Responses of surface ozone to future agricultural ammonia emissions and subsequent nitrogen deposition through terrestrial ecosystem changes

With the rising food demands from the future world population, more intense agricultural activities are expected to cause substantial perturbations to the global nitrogen cycle, aggravating surface air pollution and imposing stress on terrestrial ecosystems. Much less studied, however, is how the terrestrial ecosystem changes induced by agricultural nitrogen deposition may modify biosphere–atmosphere exchange and further exert secondary feedback effects on global air quality. Here we examined the responses of surface ozone air quality to terrestrial ecosystem changes caused by year 2000 to year 2050 changes in agricultural ammonia emissions and the subsequent nitrogen deposition by asynchronously coupling between the land and atmosphere components within the Community Earth System Model framework. We found that global gross primary production is enhanced by 2.1 Pg C yr−1, following a 20 % (20 Tg N yr−1) increase in global nitrogen deposition by the end of the year 2050 in response to rising agricultural ammonia emissions. Leaf area index was simulated to be higher by up to 0.3–0.4 m2 m−2 over most tropical grasslands and croplands and 0.1–0.2 m2 m−2 across boreal and temperate forests at midlatitudes. Around 0.1–0.4 m increases in canopy height were found in boreal and temperate forests, and there were ∼0.1 m increases in tropical grasslands and croplands. We found that these vegetation changes could lead to surface ozone changes by ∼0.5 ppbv (part per billion by volume) when prescribed meteorology was used (i.e., large-scale meteorological responses to terrestrial changes were not allowed), while surface ozone could typically be modified by 2–3 ppbv when meteorology was dynamically simulated in response to vegetation changes. Rising soil NOx emissions, from 7.9 to 8.7 Tg N yr−1, could enhance surface ozone by 2–3 ppbv with both prescribed and dynamic meteorology. We, thus, conclude that, following enhanced nitrogen deposition, the modification of the meteorological environment induced by vegetation changes and soil biogeochemical changes are the more important pathways that can modulate future ozone pollution, representing a novel linkage between agricultural activities and ozone air quality.

Unexpected global patterns in plant vulnerability to climate change

Understanding how species will respond to climate change is critically important for managing our ecosystems into the future. However, surprisingly little is known about the distribution of risk based on the actual thermal tolerances of species, especially plants. We used germination records from 776 species to provide a global map of plant warming risk – the difference between maximum germination temperature and the predicted 2070 temperature. We then tested a series of hypotheses about factors associated with high risk. Many of our predictions were overturned. For example, although a great deal of attention has been paid to the risks faced by tropical forests, we found that the biomes most at risk were tropical grasslands, savannas and shrublands. Similarly, while we expected Australian species to have a lower warming risk due to its already variable conditions, our data showed that Australia had the highest average warming risk. Conversely, European species faced the lowest risk, with no plants examined in this study predicted to exceed their upper limits by 2070. Plants from regions with higher seasonality and higher canopy cover had lower warming risk, but the absolute range of annual temperature had no effect on risk. Therefore, the underlying factors contributing to warming risk warrant further examination. Overall, our results highlight that the regions most at risk from warming are not necessarily those with the most warming, but regions where species are closest to their upper limits. More attention needs to be given to high risk tropical environments, especially non-forest tropical environments which face the highest risk. In summary, while much of the world’s biota faces substantial threats from climate change, researchers may be surprised about where the effects are most acute.

50 years publishing on tropical forages - from Tropical Grasslands and Pasturas Tropicales to Tropical Grasslands-Forrajes Tropicales

Preamble of the Volume 9, Issue 3

Responses of surface ozone to future agricultural ammonia emissions and subsequent nitrogen deposition through terrestrial ecosystem changes

With the rising food demands from the future world population, more intense agricultural activities are expected to cause substantial perturbations to the global nitrogen cycle, aggravating surface air pollution and imposing stress on terrestrial ecosystems. Much less studied, however, is how the terrestrial ecosystem changes induced by agricultural nitrogen deposition may modify biosphere-atmosphere exchange and further exert secondary feedback effects on global air quality. Here we examined the responses of surface ozone air quality to terrestrial ecosystem changes caused by 2000-to-2050 changes in agricultural ammonia emission and the subsequent nitrogen deposition by asynchronously coupling between the land and atmosphere components within the Community Earth System Model framework. We found that global gross primary production is enhanced by 2.1 Pg C yr−1 following a 20 % (20 Tg N yr−1) increase in global nitrogen deposition by the end of year 2050 in response to rising agricultural ammonia emission. Leaf area index was simulated to be higher by up to 0.3–0.4 m2 m−2 over most tropical grasslands and croplands, and 0.1–0.2 m2 m−2 across boreal and temperate forests at midlatitudes. Around 0.1–0.4 m increases in canopy height were found in boreal and temperate forests, and ~0.1 m increases in tropical grasslands and croplands. We found that these vegetation changes could lead to surface ozone changes by ~0.5 ppbv when prescribed meteorology was used (i.e., large-scale meteorological responses to terrestrial changes were not allowed), while surface ozone could typically be modified by 2–3 ppbv when meteorology was dynamically simulated in response to vegetation changes. Rising soil NOx emission from 7.9 to 8.7 Tg N yr−1 could enhance surface ozone by 2–3 ppbv with both prescribed and dynamic meteorology. We thus conclude that following enhanced nitrogen deposition, the modification of the meteorological environment induced by vegetation changes and soil biogeochemical changes are the more important pathways that can modulate future ozone pollution, representing a novel linkage between agricultural activities and ozone air quality.

Grass-legume intercropping for sustainability animal production in the tropics.

Seasonal and low forage availability and quality, shrinking of grassland area, and poor grassland management are the main causes of low soil fertility and animal production in tropical grasslands. One sustainable way to overcome the problems is through establishment of grass-legume intercropping in tropical grassland. Results revealed that grass-legume intercropping improved soil health and fertility, forage yield, and stability and reduced weed invasion. Besides, it improves forage nutritive value and animal production. To enhance grass-legume intercropping, the selected grass and legume species should be matched with local environmental conditions followed by good management.

Testing the efficacy of hyperspectral (AVIRIS-NG), multispectral (Sentinel-2) and radar (Sentinel-1) remote sensing images to detect native and invasive non-native trees

Invasive alien species (IAS) threaten tropical grasslands and native biodiversity and impact ecosystem service delivery, ecosystem function, and associated human livelihoods. Tropical grasslands have been dramatically and disproportionately lost to invasion by trees. The invasion continues to move rapidly into the remaining fragmented grasslands impacting various native grassland-dependent species and water streamflow in tropical montane habitats. The Shola Sky Islands of the Western Ghats host a mosaic of native grasslands and forests; of which the grasslands have been lost to exotic tree invasion (Acacias, Eucalyptus and Pines) since the 1950s. The invasion intensities, however, differ between these species wherein Acacia mearnsii and Pinus patula are highly invasive in contrast to Eucalyptus globulus. These disparities necessitate distinguishing these species for effective grassland restoration. Further, these invasive alien trees are highly intermixed with native species, thus requiring high discrimination abilities to native species apart from the non-native species.Here we assess the accuracy of various satellite and airborne remote sensing sensors and machine learning classification algorithms to identify the spatial extent of native habitats and invasive trees. Specifically, we test Sentinel-1 SAR and Sentinel-2 multispectral data and assess high spatial and spectral resolution AVIRIS-NG imagery identifying invasive species across this landscape. Sensor combinations thus include hyperspectral, multispectral and radar data and present tradeoffs in associated costs and ease of procurement. Classification methods tested include Support Vector Machine (SVM), Classification and Regression Trees (CART) and Random Forest (RF) algorithms implemented on the Google Earth Engine platform. Results indicate that AVIRIS-NG data in combination with SVM recover the highest classification skill (Overall −98%, Kappa-0.98); while CART and RF yielded < 90% accuracy. Fused Sentinel-1 and Sentinel-2 produce 91% accuracy, while Sentinel-2 alone yielded 91% accuracy with RF and SVM classification; but only with higher coverage of ground control points. AVIRIS-NG imagery was able to accurately (97%) demarcate the Acacia invasion front while Sentinel-1 and Sentinel-2 data failed. Our results suggest that Sentinel-2 images could be useful for detecting the native and non-native forests with more ground truth points, but hyperspectral data (AVIRIS-NG) permits distinguishing, native and non-native tree species and recent invasions with high precision using limited ground truth points. We suspect that large areas will have to be mapped and assessed in the coming years by conservation managers, NGOs to plan restoration, or to assess the success of restoration activities, and several data procurement and analysis steps may have to be simplified.