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Satellite remote sensing provides a wealth of information about environmental factors that influence malaria transmission cycles and human populations at risk. Long-term observations facilitate analysis of climate–malaria relationships, and high-resolution data can be used to assess the effects of agriculture, urbanization, deforestation, and water management on malaria. New sources of very-high-resolution satellite imagery and synthetic aperture radar data will increase the precision and frequency of observations. Cloud computing platforms for remote sensing data combined with analysis-ready datasets and high-level data products have made satellite remote sensing more accessible to nonspecialists. Further collaboration between the malaria and remote sensing communities is needed to develop and implement useful geospatial data products that will support global efforts toward malaria control, elimination, and eradication.

Multiple hypotheses predict how gradients of nutrient availability, plant biomass, and temperature shape trophic pyramids. We aim to disentangle the simultaneous influence of those factors and their indirect effects on trophic structure and individual trophic levels. Location: United States. Time period: 2017. Major taxa studied: Invertebrates. Methods: To examine differences in trophic pyramid shape and abundance within trophic levels and across ecological gradients, we conducted 54 standardized surveys of invertebrate communities in North American grasslands. We tested for the direct and indirect effects of plant biomass, temperature, sodium (Na), other essential elements (e.g. N, P, and K), and toxic heavy metals, (e.g. Ar and Pb) in plant tissue on both individual trophic levels, and trophic pyramid shape, estimated as the community trophic mean (CTM). Results: Plant sodium increased CTM, indicating that high plant sodium concentrations are associated with top-heavy invertebrate trophic pyramids. Sites with higher plant biomass had higher proportions of herbivores compared to higher trophic levels. Finally, increasing temperature resulted in more top-heavy trophic pyramids. Overall, plant biomass, temperature, and plant chemistry directly and indirectly affected the abundances within different trophic levels, highlighting the complexity of factors regulating trophic structure. Main conclusions: Trophic structure of grassland invertebrate communities is strongly influenced by plant sodium, plant biomass, and to a lesser extent, temperature. Grasslands occupy 30% of the Earth’s terrestrial surface and are an imperiled ecosystem due to conversion to row crop agriculture. As biogeochemistry and temperature in the Anthropocene are increasingly modified, our results have considerable implications for the trophic structure of future grassland communities.

Activity density (AD), the rate that an individual taxon or its biomass moves through the environment, is used both to monitor communities and quantify the potential for ecosystem work. The Abundance Velocity Hypothesis posited that AD increases with aboveground net primary productivity (ANPP) and is a unimodal function of temperature. Here we show that, at continental extents, increasing ANPP may have nonlinear effects on AD: increasing abundance, but decreasing velocity as accumulating vegetation interferes with movement. We use 5 yr of data from the NEON invertebrate pitfall trap arrays including 43 locations and four habitat types for a total of 77 habitat–site combinations to evaluate continental drivers of invertebrate AD. ANPP and temperature accounted for one-third to 92% of variation in AD. As predicted, AD was a unimodal function of temperature in forests and grasslands but increased linearly in open scrublands. ANPP yielded further nonlinear effects, generating unimodal AD curves in wetlands, and bimodal curves in forests. While all four habitats showed no AD trends over 5 yr of sampling, these nonlinearities suggest that trends in AD, often used to infer changes in insect abundance, will vary qualitatively across ecoregions.

The latest collection (C6) of MODIS data provides several algorithmic improvements and calibration adjustments that correct for sensor degradation, theoretically making the C6 MODIS products more accurate compared to previous collections. C6 adjustments also introduce several improvements in the vegetation index (VI) retrieval algorithms. With these improvements, we expect only minor differences between data from Terra and Aqua, but significantly different results between C5 and C6. In this paper, we investigate three different MODIS products to determine the extent that improvements made to C6 influence the overall trend results for time series between 2001 and 2017. We focus on these three products specifically, both to allow for a comparison of vegetation index products—NDVI and EVI from MOD13C1, and NDVI and EVI calculated based on surface reflectance from MCD43C4—and also to gain an understanding of the improvements on an entirely different product from the same sensor, namely Land Surface Temperature (LST) from MOD11C2. For the MCD43C4 dataset, we find that 17.9% and 16.4% of EVI and NDVI pixels, respectively, display trend discordance between C5 and C6. For the MOD13C1 vegetation indices, we found comparable rates of trend discordance between C5 and C6: 18.5% and 17.4% for the EVI and NDVI pixels, respectively. For both products the greatest changes between C5 and C6 are an overall increase in pixels exhibiting a significant greening trend and an overall decline in pixels exhibiting a significant browning trend. Moreover, the largest differences between C5 and C6 for the NDVI and EVI data appear in cropland areas and in regions with relatively little human influence. In the Land Surface Temperature product (MOD11C2), the discordance between C5 and C6 is much lower: only 3.2% of day and 5.0% of night LST trends exhibited discordance between C5 and C6. We analyze the complementary results of vegetation index and land surface temperature trends and demonstrate that combining the results from different products observed at different portions of the electromagnetic spectrum—but linked through the biogeophysical processes of surface energy balance—allows us to portray change with more confidence than when relying on vegetation index data alone.

Plant elemental content can vary up to 1,000-fold across grasslands, with implications for the herbivores the plants feed. We contrast the regulation, in grasses and forbs, of 12 elements essential to plants and animals (henceforth plant-essential), 7 essential to animals but not plants (animal-essential) and 6 with no known metabolic function (nonessential). Four hypotheses accounted for up to two thirds of the variation in grass and forb ionomes across 54 North American grasslands. Consistent with the supply-side hypothesis, the plant-essential ionome of both forbs and grasses tracked soil availability. Grass ionomes were more likely to harvest even nonessential elements like Cd and Sr. Consistent with the grazing hypothesis, cattle-grazed grasslands also accumulated a handful of metals like Cu and Cr. Consistent with the NP-catalysis hypothesis, increases in the macronutrients N and P in grasses were associated with higher densities of cofactors like Zn and Cu. The plant-essential elements of forbs, in contrast, consistently varied as per the nutrient-dilution hypothesis—there was a decrease in elemental parts per million with increasing local carbohydrate production. Combined, these data fit a working hypothesis that grasses maintain lower elemental densities and survive on nutrient-poor patches by opportunistically harvesting soil nutrients. In contrast, nutrient-rich forbs use episodes of high precipitation and temperature to build new carbohydrate biomass, raising leaves higher to compete for light, but diluting the nutrient content in every bite of tissue. Herbivores of forbs may thus be particularly prone to increases in pCO2 via nutrient dilution.

The urban heat island (UHI) effect is a global problem that is likely to grow as a result of urban population expansion. Multiple studies conclude that green spaces and waterbodies can reduce urban heat islands. However, previous studies often treat urban green spaces (UGSs) as static or limit the number of green spaces investigated within a city. Cognizant of these shortcomings, Landsat derived vegetation and land surface temperature (LST) metrics for 80 urban green spaces in Puebla, Mexico, over a 34-year (1986–2019) and a 20-year (2000–2019) period were studied. To create a photo library, 73 of these green spaces were visited and the available land cover types were recorded. Green spaces with Indian laurel were found to be much greener and vegetation index values remained relatively stable compared to green spaces with mixed vegetation cover. Similarly, green spaces with large waterbodies were cooler than those without water. These results show that larger green spaces were significantly cooler (p &lt, 0.01) and that size can explain almost 30% of temperature variability. Furthermore, green spaces with higher vegetation index values were significantly cooler (p &lt, 0.01), and the relationship between greenness and temperature strengthened over time.

Humans have been changing the environment word-wide. Central Asia is a great example of a region that is strongly affected by human (anthropogenic) related activities. Political and economic transformations that have been occurring throughout the region have also been strongly affecting the environment. As a result, unprecedented changes have occurring in the land-use and -cover dynamics, as well as in water use and water availability for crops and human. Anthropogenic changes in Central Asia have significant consequences to the environment and human well-being. This chapter focuses on characterizing anthropogenic signatures in Central Asia, addressing their adverse consequences to the population and the environment of Central Asia. Sections address the anthropogenic dust emission associated with human activities, anthropogenic water use, and human growth. The anthropogenic dust emission is reconstructed by taking into account the changes in the land-cover and land use that have been caused by various human activities, including the drying up of the Aral Sea. The latter is a well-known human made disaster that has a profound impact on the entire region. Drastic changes have been occurring in the water use. The population dynamic causes additional problems. We investigated the rate of change in the intensity of the stable average lights product between 1991 and 2000. While the total percentage of lit land increased (3.1–3.4%) between 1991 and 2000, almost all lit areas in Kazakhstan declined in night light intensity. The only areas with increasing nightlights are some of the core urban areas, the Kenkiyak oil fields south of Aktobe and another oil field to the north of Kyzylorda.

Evidence for global insect declines mounts, increasing our need to understand underlying mechanisms. We test the nutrient dilution (ND) hypothesis—the decreasing concentration of essential dietary minerals with increasing plant productivity—that particularly targets insect herbivores. Nutrient dilution can result from increased plant biomass due to climate or CO 2 enrichment. Additionally, when considering long-term trends driven by climate, one must account for large-scale oscillations including El Niño Southern Oscillation (ENSO), North Atlantic Oscillation (NAO), and Pacific Decadal Oscillation (PDO). We combine long-term datasets of grasshopper abundance, climate, plant biomass, and end-of-season foliar elemental content to examine potential drivers of abundance cycles and trends of this dominant herbivore. Annual grasshopper abundances in 16- and 22-y time series from a Kansas prairie revealed both 5-y cycles and declines of 2.1–2.7%/y. Climate cycle indices of spring ENSO, summer NAO, and winter or spring PDO accounted for 40–54% of the variation in grasshopper abundance, mediated by effects of weather and host plants. Consistent with ND, grass biomass doubled and foliar concentrations of N, P, K, and Na—nutrients which limit grasshopper abundance—declined over the same period. The decline in plant nutrients accounted for 25% of the variation in grasshopper abundance over two decades. Thus a warming, wetter, more CO 2 -enriched world will likely contribute to declines in insect herbivores by depleting nutrients from their already nutrient-poor diet. Unlike other potential drivers of insect declines—habitat loss, light and chemical pollution—ND may be widespread in remaining natural areas.

Aim: In ectotherms, gradients of environmental temperature can regulate metabolism, development and ultimately fitness. The thermal adaptation hypothesis assumes that thermoregulation is costly and predicts that more thermally variable environments favour organisms with wider thermal ranges and thermal limits (i.e., critical thermal minima and maxima, CTmin and CTmax) which track environmental temperatures. We test the thermal adaptation hypothesis at two biological levels of organization, the community and species level. Location: Continental USA. Time period: May–August 2016 and May–August 2017. Major taxa studied: Ants (Hymenoptera:Formicidae). Methods: We used ramping assays to measure CTmax and C Tmin for 132 species of North American ants across 31 communities spanning 15.7° of latitude. Results: Ants were cold tolerant in cooler environments particularly at the community level where CTmin was positively correlated with the maximum monthly temperature (CTmin = 0.24Tmax − 0.4 ; R2 = .39, p < .001). In contrast, most ant communities included some highly thermophilic species, with the result that CTmax did not covary with environmental temperature means or extremes. Consequently, we found no evidence that thermally variable environments supported ant communities with broader thermal ranges. We found a strong phylogenetic signal in CTmax but not CTmin. Species level responses paralleled community data, where maximum monthly temperatures positively correlated with species CTmin but not CTmax, which was significantly lower in subterranean species. Main conclusions: Our results suggest a large fraction of continental trait diversity in CTmax and CTmin can be found in a given ant community, with species with high CTmax widely distributed regardless of environmental temperature. Species level analyses found the importance of local microclimate and seasonality in explaining thermal tolerances. Frequent invariance in CTmax of insects at a large scale might be caused by (a) local adaptations to a site's microclimates and (b) species acclimation potential, both of which cannot be accounted for with mean annual temperatures.

Evaluation of the standardized precipitation index (SPI) dataset published monthly in the National Oceanic and Atmospheric Administration/National Centers for Environmental Information (NOAA/NCEI) climate divisional database revealed that drought frequency is being mischaracterized in climate divisions across the United States. The 3- and 6-month September SPI values were downloaded from the database for all years between 1931 and 2019; the SPI was also calculated for the same time scales and span of years following the SPI method laid out by NOAA/NCEI. Drought frequency is characterized as the total number of years that the SPI fell below −1. SPI values across 1931–90, the calibration period cited by NOAA/NCEI, showed regional patterns in climate divisions that are biased toward or away from drought, according to the average values of the SPI. For both time scales examined, the majority of the climate divisions in the central, Midwest, and northeastern United States showed negative averages, indicating bias toward drought, whereas climate divisions in the western United States, the northern Midwest, and parts of the Southeast and Texas had positive averages, indicating bias away from drought. The standard deviation of the SPI also differed from the expected value of 1. These regional patterns in the NCEI’s SPI values are the result of a different (sliding) calibration period, 1895–2019, instead of the cited standardized period of 1931–90. The authors recommend that the NCEI modify its SPI computational procedure to reflect the best practices identified in the benchmark papers, namely, a fixed baseline period.

We analyzed trends in and linkages between 16 years of MODIS land surface temperature data and 15 years of MODIS annual land cover data across drylands in Greater Central Asia and three subregions (Central Asia Core, Drylands East Asia, and Middle East) as well as 24 nations and administrative subunits. The spatial resolution of the analyses was 0.05°, roughly 5 km. We found that a large fraction of the drylands of Greater Central Asia has experienced significant changes in one or more aspects of the thermal regime. Significantly warmer nights were found in 19 of 24 political entities, where greater than 10% of their area was affected. However, these changes are distributed geographically in large patches without clear linkage to land cover type. These findings point to the need for further analysis using finer spatial resolution data to understand recent changes in the land surface dynamics across Greater Central Drylands.

We investigate where bottom-up and top-down control regulates ecological communities as a mechanism linking ecological gradients to the geography of consumer abundance and biomass. We use standardized surveys of 54 North American grasslands to test alternate hypotheses predicting 100-fold shifts in the biomass of four common grassland arthropod taxa—Auchenorrhyncha, sucking herbivores, Acrididae, chewing herbivores, Tettigoniidae, omnivores, and Araneae, predators. Bottom-up models predict that consumer biomass tracks plant quantity (e.g. productivity and standing biomass) and quality (nutrient content) and that ectotherm access to food increases with temperature. Each of the focal trophic groups responded differently to these drivers: the biomass of sucking herbivores and omnivores increased with plant biomass; that of chewing herbivores tracked plant quality; and predator biomass did not depend on plant quality, plant quantity or temperature. The Exploitation Ecosystem Hypothesis is a top-down hypothesis that predicts a shift from resource limitation of herbivores when plant production is low, to predator limitation when plant production is high. In grasslands where spider biomass was low, herbivore biomass increased with plant biomass, whereas bottom-up structuring was not evident when spiders were abundant. Furthermore, neither predator biomass nor trophic position (via stable isotope analysis) increased with plant biomass, suggesting predators themselves are top-down limited. Stable isotope analysis revealed that trophic position of the chewing herbivore and omnivore increased significantly with plant biomass, suggesting these groups increased scavenging and meat consumption in grasslands with higher carbohydrate availability. Taken together, our snapshot sampling documents gradients of food web structure across 54 grasslands, consistent with multiple hypotheses of bottom-up and top-down regulation.

The extraction of phenological events in forest and agriculture commonly relies on Vegetation Indices (VI) composed by visible and near infrared bands from satellite images. However, the textural information playing an important role in image fusion, image classification and change detection is commonly ignored. In this study, high-throughput images collected from an Unmanned Aerial Vehicle (UAV) platform during the growth stages of summer maize were used to identify the Tasseling Date (TD) based on both spectral and textural information. The spectral and textural information were extracted using various VI and the Gray Level Co-occurrence Matrix (GLCM), respectively. The results showed that the Normalized Green Blue Difference Index (NGBDI), and the Green Blue Difference Index (GBDI) of VI and the Contrast Information (Contrast) of GLCM performed better than other variables. A new index was generated by integrating spectral and textural information using the Improved Adaptive Feature Weighting Method (IAFWM), and then the TDs were identified for each plot. The Root Mean Square Error (RMSE) of new index was 5.77 days and it was the lowest among all variables. The potential ability of more advanced machine learning and deep learning in integrating the spectral and textural information should be investigated.

Relationships between land use and water quality are complex with interdependencies, feedbacks, and legacy effects. Most river water quality studies have assessed catchment land use as areal coverage, but here, we hypothesize and test whether land use intensity – the inputs (fertilizer, livestock) and activities (vegetation removal) of land use – is a better predictor of environmental impact. We use New Zealand (NZ) as a case study because it has had one of the highest rates of agricultural land intensification globally over recent decades. We interpreted water quality state and trends for the 26 years from 1989 to 2014 in the National Rivers Water Quality Network (NRWQN) – consisting of 77 sites on 35 mostly large river systems. To characterize land use intensity, we analyzed spatial and temporal changes in livestock density and land disturbance (i.e., bare soil resulting from vegetation loss by either grazing or forest harvesting) at the catchment scale, as well as fertilizer inputs at the national scale. Using simple multivariate statistical analyses across the 77 catchments, we found that median visual water clarity was best predicted inversely by areal coverage of intensively managed pastures. The primary predictor for all four nutrient variables (TN, NOx, TP, DRP), however, was cattle density, with plantation forest coverage as the secondary predictor variable. While land disturbance was not itself a strong predictor of water quality, it did help explain outliers of land use–water quality relationships. From 1990 to 2014, visual clarity significantly improved in 35 out of 77 (34∕77) catchments, which we attribute mainly to increased dairy cattle exclusion from rivers (despite dairy expansion) and the considerable decrease in sheep numbers across the NZ landscape, from 58 million sheep in 1990 to 31 million in 2012. Nutrient concentrations increased in many of NZ's rivers with dissolved oxidized nitrogen significantly increasing in 27∕77 catchments, which we largely attribute to increased cattle density and legacy nutrients that have built up on intensively managed grasslands and plantation forests since the 1950s and are slowly leaking to the rivers. Despite recent improvements in water quality for some NZ rivers, these legacy nutrients and continued agricultural intensification are expected to pose broad-scale environmental problems for decades to come.

Urban area expansion is happening at much faster rates in Asian and African cities than elsewhere in the world. This study uses multi-temporal Landsat images to map the urban extent of six small to large cities in West Africa at four different time steps from the early 1970s–2010. The selected cities are Kumasi of Ghana, Daloa of Cote d’Ivoire, Abuja and Kano in Nigeria, Kindia of Guinea, and Ouagadougou of Burkina Faso. All cities revealed significant urban growth in both urban area and population; however, it was apparent that there was a lot of variability in urban area development. Exponential urban growth rates in the cities were measured as ranging between 0.026 and 0.077, with allometric scaling factors matching those of other countries.

Tropical cyclones are natural events that transform into natural disasters as they approach and reach land. In 2017 alone, tropical cyclones caused an estimated $215 billion in damage. While MODIS data are regularly used in the analysis of hurricanes and typhoons, damage studies typically focus on just a few events without providing a comprehensive overview and comparison across events. The MODIS record is now sufficiently long to enable standardization in time, allowing us to extend previously developed disturbance methodology and to remove dependency on land cover datasets. We apply this new approach to detect the impact of both droughts and hurricanes on the four largest Caribbean islands since 2001. We find that the percentage of disturbed land on the four islands varies from approximately 0–50% between 2001 and 2017, with the highest percentages coinciding with major droughts in Cuba, and Hurricane Maria in Puerto Rico. We demonstrate that (1) Hurricane Maria resulted in significant disturbance across 50% of Puerto Rico (4549 km2), and (2) gradual recovery started about 2.5 months after the hurricane hit. While our approach focuses on the identification of damage arising from hurricanes, it is also capable of identifying the damage from droughts. This approach ultimately enables a better understanding of the combined effects of these two natural hazards across island landscapes.

Sugar and sodium are essential nutrients to above- and below-ground consumers. Unlike other properties of ecological communities such as abundance and richness, we know relatively little about nutritional geography-the sources and supply rates of nutrients, and how and why they vary across communities and ecosystems. Towards a remedy, we present a suite of hypotheses for how sodium and sugary exudate availability should vary for a common omnivore-the ants-and test them using a survey of 53 North American grasslands. We do so by running transects of salt and sugar baits and inferring the magnitude of environmental supplies as the inverse of their use as exogenous baits. We then use estimates of potential drivers of the availability of salt and sugary exudates-plant and soil nutrients, and bioclimatic variables-to test the best predictors of sodium and salt use by ant communities. Beyond a baseline of ant activity, salt use increased as an inverse of the amount of sodium in an ecosystem's plant tissue, but not its soils. Plant sodium varied by two orders of magnitude in grasslands across 16° latitude. This suggests that plant exudates are an important source of sodium for grassland consumers. The three drivers that best predict exogenous sugar use by ants all point to factors constraining sugar production: net above-ground productivity, how far the community is into that year's growing season (both reflecting the rates of photosynthesis) and, intriguingly, the potassium content of plant tissue, which is likely linked to exudate production via plant turgor. These data suggest that ants and other consumers across a range of grasslands and climate vary significantly in the demand and supply of sugar and salt. This nutritional geography ultimately arises from gradients of climate and biogeochemistry with implications for the geography of plant-consumer interactions.

In an era of rapid climate change, and with it concern over insect declines, we used two theories to predict 20-yr changes in 34 North American ant communities. The ecosystems, from deserts to hardwood forests, were first surveyed in the 1990s. When resurveyed in 2016-2017, they averaged 1°C warmer with 200 g C·m-2 ·yr-1 higher plant productivity. Ant colony abundance changed from -49% to +61%. Consistent with Thermal Performance Theory, colony abundance increased with temperature increases

As the world's population is projected to reach 9.7 billion by 2050, large and small cities will continue to expand. There are few studies investigating how the size of cities affects air pollution. Carbon monoxide (CO), a precursor of ozone and a by-product of incomplete combustion, is a common air pollutant. The major sources of CO in the US urban areas are motor vehicles. Here we examined the scaling relation of CO concentrations over major US metropolitan statistical areas (MSAs) using Measurement Of Pollution in The Troposphere (MOPITT) surface CO retrievals and National Emissions Inventory (NEI) data. We found significant power-law scaling relationships between CO and population (r2 of 0.30 for MOPITT average CO concentration and r2 of 0.71 for NEI total CO emission). We found decreasing CO trends from 2000 to 2015 using MOPITT and EPA CO ground measurements. Sublinear scaling relationships (scaling coefficient β < 1) suggest that larger MSAs are more combustion-efficient in terms of CO emissions. We found a weaker scaling relation and smaller scaling coefficient from MOPITT CO concentrations than from NEI total CO emission data. This pattern may be attributed to the differences between the two CO datasets: annual average of monthly MOPITT CO concentration at 1° by 1° spatial resolution versus the NEI annual CO emissions compiled from emission inventories and estimated from mobile source emissions models. Future research is needed to investigate the capability of using satellite observations to study scaling relations between air pollutants and population.

Consumer activity—the rate that individuals move through and discover items in their environment—can constrain population interactions and ecosystem services. We introduce a model that assumes consumer activity is co-limited by the abundance and velocity of consumers, which in turn are constrained by two global drivers: net primary productivity (NPP) and environmental temperature, respectively. We test it with data from a recent study showing how arthropod activity decreases with latitude and elevation. The maximum discovery rates (discoveries per day) of these ectotherms increased linearly with NPP and accounted for the observed latitudinal gradient in activity. The mean temperature of the warmest month in contrast had no consistent effect on activity. An ecosystem's NPP, which provides carbon to build individuals and sugars to fuel them, can thus be an important constraint on the activity of its ectotherm consumers.