Earth system data cubes unravel global multivariate dynamics

Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model-data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model-data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model-data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved

Earth system data cubes unravel global multivariate dynamics

Understanding Earth system dynamics in light of ongoing human intervention and dependency remains a major scientific challenge. The unprecedented availability of data streams describing different facets of the Earth now offers fundamentally new avenues to address this quest. However, several practical hurdles, especially the lack of data interoperability, limit the joint potential of these data streams. Today, many initiatives within and beyond the Earth system sciences are exploring new approaches to overcome these hurdles and meet the growing interdisciplinary need for data-intensive research; using data cubes is one promising avenue. Here, we introduce the concept of Earth system data cubes and how to operate on them in a formal way. The idea is that treating multiple data dimensions, such as spatial, temporal, variable, frequency, and other grids alike, allows effective application of user-defined functions to co-interpret Earth observations and/or model-data integration. An implementation of this concept combines analysis-ready data cubes with a suitable analytic interface. In three case studies, we demonstrate how the concept and its implementation facilitate the execution of complex workflows for research across multiple variables, and spatial and temporal scales: (1) summary statistics for ecosystem and climate dynamics; (2) intrinsic dimensionality analysis on multiple timescales; and (3) model-data integration. We discuss the emerging perspectives for investigating global interacting and coupled phenomena in observed or simulated data. In particular, we see many emerging perspectives of this approach for interpreting large-scale model ensembles. The latest developments in machine learning, causal inference, and model-data integration can be seamlessly implemented in the proposed framework, supporting rapid progress in data-intensive research across disciplinary boundaries. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved

Monitoring ecological change during rapid socio-economic and political transitions: Colombian ecosystems in the post-conflict era

After more than 50-years of armed conflict, Colombia is now transitioning to a more stable social and political climate due to a series of peace agreements between the government and different armed groups. Consequences of these socio-economic and political changes on ecosystems are largely uncertain, but there is growing concern about derived increases in environmental degradation. Here, we review the capacity of Colombia to monitor the state of its ecosystems and their rate of change over time. We found several important programs currently set in place by different institutions as well as by independent groups of scientists that address different aspects of environmental monitoring. However, most of the current initiatives could be improved in terms of data coverage, quality and access, and could be better articulated among each other. We propose a set of activities that would increase the capacity of Colombia to monitor its ecosystems, provide useful information to policy makers, and facilitate scientific research. These include: 1) the establishment of a national center for ecological synthesis that focuses on analyzing existing information; 2) the establishment of an ecological observatory system that collects new information, integrates remote sensing products, and produces near real-time products on key ecological variables; and 3) the creation of new platforms for dialog and action within existing scientific and policy groups

The drivers and impacts of Amazon forest degradation

BACKGROUND: Most analyses of land-use and land-cover change in the Amazon forest have focused on the causes and effects of deforestation. However, anthropogenic disturbances cause degradation of the remaining Amazon forest and threaten their future. Among such disturbances, the most important are edge effects (due to deforestation and the resulting habitat fragmentation), timber extraction, fire, and extreme droughts that have been intensified by human-induced climate change. We synthesize knowledge on these disturbances that lead to Amazon forest degradation, including their causes and impacts, possible future extents, and some of the interventions required to curb them. ADVANCES: Analysis of existing data on the extent of fire, edge effects, and timber extraction between 2001 and 2018 reveals that 0.36 ×106 km2 (5.5%) of the Amazon forest is under some form of degradation, which corresponds to 112% of the total area deforested in that period. Adding data on extreme droughts increases the estimate of total degraded area to 2.5 ×106 km2, or 38% of the remaining Amazonian forests. Estimated carbon loss from these forest disturbances ranges from 0.05 to 0.20 Pg C year−1 and is comparable to carbon loss from deforestation (0.06 to 0.21 Pg C year−1). Disturbances can bring about as much biodiversity loss as deforestation itself, and forests degraded by fire and timber extraction can have a 2 to 34% reduction in dry-season evapotranspiration. The underlying drivers of disturbances (e.g., agricultural expansion or demand for timber) generate material benefits for a restricted group of regional and global actors, whereas the burdens permeate across a broad range of scales and social groups ranging from nearby forest dwellers to urban residents of Andean countries. First-order 2050 projections indicate that the four main disturbances will remain a major threat and source of carbon fluxes to the atmosphere, independent of deforestation trajectories. OUTLOOK: Whereas some disturbances such as edge effects can be tackled by curbing deforestation, others, like constraining the increase in extreme droughts, require additional measures, including global efforts to reduce greenhouse gas emissions. Curbing degradation will also require engaging with the diverse set of actors that promote it, operationalizing effective monitoring of different disturbances, and refining policy frameworks such as REDD+. These will all be supported by rapid and multidisciplinary advances in our socioenvironmental understanding of tropical forest degradation, providing a robust platform on which to co-construct appropriate policies and programs to curb it

The drivers and impacts of Amazon forest degradation

Approximately 2.5 × 10 6 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year −1 ), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year −1 ). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

ecochange: An R-package to derive ecosystem change indicators from freely available earth observation products

1. Spatial resources accessible for the derivation of biodiversity indicators of the class ecosystem structure are sparse and disparate, and their integration into computer algorithms for biodiversity monitoring remains problematic. We describe ecochange as an R-package that integrates spatial analyses with a monitoring workflow for computing routines necessary for biodiversity monitoring. 2. The ecochange comprises three modules for data integration, statistical analysis and graphics. The first module currently downloads and integrates diverse remote sensing products belonging to the essential biodiversity class of structure. The module for statistical analysis calculates RasterStack ecosystem-change representations across areas of interest; this module also allows focusing on species habitats while deriving changes in a variety of indicators, including ecosystem areas, conditional entropy and fractal dimension indices. The graphics module produces level and bar plots that ease the development of indicator reports. 3. Its functionality is described with an example workflow to calculate ecosystem-class areas and conditional entropy across an area of interest contained in the package documentation. 4. We conclude that ecochange features procedures necessary to derive ecosystem structure indicators integrating the retrieval of spatially explicit data with the use of workflows to calculate/visualize biodiversity indicators at the national/regional scales.ecochange: An R-package to derive ecosystem change indicators from freely available earth observation productspublishedVersio

Greening peace in Colombia

As peace consolidates in Colombia, can biodiversity survive development? We discuss challenges and opportunities for integrating forest biodiversity conservation into developing, war-dilapidated economies of post-conflict regions, paving the way for a green economy and climate resilient society

Essential Ecosystem Variables

“Essential Ecosystem Variables” (EEVs) framework: Fundamental interactions among ECVs and EBVs govern the states, processes, and functions of ecosystems