An Operational Analysis Ready Radar Backscatter Dataset for the African Continent

Digital Earth Africa is now providing an operational Sentinel-1 normalized radar backscatter dataset for Africa. This is the first free and open continental scale analysis ready data of this kind that has been developed to be compliant with the CEOS Analysis Ready Data for Land (CARD4L) specification for normalized radar backscatter (NRB) products. Partnership with Sinergise, a European geospatial company and Earth observation data provider, has ensured this dataset is produced efficiently in the cloud infrastructure and can be sustained in the long term. The workflow applies radiometric terrain correction (RTC) to the Sentinel-1 ground range detected (GRD) product, using the Copernicus 30 m digital elevation model (DEM). The method is used to generate data for a range of sites around the world and has been validated as producing good results. This dataset over Africa is made available publicly as a AWS public dataset and can be accessed through the Digital Earth Africa platform and its Open Data Cube API. We expect this dataset to support a wide range of applications, including natural resource monitoring, agriculture, and land cover mapping across Africa.

Towards an Improved Large-Scale Gridded Population Dataset: A Pan-European Study on the Integration of 3D Settlement Data into Population Modelling

Large-scale gridded population datasets available at the global or continental scale have become an important source of information in applications related to sustainable development. In recent years, the emergence of new population models has leveraged the inclusion of more accurate and spatially detailed proxy layers describing the built-up environment (e.g., built-area and building footprint datasets), enhancing the quality, accuracy and spatial resolution of existing products. However, due to the consistent lack of vertical and functional information on the built-up environment, large-scale gridded population datasets that rely on existing built-up land proxies still report large errors of under- and overestimation, especially in areas with predominantly high-rise buildings or industrial/commercial areas, respectively. This research investigates, for the first time, the potential contributions of the new World Settlement Footprint—3D (WSF3D) dataset in the field of large-scale population modelling. First, we combined a Random Forest classifier with spatial metrics derived from the WSF3D to predict the industrial versus non-industrial use of settlement pixels at the Pan-European scale. We then examined the effects of including volume and settlement use information into frameworks of dasymetric population modelling. We found that the proposed classification method can predict industrial and non-industrial areas with overall accuracies and a kappa-coefficient of ~84% and 0.68, respectively. Additionally, we found that both, integrating volume and settlement use information considerably increased the accuracy of population estimates between 10% and 30% over commonly employed models (e.g., based on a binary settlement mask as input), mainly by eliminating systematic large overestimations in industrial/commercial areas. While the proposed method shows strong promise for overcoming some of the main limitations in large-scale population modelling, future research should focus on improving the quality of the WFS3D dataset and the classification method alike, to avoid the false detection of built-up settlements and to reduce misclassification errors of industrial and high-rise buildings.

Mapping Perceptions of Violence Across Asian Regions and Countries

Violence is increasing in Asia. However, limited research exists on the prevalence and types of violence across Asian regions and countries; a comprehensive study on a continental-scale in Asia has been understudied. Guided by the World Health Organization’s definition of violence, this study used World Values Survey Wave 7 ( n = 35,435) to map the perceptions of the justifiability of three categories of violence (self-inflicted, interpersonal, collective) with five subtypes (suicide, intimate partner violence against wife, child abuse, violence toward other people, political violence) in six regions and 24 countries in Asia. Findings indicate that perceptions of the justifiability of violence are significantly different across regions in Asia. Perceptions of the justifiability of various types of violence differed across Asian countries. Considering the complexity and diversity of violence across Asian regions and countries, this study may be a cornerstone for violence research in Asia.

Forest tree growth is linked to mycorrhizal fungal composition and function across Europe

Most trees form symbioses with ectomycorrhizal fungi (EMF) which influence access to growth-limiting soil resources. Mesocosm experiments repeatedly show that EMF species differentially affect plant development, yet whether these effects ripple up to influence the growth of entire forests remains unknown. Here we tested the effects of EMF composition and functional genes relative to variation in well-known drivers of tree growth by combining paired molecular EMF surveys with high-resolution forest inventory data across 15 European countries. We show that EMF composition was linked to a three-fold difference in tree growth rate even when controlling for the primary abiotic drivers of tree growth. Fast tree growth was associated with EMF communities harboring high inorganic but low organic nitrogen acquisition gene proportions and EMF which form contact versus medium-distance fringe exploration types. These findings suggest that EMF composition is a strong bio-indicator of underlying drivers of tree growth and/or that variation of forest EMF communities causes differences in tree growth. While it may be too early to assign causality or directionality, our study is one of the first to link fine-scale variation within a key component of the forest microbiome to ecosystem functioning at a continental scale.

Versatile and Targeted Validation of Space-Borne XCO2, XCH4 and XCO Observations by Mobile Ground-Based Direct-Sun Spectrometers

Satellite measurements of the atmospheric concentrations of carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO) require careful validation. In particular for the greenhouse gases CO2 and CH4, concentration gradients are minute challenging the ultimate goal to quantify and monitor anthropogenic emissions and natural surface-atmosphere fluxes. The upcoming European Copernicus Carbon Monitoring mission (CO2M) will focus on anthropogenic CO2 emissions, but it will also be able to measure CH4. There are other missions such as the Sentinel-5 Precursor and the Sentinel-5 series that target CO which helps attribute the CO2 and CH4 variations to specific processes. Here, we review the capabilities and use cases of a mobile ground-based sun-viewing spectrometer of the type EM27/SUN. We showcase the performance of the mobile system for measuring the column-average dry-air mole fractions of CO2 (XCO2), CH4 (XCH4) and CO (XCO) during a recent deployment (Feb./Mar. 2021) in the vicinity of Japan on research vessel Mirai which adds to our previous campaigns on ships and road vehicles. The mobile EM27/SUN has the potential to contribute to the validation of 1) continental-scale background gradients along major ship routes on the open ocean, 2) regional-scale gradients due to continental outflow across the coast line, 3) urban or other localized emissions as mobile part of a regional network and 4) emissions from point sources. Thus, operationalizing the mobile EM27/SUN along these use cases can be a valuable asset to the validation activities for CO2M, in particular, and for various upcoming satellite missions in general.

Multi-proxy evidence of Caribbean-sourced marine incursions in the Neogene of Western Amazonia, Brazil

The timing of continental-scale marine flooding events in Western Amazonia during the Neogene is still an unsolved question. Despite broad proxy-based evidence of such events, the pathways and duration of late Miocene marine incursions remain controversial. We provide coupled calcareous and organic microfossil and geochemical data from six onshore cores from Neogene sequences of the Solimões Basin, Brazil. Our records support minor marine influence in the early Miocene (23.0, 21.1, 18.6, and 16.3 Ma), middle Miocene (14.9, 13.7, and 12.9 Ma) and early Pliocene (4.7, 4.2–4.1, and 3.8 Ma), and conspicuous marine incursions in the late Miocene (11.1–8.8 Ma) suggested by the consistent presence of salinity-indicative microfossils and geochemical data. Our findings challenge the view of major marine incursions in the early and middle Miocene in the studied area. We propose for the first time a new late Miocene incursion (LMI) event as the main marine flooding event in Western Amazonia during the Neogene. These onshore records are compared with three offshore cores from the Atlantic and Pacific Oceans. The similarity between microfossil assemblages of the Solimões Basin and the Caribbean Sea, and evidence of increased runoff from the Orinoco river drainage system, strongly suggest the Caribbean Sea as the primary source area of the marine incursions, supporting a Venezuelan seaway. We further show for the first time the potential linkage between Neogene marine incursions (mainly the LMI) into the Solimões Basin and major disturbances in the global carbon cycle.

Environmental drivers of autumn migration departure decisions in midcontinental mallards

Background The timing of autumn migration in ducks is influenced by a range of environmental conditions that may elicit individual experiences and responses from individual birds, yet most studies have investigated relationships at the population level. We used data from individual satellite-tracked mallards (Anas platyrhynchos) to model the timing and environmental drivers of autumn migration movements at a continental scale. Methods We combined two sets of location records (2004–2007 and 2010–2011) from satellite-tracked mallards during autumn migration in the Mississippi Flyway, and identified records that indicated the start of long-range (≥ 30 km) southward movements during the migration period. We modeled selection of departure date by individual mallards using a discrete choice model accounting for heterogeneity in individual preferences. We developed candidate models to predict the departure date, conditional on daily mean environmental covariates (i.e. temperature, snow and ice cover, wind conditions, precipitation, cloud cover, and pressure) at a 32 × 32 km resolution. We ranked model performance with the Bayesian Information Criterion. Results Departure was best predicted (60% accuracy) by a “winter conditions” model containing temperature, and depth and duration of snow cover. Models conditional on wind speed, precipitation, pressure variation, and cloud cover received lower support. Number of days of snow cover, recently experienced snow cover (snow days) and current snow cover had the strongest positive effect on departure likelihood, followed by number of experienced days of freezing temperature (frost days) and current low temperature. Distributions of dominant drivers and of correct vs incorrect prediction along the movement tracks indicate that these responses applied throughout the latitudinal range of migration. Among recorded departures, most were driven by snow days (65%) followed by current temperature (30%). Conclusions Our results indicate that among the tested environmental parameters, the dominant environmental driver of departure decision in autumn-migrating mallards was the onset of snow conditions, and secondarily the onset of temperatures close to, or below, the freezing point. Mallards are likely to relocate southwards quickly when faced with snowy conditions, and could use declining temperatures as a more graduated early cue for departure. Our findings provide further insights into the functional response of mallards to weather factors during the migration period that ultimately determine seasonal distributions.

The Decline, Fall, and Rise of a Large Urban Colonising Bird

ContextThe process of urbanisation results in dramatic landscape changes with long-lasting and sometimes irreversible consequences for the biota. Urban sensitive species can be eliminated from the landscape, while urban tolerant species can persist in or colonise the changed environment. ObjectivesHere we used historical atlas data to examine the changing distribution of the Australian Brush-turkey, a recent urban colonising species, at continental and city scales, and the changing land use in urban areas occupied by the species. MethodsWe assessed changes at the continental scale from 1839-2019. We then assessed colonisation of the cities of Sydney and Brisbane, located 900 km apart, over the period 1960-2019. At the city scale, we quantified the changing land use within Brush-turkey occupied areas over time using classification of satellite imagery. ResultsThe Brush-turkey range has shifted over the last century, with the species receding from the western and southwestern proportions of their range, while expanding in the northwest. Areas occupied in both cities have expanded, with recently colonised areas containing less vegetation and more developed land. ConclusionsOur results confirm that Brush-turkeys are successfully colonising urban areas, including major cities, and are likely to continue moving into urban areas, despite declines elsewhere in their natural range. This study highlights that species which were locally extirpated from urban areas and thought to be an unlikely candidate for recolonisation can adapt to human modified habitats; successful expansion is likely to be associated with urban greening and legal protection from human persecution.