Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data

Understanding monthly-to-annual climate variability is essential for adapting to future climate extremes. Key ways to do this are through analysing climate field reconstructions and reanalyses. However, producing such reconstructions can be limited by high production costs, unrealistic linearity assumptions, or uneven distribution of local climate records. Here, we present a machine learning-based non-linear climate variability reconstruction method using a Recurrent Neural Network that is able to learn from existing model outputs and reanalysis data. As a proof-of-concept, we reconstructed more than 400 years of global, monthly temperature anomalies based on sparse, realistically distributed pseudo-station data and show the impact of different training data sets. Our reconstructions show realistic temperature patterns and magnitude reproduction costing about 1 hour on a middle-class laptop. We highlight the method's capability in terms of mean statistics compared to more established methods and find that it is also suited to reconstruct specific climate events. This approach can easily be adapted for a wide range of regions, periods and variables.

Climate impacts on tree-ring stable isotopes across the Northern Hemispheric boreal zone

Boreal regions are changing rapidly with anthropogenic global warming. In order to assess risks and impacts of this process, it is crucial to put these observed changes into a long-term perspective. Summer air temperature variability can be well reconstructed from conifer tree rings. While the application of stable isotopes can potentially provide complementary climatic information over different seasons. In this study, we developed new triple stable isotope chronologies in tree-ring cellulose (δ¹³C_trc, δ¹⁸O_trc, δ²H_trc) from a study site in Canada. Additionally, we performed regional aggregated analysis of available stable isotope chronologies from 6 conifers' tree species across high-latitudinal (HL) and - altitudinal (HA) as well as Siberian (SIB) transects of the Northern Hemispheric boreal zone. Our results show that summer air temperature still plays an important role in determining tree-ring isotope variability at 11 out of 24 sites for δ¹³C_trc, 6 out of 18 sites for δ¹⁸O_trc and 1 out of 6 sites for δ²H_trc. Precipitation, relative humidity and vapor pressure deficit are significantly and consistently recorded in both δ¹³C_trc and δ¹⁸O_trc along HL. Summer sunshine duration is captured by all isotopes, mainly for HL and HA transects, indicating an indirect link with an increase in air and leaf temperature. A mixed temperature-precipitation signal is preserved in δ¹³C_trc and δ¹⁸O_trc along SIB transect. The δ²H_trc data obtained for HL-transect provide information not only about growing seasonal moisture and temperature, but also capture autumn, winter and spring sunshine duration signals. We conclude that a combination of triple stable isotopes in tree-ring studies can provide a comprehensive description of climate variability across the boreal forest zone and improve ecohydrological reconstructions.

Enhancing the structural diversity between forest patches-A concept and real-world experiment to study biodiversity, multifunctionality and forest resilience across spatial scales

Intensification of land use by humans has led to a homogenization of landscapes and decreasing resilience of ecosystems globally due to a loss of biodiversity, including the majority of forests. Biodiversity-ecosystem functioning (BEF) research has provided compelling evidence for a positive effect of biodiversity on ecosystem functions and services at the local (α-diversity) scale, but we largely lack empirical evidence on how the loss of between-patch β-diversity affects biodiversity and multifunctionality at the landscape scale (γ-diversity). Here, we present a novel concept and experimental framework for elucidating BEF patterns at α-, β-, and γ-scales in real landscapes at a forest management-relevant scale. We examine this framework using 22 temperate broadleaf production forests, dominated by Fagus sylvatica. In 11 of these forests, we manipulated the structure between forest patches by increasing variation in canopy cover and deadwood. We hypothesized that an increase in landscape heterogeneity would enhance the β-diversity of different trophic levels, as well as the β-functionality of various ecosystem functions. We will develop a new statistical framework for BEF studies extending across scales and incorporating biodiversity measures from taxonomic to functional to phylogenetic diversity using Hill numbers. We will further expand the Hill number concept to multifunctionality allowing the decomposition of γ-multifunctionality into α- and β-components. Combining this analytic framework with our experimental data will allow us to test how an increase in between patch heterogeneity affects biodiversity and multifunctionality across spatial scales and trophic levels to help inform and improve forest resilience under climate change. Such an integrative concept for biodiversity and functionality, including spatial scales and multiple aspects of diversity and multifunctionality as well as physical and environmental structure in forests, will go far beyond the current widely applied approach in forestry to increase resilience of future forests through the manipulation of tree species composition.

The Spectral Species Concept in Living Color

Biodiversity monitoring is an almost inconceivable challenge at the scale of the entire Earth. The current (and soon to be flown) generation of spaceborne and airborne optical sensors (i.e., imaging spectrometers) can collect detailed information at unprecedented spatial, temporal, and spectral resolutions. These new data streams are preceded by a revolution in modeling and analytics that can utilize the richness of these datasets to measure a wide range of plant traits, community composition, and ecosystem functions. At the heart of this framework for monitoring plant biodiversity is the idea of remotely identifying species by making use of the 'spectral species' concept. In theory, the spectral species concept can be defined as a species characterized by a unique spectral signature and thus remotely detectable within pixel units of a spectral image. In reality, depending on spatial resolution, pixels may contain several species which renders species-specific assignment of spectral information more challenging. The aim of this paper is to review the spectral species concept and relate it to underlying ecological principles, while also discussing the complexities, challenges and opportunities to apply this concept given current and future scientific advances in remote sensing.

rasterdiv-An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow.In this paper, we present a new R package-rasterdiv-to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns.The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

[Development of Decision Aids for Organized Cervical Carcinoma Screening in Germany]

AIM OF THE STUDY

The Federal Joint Committee has decided to introduce organized cervical carcinoma screening in 2020. The present work describes the development of decision aids that will be sent to women in this program.

METHODS

A systematic search for qualitative studies and surveys was conducted to gather information on experiences, attitudes and information needs. Furthermore, we searched for systematic reviews on advantages and disadvantages of screening. An existing decision analysis for cervical carcinoma screening in Germany was used. The designs were subjected to a qualitative test (focus groups with 26 women and 8 expert interviews), to a quantitative user test (online survey n=2,014 women) and to a public hearing.

RESULTS

Most women found the decision aids informative and helpful. The majority would recommend the use of these materials to others. For many women, part of the information was new, although they had been involved in cervical cancer screening for some time. The presentation of the advantages and disadvantages was judged to be balanced. However, 10% changed their attitude towards participation and 70% of women would attend screening.

CONCLUSION

The decision aids found a high acceptance among the users. They can help to reduce knowledge deficits on cervical carcinoma screening and support a informed decision making.

Habitat degradation and indiscriminate hunting differentially impact faunal communities in the Southeast Asian tropical biodiversity hotspot

Habitat degradation and hunting have caused the widespread loss of larger vertebrate species (defaunation) from tropical biodiversity hotspots. However, these defaunation drivers impact vertebrate biodiversity in different ways and, therefore, require different conservation interventions. We conducted landscape-scale camera-trap surveys across six study sites in Southeast Asia to assess how moderate degradation and intensive, indiscriminate hunting differentially impact tropical terrestrial mammals and birds. We found that functional extinction rates were higher in hunted compared to degraded sites. Species found in both sites had lower occupancies in the hunted sites. Canopy closure was the main predictor of occurrence in the degraded sites, while village density primarily influenced occurrence in the hunted sites. Our findings suggest that intensive, indiscriminate hunting may be a more immediate threat than moderate habitat degradation for tropical faunal communities, and that conservation stakeholders should focus as much on overhunting as on habitat conservation to address the defaunation crisis.

An automatable platform for genotoxicity testing of nanomaterials based on the fluorometric γ-H2AX assay reveals no genotoxicity of properly surface-shielded cadmium-based quantum dots

The large number of nanomaterial-based applications emerging in the materials and life sciences and the foreseeable increasing use of these materials require methods that evaluate and characterize the toxic potential of these nanomaterials to keep safety risks to people and environment as low as possible. As nanomaterial toxicity is influenced by a variety of parameters like size, shape, chemical composition, and surface chemistry, high throughput screening (HTS) platforms are recommended for assessing cytotoxicity. Such platforms are not yet available for genotoxicity testing. Here, we present first results obtained for application-relevant nanomaterials using an automatable genotoxicity platform that relies on the quantification of the phosphorylated histone H2AX (γ-H2AX) for detecting DNA double strand breaks (DSBs) and the automated microscope system AKLIDES® for measuring integral fluorescence intensities at different excitation wavelengths. This platform is used to test the genotoxic potential of 30 nm-sized citrate-stabilized gold nanoparticles (Au-NPs) as well as micellar encapsulated iron oxide nanoparticles (FeOx-NPs) and different cadmium (Cd)-based semiconductor quantum dots (QDs), thereby also searching for positive and negative controls as reference materials. In addition, the influence of the QD shell composition on the genotoxic potential of these Cd-based QDs was studied, using CdSe cores as well as CdSe/CdS core/shell and CdSe/CdS/ZnS core/shell/shell QDs. Our results clearly revealed the genotoxicity of the Au-NPs and its absence in the FeOx-NPs. The genotoxicity of the Cd-QDs correlates with the shielding of their Cd-containing core, with the core/shell/shell architecture preventing genotoxicity risks. The fact that none of these nanomaterials showed cytotoxicity at the chosen particle concentrations in a conventional cell viability assay underlines the importance of genotoxicity studies to assess the hazardous potential of nanomaterials.

Tambora 1815 as a test case for high impact volcanic eruptions: Earth system effects

The eruption of Tambora (Indonesia) in April 1815 had substantial effects on global climate and led to the 'Year Without a Summer' of 1816 in Europe and North America. Although a tragic event-tens of thousands of people lost their lives-the eruption also was an 'experiment of nature' from which science has learned until today. The aim of this study is to summarize our current understanding of the Tambora eruption and its effects on climate as expressed in early instrumental observations, climate proxies and geological evidence, climate reconstructions, and model simulations. Progress has been made with respect to our understanding of the eruption process and estimated amount of SO₂ injected into the atmosphere, although large uncertainties still exist with respect to altitude and hemispheric distribution of Tambora aerosols. With respect to climate effects, the global and Northern Hemispheric cooling are well constrained by proxies whereas there is no strong signal in Southern Hemisphere proxies. Newly recovered early instrumental information for Western Europe and parts of North America, regions with particularly strong climate effects, allow Tambora's effect on the weather systems to be addressed. Climate models respond to prescribed Tambora-like forcing with a strengthening of the wintertime stratospheric polar vortex, global cooling and a slowdown of the water cycle, weakening of the summer monsoon circulations, a strengthening of the Atlantic Meridional Overturning Circulation, and a decrease of atmospheric CO₂. Combining observations, climate proxies, and model simulations for the case of Tambora, a better understanding of climate processes has emerged. WIREs Clim Change 2016, 7:569-589. doi: 10.1002/wcc.407 This article is categorized under: 1Paleoclimates and Current Trends > Paleoclimate.

Distal airways are protected from goblet cell metaplasia by diminished expression of IL-13 signalling components

BACKGROUND

Increased mucus production is a critical factor impairing lung function in patients suffering from bronchial asthma, the most common chronic inflammatory lung disease worldwide.

OBJECTIVE

This study aimed at investigating whether goblet cell (GC) metaplasia and mucus production are differentially regulated in proximal and distal airways.

METHODS

Female Balb/c mice were sensitized to ovalbumin (OVA) and challenged with an OVA-aerosol on two consecutive days for 1 week (acute) or 12 weeks (chronic). Real-time RT-PCR analysis was applied on microdissected airways.

RESULTS

In acutely and chronically OVA-challenged mice, GC metaplasia and mucus production were observed in proximal but not in distal airways. In contrast, inflammation reflected by the infiltration of eosinophils and expression of the TH2-type cytokines IL-4 and IL-13 was increased in both proximal and distal airways. Abundance of IL-13Rα1 was lower in distal airways of healthy control mice. Under acute and chronic OVA-exposure, activation of IL-13Rα1-dependent signalling cascade, reflected by Spdef and Foxo3A transcription factors, was attenuated in distal compared to proximal airways.

CONCLUSION AND CLINICAL RELEVANCE

These data indicate that distal airways might be less sensitive to IL-13-induced GC metaplasia and mucus production through lower expression of IL-13Rα1 and attenuated activation of downstream signalling. This might represent a protective strategy to prevent mucus plugging of distal airways and thus impaired ventilation of attached alveoli.

Use of an ecologically relevant modelling approach to improve remote sensing-based schistosomiasis risk profiling

Schistosomiasis is a widespread water-based disease that puts close to 800 million people at risk of infection with more than 250 million infected, mainly in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and the frequency, duration and extent of human bodies exposed to infested water sources during human water contact. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. Since schistosomiasis risk profiling based on remote sensing data inherits a conceptual drawback if school-based disease prevalence data are directly related to the remote sensing measurements extracted at the location of the school, because the disease transmission usually does not exactly occur at the school, we took the local environment around the schools into account by explicitly linking ecologically relevant environmental information of potential disease transmission sites to survey measurements of disease prevalence. Our models were validated at two sites with different landscapes in Côte d'Ivoire using high- and moderate-resolution remote sensing data based on random forest and partial least squares regression. We found that the ecologically relevant modelling approach explained up to 70% of the variation in Schistosoma infection prevalence and performed better compared to a purely pixel-based modelling approach. Furthermore, our study showed that model performance increased as a function of enlarging the school catchment area, confirming the hypothesis that suitable environments for schistosomiasis transmission rarely occur at the location of survey measurements.

Modeling and Validation of Environmental Suitability for Schistosomiasis Transmission Using Remote Sensing

BACKGROUND

Schistosomiasis is the most widespread water-based disease in sub-Saharan Africa. Transmission is governed by the spatial distribution of specific freshwater snails that act as intermediate hosts and human water contact patterns. Remote sensing data have been utilized for spatially explicit risk profiling of schistosomiasis. We investigated the potential of remote sensing to characterize habitat conditions of parasite and intermediate host snails and discuss the relevance for public health.

METHODOLOGY

We employed high-resolution remote sensing data, environmental field measurements, and ecological data to model environmental suitability for schistosomiasis-related parasite and snail species. The model was developed for Burkina Faso using a habitat suitability index (HSI). The plausibility of remote sensing habitat variables was validated using field measurements. The established model was transferred to different ecological settings in Côte d'Ivoire and validated against readily available survey data from school-aged children.

PRINCIPAL FINDINGS

Environmental suitability for schistosomiasis transmission was spatially delineated and quantified by seven habitat variables derived from remote sensing data. The strengths and weaknesses highlighted by the plausibility analysis showed that temporal dynamic water and vegetation measures were particularly useful to model parasite and snail habitat suitability, whereas the measurement of water surface temperature and topographic variables did not perform appropriately. The transferability of the model showed significant relations between the HSI and infection prevalence in study sites of Côte d'Ivoire.

CONCLUSIONS/SIGNIFICANCE

A predictive map of environmental suitability for schistosomiasis transmission can support measures to gain and sustain control. This is particularly relevant as emphasis is shifting from morbidity control to interrupting transmission. Further validation of our mechanistic model needs to be complemented by field data of parasite- and snail-related fitness. Our model provides a useful tool to monitor the development of new hotspots of potential schistosomiasis transmission based on regularly updated remote sensing data.

Ten ways remote sensing can contribute to conservation

In an effort to increase conservation effectiveness through the use of Earth observation technologies, a group of remote sensing scientists affiliated with government and academic institutions and conservation organizations identified 10 questions in conservation for which the potential to be answered would be greatly increased by use of remotely sensed data and analyses of those data. Our goals were to increase conservation practitioners' use of remote sensing to support their work, increase collaboration between the conservation science and remote sensing communities, identify and develop new and innovative uses of remote sensing for advancing conservation science, provide guidance to space agencies on how future satellite missions can support conservation science, and generate support from the public and private sector in the use of remote sensing data to address the 10 conservation questions. We identified a broad initial list of questions on the basis of an email chain-referral survey. We then used a workshop-based iterative and collaborative approach to whittle the list down to these final questions (which represent 10 major themes in conservation): How can global Earth observation data be used to model species distributions and abundances? How can remote sensing improve the understanding of animal movements? How can remotely sensed ecosystem variables be used to understand, monitor, and predict ecosystem response and resilience to multiple stressors? How can remote sensing be used to monitor the effects of climate on ecosystems? How can near real-time ecosystem monitoring catalyze threat reduction, governance and regulation compliance, and resource management decisions? How can remote sensing inform configuration of protected area networks at spatial extents relevant to populations of target species and ecosystem services? How can remote sensing-derived products be used to value and monitor changes in ecosystem services? How can remote sensing be used to monitor and evaluate the effectiveness of conservation efforts? How does the expansion and intensification of agriculture and aquaculture alter ecosystems and the services they provide? How can remote sensing be used to determine the degree to which ecosystems are being disturbed or degraded and the effects of these changes on species and ecosystem functions?

IL-37 requires IL-18Rα and SIGIRR/IL-1R8 to diminish allergic airway inflammation in mice

BACKGROUND

Interleukin (IL) 37 has been described as a negative regulator of innate immunity, as it reduces the activation and cytokine production of different innate immune cells. Recently, results from the CLARA childhood asthma cohort suggested an implication of IL-37 for human asthma pathogenesis. This study aimed to investigate the effects of IL-37 on allergic airway inflammation in a mouse model of experimental asthma.

METHODS

Peripheral blood mononuclear cells (PBMCs) of children were cultured for 48 h (anti-CD3/anti-CD28 stimulation or unstimulated), and IL-37 concentrations in supernatants were determined. Wild-type, IL-18Rα-deficient ((-/-) ), and SIGIRR(-/-) C57BL/6 mice were sensitized to ovalbumin (OVA) and challenged with OVA aerosol to induce acute experimental asthma, and IL-37 was applied intranasally prior to each OVA challenge. Airway hyper-responsiveness (AHR), airway inflammation, cytokine levels in broncho-alveolar lavage fluid, and mucus production were determined.

RESULTS

IL-37 production of human PBMCs was significantly lower in allergic asthmatics vs healthy children. In wild-type mice, intranasal administration of IL-37 ablated allergic airway inflammation as well as cytokine production and subsequently diminished the hallmarks of experimental asthma including mucus hyperproduction and AHR. In contrast, local application of IL-37 produced none of these effects in mice lacking either IL18Rα or SIGIRR/IL-1R8.

CONCLUSIONS

This study demonstrates that IL-37 is able to ablate a TH2 cell-directed allergic inflammatory response and the hallmarks of experimental asthma in mice, suggesting that IL-37 may be critical for asthma pathogenesis. Furthermore, these data suggest a mode of action of IL-37 that involves IL18Rα as well as the orphan receptor SIGIRR/IL-1R8.

Risk profiling of schistosomiasis using remote sensing: approaches, challenges and outlook

BACKGROUND

Schistosomiasis is a water-based disease that affects an estimated 250 million people, mainly in sub-Saharan Africa. The transmission of schistosomiasis is spatially and temporally restricted to freshwater bodies that contain schistosome cercariae released from specific snails that act as intermediate hosts. Our objective was to assess the contribution of remote sensing applications and to identify remaining challenges in its optimal application for schistosomiasis risk profiling in order to support public health authorities to better target control interventions.

METHODS

We reviewed the literature (i) to deepen our understanding of the ecology and the epidemiology of schistosomiasis, placing particular emphasis on remote sensing; and (ii) to fill an identified gap, namely interdisciplinary research that bridges different strands of scientific inquiry to enhance spatially explicit risk profiling. As a first step, we reviewed key factors that govern schistosomiasis risk. Secondly, we examined remote sensing data and variables that have been used for risk profiling of schistosomiasis. Thirdly, the linkage between the ecological consequence of environmental conditions and the respective measure of remote sensing data were synthesised.

RESULTS

We found that the potential of remote sensing data for spatial risk profiling of schistosomiasis is - in principle - far greater than explored thus far. Importantly though, the application of remote sensing data requires a tailored approach that must be optimised by selecting specific remote sensing variables, considering the appropriate scale of observation and modelling within ecozones. Interestingly, prior studies that linked prevalence of Schistosoma infection to remotely sensed data did not reflect that there is a spatial gap between the parasite and intermediate host snail habitats where disease transmission occurs, and the location (community or school) where prevalence measures are usually derived from.

CONCLUSIONS

Our findings imply that the potential of remote sensing data for risk profiling of schistosomiasis and other neglected tropical diseases has yet to be fully exploited.

Disentangling the relative effects of bushmeat availability on human nutrition in central Africa

We studied links between human malnutrition and wild meat availability within the Rainforest Biotic Zone in central Africa. We distinguished two distinct hunted mammalian diversity distributions, one in the rainforest areas (Deep Rainforest Diversity, DRD) containing taxa of lower hunting sustainability, the other in the northern rainforest-savanna mosaic, with species of greater hunting potential (Marginal Rainforest Diversity, MRD). Wild meat availability, assessed by standing crop mammalian biomass, was greater in MRD than in DRD areas. Predicted bushmeat extraction was also higher in MRD areas. Despite this, stunting of children, a measure of human malnutrition, was greater in MRD areas. Structural equation modeling identified that, in MRD areas, mammal diversity fell away from urban areas, but proximity to these positively influenced higher stunting incidence. In DRD areas, remoteness and distance from dense human settlements and infrastructures explained lower stunting levels. Moreover, stunting was higher away from protected areas. Our results suggest that in MRD areas, forest wildlife rational use for better human nutrition is possible. By contrast, the relatively low human populations in DRD areas currently offer abundant opportunities for the continued protection of more vulnerable mammals and allow dietary needs of local populations to be met.

Adding structure to land cover - using fractional cover to study animal habitat use

BACKGROUND

Linking animal movements to landscape features is critical to identify factors that shape the spatial behaviour of animals. Habitat selection is led by behavioural decisions and is shaped by the environment, therefore the landscape is crucial for the analysis. Land cover classification based on ground survey and remote sensing data sets are an established approach to define landscapes for habitat selection analysis. We investigate an approach for analysing habitat use using continuous land cover information and spatial metrics. This approach uses a continuous representation of the landscape using percentage cover of a chosen land cover type instead of discrete classes. This approach, fractional cover, captures spatial heterogeneity within classes and is therefore capable to provide a more distinct representation of the landscape. The variation in home range sizes is analysed using fractional cover and spatial metrics in conjunction with mixed effect models on red deer position data in the Bohemian Forest, compared over multiple spatio-temporal scales.

RESULTS

We analysed forest fractional cover and a texture metric within each home range showing that variance of fractional cover values and texture explain much of variation in home range sizes. The results show a hump-shaped relationship, leading to smaller home ranges when forest fractional cover is very homogeneous or highly heterogeneous, while intermediate stages lead to larger home ranges.

CONCLUSION

The application of continuous land cover information in conjunction with spatial metrics proved to be valuable for the explanation of home-range sizes of red deer.

Role of African protected areas in maintaining connectivity for large mammals

The African protected area (PA) network has the potential to act as a set of functionally interconnected patches that conserve meta-populations of mammal species, but individual PAs are vulnerable to habitat change which may disrupt connectivity and increase extinction risk. Individual PAs have different roles in maintaining connectivity, depending on their size and location. We measured their contribution to network connectivity (irreplaceability) for carnivores and ungulates and combined it with a measure of vulnerability based on a 30-year trend in remotely sensed vegetation cover (Normalized Difference Vegetation Index). Highly irreplaceable PAs occurred mainly in southern and eastern Africa. Vegetation cover change was generally faster outside than inside PAs and particularly so in southern Africa. The extent of change increased with the distance from PAs. About 5% of highly irreplaceable PAs experienced a faster vegetation cover loss than their surroundings, thus requiring particular conservation attention. Our analysis identified PAs at risk whose isolation would disrupt the connectivity of the PA network for large mammals. This is an example of how ecological spatial modelling can be combined with large-scale remote sensing data to investigate how land cover change may affect ecological processes and species conservation.

Oil in the Sahara: mapping anthropogenic threats to Saharan biodiversity from space

Deserts are among the most poorly monitored and understood biomes in the world, with evidence suggesting that their biodiversity is declining fast. Oil exploration and exploitation can constitute an important threat to fragmented and remnant desert biodiversity, yet little is known about where and how intensively such developments are taking place. This lack of information hinders local efforts to adequately buffer and protect desert wildlife against encroachment from anthropogenic activity. Here, we investigate the use of freely available satellite imagery for the detection of features associated with oil exploration in the African Sahelo-Saharan region. We demonstrate how texture analyses combined with Landsat data can be employed to detect ground-validated exploration sites in Algeria and Niger. Our results show that site detection via supervised image classification and prediction is generally accurate. One surprising outcome of our analyses is the relatively high level of site omission errors in Niger (43%), which appears to be due to non-detection of potentially small-scale, temporary exploration activity: we believe the repeated implementation of our framework could reduce the severity of potential methodological limitations. Overall, our study provides a methodological basis for the mapping of anthropogenic threats associated with oil exploitation that can be conducted across desert regions.