Changes In Vegetation Properties Research Articles

Stability in time and consistency between atmospheric corrections: Assessing the reliability of Sentinel-2 products for biodiversity monitoring in tropical forests

Earth observation satellite imagery is increasingly accessible, and has become a key component for vegetation mapping and monitoring. Sentinel-2 satellites acquire optical images with five days’ revisit frequency, which is an important feature to increase the probability of acquisition with reasonable cloud cover in tropical regions. Regular and reliable satellite observations open perspectives for the monitoring of vegetation properties and biodiversity. Atmospheric correction methods (ACMs) producing bottom-of-atmosphere (BOA) reflectance are critical to ensure temporal consistency of higher-level products and optimal sensitivity to changes in vegetation properties. Still their application in tropical regions remains challenging due to complex atmospheric issues. This study aims at performing ACM inter-comparison in the context of tropical forest monitoring. We produced BOA reflectance for a set of Sentinel-2 acquisitions corresponding to a forested area in Cameroon, using four atmospheric correction methods: Sen2cor, MAJA, Overland and LaSRC. We selected five successive acquisitions with moderate to no cloud cover, and computed a set of spectral indices and spectral diversity metrics in order to compare the consistency of these products through time, under the hypothesis that they should remain stable over a short period. We also assessed the agreement between atmospheric correction methods. Two spatial extents were used for the computation of spectral diversity metrics to assess the robustness of the data-driven processes applied to compute spectral diversity. We found that the choice of an ACM did have a significant impact on BOA reflectance and higher-level products. In the visible domain, Overland and LaSRC produced consistent BOA reflectance values, while MAJA and Sen2Cor showed strong variability which could not be explained by changes in surface properties. This directly influenced the temporal consistency of NDVI. Yet, the influence on the temporal consistency for EVI and NDWI was moderate. Spectral diversity metrics were consistent through time for all methods, but to a lesser degree than vegetation indices. When comparing the mean values over the period considered, vegetation indices were stable across methods, but not diversity metrics. Spatial context changes had an impact on the Shannon index, but not on Bray-Curtis dissimilarity. These results suggest that the choice of ACM has major potential implications for tropical forest monitoring.

Modeling the short-term fire effects on vegetation dynamics and surface energy in southern Africa using the improved SSiB4/TRIFFID-Fire model

Abstract. Fire causes abrupt changes in vegetation properties and modifies flux exchanges between land and atmosphere at subseasonal to seasonal scales. Yet these short-term fire effects on vegetation dynamics and surface energy balance have not been comprehensively investigated in the fire-coupled vegetation model. This study applies the SSiB4/TRIFFID-Fire (the Simplified Simple Biosphere Model coupled with the Top-down Representation of Interactive Foliage and Flora Including Dynamics with fire) model to study the short-term fire impact in southern Africa. Specifically, we aim to quantify how large impacts fire exerts on surface energy through disturbances on vegetation dynamics, how fire effects evolve during the fire season and the subsequent rainy season, and how surface-darkening effects play a role besides the vegetation change effects. We find fire causes an annual average reduction in grass cover by 4 %–8 % for widespread areas between 5–20∘ S and a tree cover reduction by 1 % at the southern periphery of tropical rainforests. The regional fire effects accumulate during June–October and peak in November, the beginning of the rainy season. After the fire season ends, the grass cover quickly returns to unburned conditions, while the tree fraction hardly recovers in one rainy season. The vegetation removal by fire has reduced the leaf area index (LAI) and gross primary productivity (GPP) by 3 %–5 % and 5 %–7 % annually. The exposure of bare soil enhances surface albedo and therefore decreases the absorption of shortwave radiation. Annual mean sensible heat has dropped by 1.4 W m−2, while the latent heat reduction is small (0.1 W m−2) due to the compensating effects between canopy transpiration and soil evaporation. Surface temperature is increased by as much as 0.33 K due to the decrease of sensible heat fluxes, and the warming would be enhanced when the surface-darkening effect is incorporated. Our results suggest that fire effects in grass-dominant areas diminish within 1 year due to the high resilience of grasses after fire. Yet fire effects in the periphery of tropical forests are irreversible within one growing season and can cause large-scale deforestation if accumulated for hundreds of years.

Remote Sensing Monitoring of Rice Fields: Towards Assessing Water Saving Irrigation Management Practices

Rice cultivation is one of the largest users of the world’s freshwater resources. The contribution of remote sensing observations for identifying the conditions under which rice is cultivated, particularly throughout the growing season, can be instrumental for water, and crop management. Data from different remote sensing platforms are being used in agriculture, namely to detecting anomalies in crops. This is attempted by calculating vegetation indices (VI) that are based on different vegetation reflectance bands, especially those that rely on the Red, Green, and near-infrared bands, such as the Normalised Difference Vegetation Index (NDVI) or the Green Normalised Difference Vegetation Index (GNDVI). However, particular features of different crops and growing conditions justify that some indices are more adequate than others on a case-to-case basis, according to the different vegetation’s spectral signatures. In recent years, a vegetation index related to the Red Edge reflectance band, the Normalised Difference Red Edge (NDRE) has shown potential to be used as a tool to support agricultural management practices; this edge band, by taking a transition position, is very sensitive to changes in vegetation properties. This work, focusing on the rice crop and the application of different irrigation practices, explores the capability of several VIs calculated from different reflectance bands to detect variability, at the plot scale, in rice cultivation in the Lower Mondego region (Portugal). The remote sensing data were obtained from satellite Sentinel-2A imagery and using a multispectral camera mounted on an Unmanned Aerial System (UAS). By comparing several vegetation indices, we found that NDRE is particularly useful for identifying non-homogeneities in irrigation and crop growth in rice fields. Since few satellite sensors are sensible in the Red Edge band and none has the spatial resolution offered by UAS, this study explores the potential of UAS to be used as a useful support information tool in rice farming and precision agriculture, regarding irrigation, and agronomic management.

Toward a comprehensive understanding of global vegetation CO2 assimilation from space.

Large-scale global analysis of the relationship between growing season solar-induced chlorophyll fluorescence (SIF) and gross primary productivity (GPP), indicated by the GPP/SIF ratio, varied greatly with higher values found in wet-and-cold climate regions and lower values found in hot-and-dry climate regions. Such pattern has been shown to be most influenced by the environmental factor of moisture availability.

Tracking Red Palm Mite Damage in the Western Hemisphere Invasion with Landsat Remote Sensing Data.

Simple SummaryThe red palm mite is a destructive pest for palm trees, impacting their productivity. Detection of their presence is important for management and the prevention of spread. Remote sensing may provide an opportunity to monitor and detect red palm mite presence using readily available land surface remote sensing, such as the Landsat satellite constellation. A study was conducted to determine if Landsat products are able to detect infestations at select sites in the Caribbean, Central, and South America. After a time series analysis, we determined that there are several impediments to detecting red palm mite damage at palm plantations.Red palm mites (Raoiella indica Hirst, Acari: Tenuipalpidae) were first observed in the western hemisphere on the islands and countries surrounding the Caribbean Sea, infesting the coconut palm (Cocos nucifera L.). Detection of invasive pests usually relies upon changes in vegetation properties as result of the pest activity. These changes may be visible in time series of satellite data records, such as Landsat satellites, which have been available with a 16-day repeat cycle at a spatial resolution of 30 m since 1982. Typical red palm mite infestations result in the yellowing of the lower leaves of the palm crown; remote sensing model simulations have indicated that this feature may be better detected using the green normalized difference vegetation index (GNDVI). Using the Google Earth Engine programming environment, a time series of Landsat 5 Thematic Mapper, Landsat 7 Enhanced Thematic Mapper Plus and Landsat 8 Operational Land Imager data was generated for plantations in northern and northeast Brazil, El Salvador, and Trinidad-Tobago. Considering the available studied plantations, there were little or no differences of GNDVI before and after the dates when red palm mites were first revealed at each location. A discussion of possible alternative approaches are discussed related to the limitations of the current satellite platforms.

Disentangling how management affects biomass stock and productivity of tropical secondary forests fallows

A better understanding of biomass production in secondary forests after cultivation is essential for assessing the resilience of slash and burn systems and their capacity to deliver ecosystem services. Biomass production is influenced by management legacies, landscape configuration and soil, but these drivers are rarely studied simultaneously, nor is the role of changes in vegetation properties in linking them to biomass production. We assessed how management legacies affect biomass in secondary forests created by slash and burn in the central Congo Basin, and tested whether changes in productivity could be attributed to changes in stem density, functional diversity, functional identity or soil. Using data from 6452 trees in 96 fallow plots nested in 3 study sites, we looked for the main determinants of aboveground biomass (AGB) of woody vegetation in fallow systems. Next, using a subset of 58 plots in fallow fields aged 5 to 10 years, we used confirmatory path analysis to explore the relations between management history, soil, vegetation properties and biomass productivity. The sampled fallow fields had, on average, 58.4 (±46.2) Mg ha−1 AGB. AGB was positively related to both fallow age and to the proportion of remnant trees in AGB and negatively related to the number of previous cultivation cycles. Biomass productivity varied with the number of previous slash-and-burn cycles, with notable declines in the fourth cycle. The effect of management history was mainly through a reduction in the dominance of fast growing tree species and in the number of regenerating stems, which were also indirectly affected by an increase in C. odorata cover. Soil fertility status and the biomass of remnant trees also modified biomass productivity. Our findings suggest that under the current management intensity the capacity of the slash and burn system to provide important ecosystem functions, such as carbon sequestration, is declining.

Progressively excluding mammals of different body size affects community and trait structure of ground beetles

Mammalian grazing induces changes in vegetation properties in grasslands, which can affect a wide variety of other animals including many arthropods. However, the impacts may depend on the type and body size of these mammals. Furthermore, how mammals influence functional trait syndromes of arthropod communities is not well known.We progressively excluded large (e.g. red deer, chamois), medium (e.g. alpine marmot, mountain hare), and small (e.g. mice) mammals using size‐selective fences in two vegetation types (short‐ and tall‐grass vegetation) of subalpine grasslands. We then assessed how these exclusions affected the community composition and functional traits of ground beetles (Coleoptera, Carabidae), and which vegetation characteristic mediated the observed effects.Total carabid biomass, the activity densities of carabids with specific traits (i.e. small eyes, short wings), the richness of small‐eyed species and the richness of herbivorous species were significantly higher when certain mammals were excluded compared to when all mammals had access, regardless of vegetation type. Excluding large and medium mammals increased the activity density of herbivorous carabid species, but only in short‐grass vegetation. Similarly, excluding large mammals (ungulates) altered carabid species composition in the short‐, but not in the tall‐grass vegetation. All these responses were related to aboveground plant biomass, but not to plant Shannon diversity or vegetation structural heterogeneity.Our results indicate that changes in aboveground plant biomass are key drivers of mammalian grazers’ influence on carabids, suggesting that bottom–up forces are important in subalpine grassland systems. The exclusion of ungulates provoked the strongest carabid response. Our results, however, also highlight the ecological significance of smaller herbivorous mammals. Our study furthermore shows that mammalian grazing not only altered carabid community composition, but also caused community‐wide functional trait shifts, which could potentially have a wider impact on species interactions and ecosystem functioning.

Vegetation effects on impulsive events in the acoustic signature of fires.

Acoustic impulse events have long been used as diagnostics for discrete phenomena in the natural world, including the detection of meteor impacts and volcanic eruptions. Wildland fires display an array of such acoustic impulse events in the form of crackling noises. Exploratory research into the properties of these impulse events revealed information regarding the specific properties of plant material. Unique acoustic frequency bands in the upper end of the sonic spectrum correlated to changes in vegetation properties. The signature of acoustic impulse events as they relate to plant species and plant water stress, were investigated in controlled laboratory combustion experiments. Correlation in the frequency range of 6.0-15.0 kHz was found for both species and water stress, indicating the possibility that a digital filter may be capable of identifying vegetation properties during wildland fire events.