an antagonistic interaction between these environmental factors was also apparent. As predicted in earlier research, high summer temperatures limited the negative growth impacts of ozone pollution. The likely mechanism for this interaction amongst stressors is stomatal closure, which prevents uptake of ozone into the leaf. These growth losses, attributable to a chronic anthropogenic stressor and modified by prevailing environmental conditions, may facilitate further change in forest processes

Habitat and climatic associations of climate‐sensitive species along a southern range boundary

Abstract Climate change and habitat loss are recognized as important drivers of shifts in wildlife species' geographic distributions. While often considered independently, there is considerable overlap between these drivers, and understanding how they contribute to range shifts can predict future species assemblages and inform effective management. Our objective was to evaluate the impacts of habitat, climatic, and anthropogenic effects on the distributions of climate‐sensitive vertebrates along a southern range boundary in Northern Michigan, USA. We combined multiple sources of occurrence data, including harvest and citizen‐science data, then used hierarchical Bayesian spatial models to determine habitat and climatic associations for four climate‐sensitive vertebrate species (American marten [Martes americana], snowshoe hare [Lepus americanus], ruffed grouse [Bonasa umbellus] and moose [Alces alces]). We used total basal area of at‐risk forest types to represent habitat, and temperature and winter habitat indices to represent climate. Marten associated with upland spruce‐fir and lowland riparian forest types, hares with lowland conifer and aspen‐birch, grouse with lowland riparian hardwoods, and moose with upland spruce‐fir. Species differed in climatic drivers with hares positively associated with cooler annual temperatures, moose with cooler summer temperatures and grouse with colder winter temperatures. Contrary to expectations, temperature variables outperformed winter habitat indices. Model performance varied greatly among species, as did predicted distributions along the southern edge of the Northwoods region. As multiple species were associated with lowland riparian and upland spruce‐fir habitats, these results provide potential for efficient prioritization of habitat management. Both direct and indirect effects from climate change are likely to impact the distribution of climate‐sensitive species in the future and the use of multiple data types and sources in the modelling of species distributions can result in more accurate predictions resulting in improved management at policy‐relevant scales