Bare Soil Cover Research Articles

Temporal and spatial variability in soil CO2 efflux in the patagonian steppe

Soil respiration is a major flux of CO2 to the atmosphere. Despite its significance there is a limited understanding of its magnitude, controlling factors and how it varies over time and space in arid ecosystems. We evaluated the temporal pattern of soil CO2 efflux and their response to rain pulses in a patagonian steppe, taking into account the spatial heterogeneity (bare soil and vegetated patches). We measured soil CO2 efflux in bare soil and vegetated patches along the year. We also analyzed physical and chemical soil traits, root density and heterotrophic bacterial count. Soil water content and temperature exhibited seasonal variability and it was larger in bare soil patches than in vegetated patches. Root density, organic matter and phosphorus were higher in vegetated patches than in bare soil. CO2 efflux was 48% higher in vegetated patches than in bare soil patches. Soil CO2 efflux decreased from summer to winter, reaching its maximum value (about 0.6 μmol m2 s−1) in spring. In both patch types, soil CO2 efflux was explained by the interaction between soil temperature and soil water content. Soil CO2 efflux also was positively correlated with soil root density. Bare soil and vegetated patches exhibited distinct response to a rain pulses. Vegetated patches were highly sensitive to rainfall events, generating a large CO2 pulse, returning to previous values after three days. Bare soil CO2 efflux did not exhibit significant changes after a rain pulse. In patagonian arid ecosystems, the seasonal variation in soil respiration is explained mainly by the interaction between soil temperature and water content. Bare soil patches had higher water content but lower root density resulting in lower soil CO2 respiration than vegetated patches. However, at ecosystem level the contribution of bare soil to total soil CO2 efflux was similar to the contribution of vegetated patches because bare soil cover is 65% in the study area. Changes in the number of small rain events as well as changes in plant cover could have large consequences on soil ecology and biochemistry in dry and heterogeneous ecosystems.

Plant Species Composition and Forage Production 14 Yr After Biosolids Application and Grazing Exclusion

This paper examines the effects of a single surface application of biosolids (at 20 dry Mg ha−1) on plant species composition, forage quality and quantity, and C stocks after 14 yr of rest in rangelands of the Central Interior of British Columbia. More than two times the aboveground biomass of grasses and the percent cover of plant litter were found in the biosolids treatment relative to the control, along with reductions in bare soil and microbiotic crust cover. Significantly greater plant uptake of all macronutrients (C, N, P, K, S, Ca, and Mg); most micronutrients (B, Cu, Mn, Mo, and Zn); and Al occurred in the biosolids treatment. P and Cu were the only two nutrients to be more concentrated in the biosolids-treated forage relative to the control forage, while N, Mg, and protein were more concentrated in the control forage. No significant difference in forage digestibility was found between biosolids and control treatments. Bluebunch wheatgrass, the late-seral native grass species, had significantly increased cover and aboveground biomass in the biosolids treatment relative to the control; however, between 2006 and 2016, non-native Kentucky bluegrass had reached > 25% cover in the biosolids plots, perhaps restricting the full recovery of bluebunch wheatgrass. Our findings indicate that biosolids application to ungrazed rangeland can increase long-term forage production and reduce bare soil. However, at our study site biosolids application also led to a long-term shift in the plant community composition away from the late-seral (i.e., bluebunch wheatgrass) trajectory, and the effects of this shift on rangeland health and productivity require further investigation.

Plant community shifts along tree canopy cover gradients in grazed Patagonian Nothofagus antarctica forests and grasslands

Nothofagus antarctica forests at the Chilean Patagonia are valued for both their ecological and livestock production value. Despite their importance, there is not enough information about the understory associated to these forests. Previous studies have reported the dependence of the understory on the light intensity reaching the sward. Thus, our objective was to study the effect of the tree canopy cover on the plant community composition and productivity of the forests´ understory. We established four experimental sites along a 100-km transect covering an area of 700 km2 in Southern Chilean Patagonia. 73 1-m2 metal exclusion cages (quadrats) were randomly distributed along tree cover gradients on the sites. Bare soil, litter and understory cover were registered. Plant botanical composition was also recorded. At the end of the growing season plant biomass was harvested to estimate yield. Species frequency and abundance were analyzed. Species richness and biodiversity were determined. We found 37 species distributed in 20 families. Woody species represented 13.5%, grasses 24.3% and forbs 62.2% of the total. Species richness was higher in grasslands than forests. There was a trend in decreasing biodiversity when increasing tree canopy cover. Differences in yield between grasslands and open forests were not significant. High forage value species presented higher abundance in open forests than grasslands. We conclude that open forests of N. antarctica have higher grazing potential than their associated grasslands. These findings support the facilitation effect of trees over understory species reported previously.

Amplitud forrajera de la hormiga escamolera (Liometopum apiculatum Mayr, Hymenoptera: Formicidae) en una zona semiárida del altiplano zacatecano

En México, la hormiga escamolera (Liometopum apiculatum Mayr) es un recurso natural económicamente importante. Sin embargo, sus colonias son sobre utilizadas. Tanto su hábitat como su actividad forrajera son aspectos poco estudiados. El objetivo de este estudio fue determinar la amplitud forrajera de L. apiculatum y las variables del hábitat que la definen en Villa González Ortega, Zacatecas, México. Durante 2014, se localizaron 31 colonias de L. apiculatum. La amplitud forrajera de la hormiga se determinó mediante la identificación de los caminos de forrajeo, sus distancias desde el nido a los sitios de forrajeo y sus azimuts. Las variables del hábitat que más se asociaron con la amplitud forrajera se determinaron con índices de Frecuencia de observación (Fo), análisis cladístico (AC) y análisis de correspondencia canónica (ACC). La hormiga escamolera forrajeó en un área de tamaño promedio de 1 565.65 ± 535.63 m2 y las variables que más explicaron esta superficie forrajera fueron la presencia de Agave salmiana, Yucca spp., Prosopis spp., Acacia farnesiana, suelo desnudo, material leñoso y cobertura de arbustos. Este estudio, sobre la amplitud forrajera de la hormiga escamolera, proporciona información para el diseño de estrategias de manejo y conservación de sus poblaciones y hábitats en México.

Management Recommendation Generation for Areas Under Forest Restoration Process through Images Obtained by UAV and LiDAR

Evaluating and monitoring forest areas during a restoration process is indispensable to estimate the success or failure of management intervention and to correct the restoration trajectory through adaptive management. However, the field measurement of several indicators in large areas can be expensive and laborious, and establishing reference values for indicators is difficult. The use of supervised classification techniques of high resolution images, combined with an expert system to generate management recommendations, can be considered promising tools for monitoring and evaluating restoration areas. The objective of the present study was to elaborate an expert system of management recommendation generation for areas under restoration, which were monitored by two different remote sensors: UAV (Unmanned Aerial Vehicle) and LiDAR (Light Detection and Ranging). The study was carried out in areas under restoration with about 54 ha and five years of implementation, owned by Fibria Celulose S.A. (recently acquired by Suzano S.A.), in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, near infrared) on UAV and LiDAR data compositions (intensity image, digital surface model, digital terrain model, normalized digital surface model). The monitored restoration indicator entailed land cover separated into three classes: Canopy cover, bare soil and grass cover. The images were classified using the Random Forest (RF) and Maximum Likelihood (ML) algorithms and the area occupied by each land cover classes was calculated. An expert system was developed in ArcGIS to define management recommendations according to the land cover classes, and then we compared the recommendations generated by both algorithms and images. There was a slight difference between the recommendations generated by the different combinations of images and classifiers. The most frequent management recommendation was “weed control + plant seedlings” (34%) for all evaluated methods. The image monitoring methods suggested by this study proved to be efficient, mainly by reducing the time and cost necessary for field monitoring and increasing the accuracy of the generated management recommendations.

Soil moisture estimation with a remotely sensed dry edge determination based on the land surface temperature-vegetation index method

As a crucial parameter in land surface systems, soil moisture plays an important role in surface energy balance studies, environmental detection, and global climate change research. Remotely sensed data have been used for estimating soil moisture through different approaches, which has resulted in many achievements. Previous studies showed that the land surface temperature (LST) vegetation index method (LST-VI method) can obtain surface soil moisture with remote sensing sources, and it is relatively simple and easy to operate at a regional scale. However, one thorny difficulty is the dry edge determination from the LST-VI feature space. In this study, a remote sensing method is proposed to determine the theoretical dry edge from the LST-VI scatter plots, which do not require any ground measured auxiliary data. Based on the surface energy balance principle, this method derived the maximum LSTs for bare soil and full vegetation cover using MODIS products. The air temperature is parameterized by the LST using a semiempirical formula as the theoretical wet edge. The estimated soil moisture is validated by in situ measurements at a comprehensive weather station of Yucheng. The coefficient of determination is ∼0.60, and the root mean square error is about 0.08 m3 / m3. The relevant key parameters in determining the dry edge are also validated from the meteorological observation. The air temperature and net surface shortwave radiation flux all reach a very high level, with an RMSE of 3.75 k and 49.3 W m − 2, respectively. The results demonstrated that the proposed method can derive the accurate dry edge to estimate soil moisture from the remote sensing data, which will provide great help for future studies of soil moisture estimation using remote sensing techniques.

Micro-scale spatial variability in soil heat flux (SHF) in a wine-grape vineyard

In vineyards, hourly soil heat flux (SHF) may account for as much as 30% of net radiation. Therefore, inaccurate estimates of SHF may lead to non-negligible errors when quantifying the surface energy balance. The typical canopy height to width ratio of two along with widely spaced rows (row spacing exceeding canopy height), and leaf biomass concentrated in the upper half of the vine canopy result in variable shading conditions producing sharp, sometimes abrupt, differences in SHF between adjacent points within the interrow space. Drip irrigation, which is also a typical practice in many vineyards in semi-arid regions, adds an additional source of variability in the interrow soil moisture which strongly affects SHF. Lastly, the common practice in Californian wine-grape vineyards to plant cover crop in the interrow, forming two distinct areas below the canopy—bare soil and crop cover, further increases SHF variability in the interrow. This small-scale variability challenges the measurement of SHF in such agrosystems. The objective of the research was to assess the micro-scale (within the interrow between two vine rows) spatial variability in SHF, and to determine which of the three variables—non-uniform (in both space and time) shading patterns, non-uniform surface cover (bare soil vs. cover crop) and non-uniform soil water content (due to the drip irrigation)—is the most significant driver for the local heterogeneity. The variability of incoming solar radiation reaching the ground was found to be the primary source for the spatial and temporal variation of SHF once the vine canopy was fully developed. The water content distribution and the grass cover in the interrow both had minor impacts on the spatial and temporal variation in SHF. It was further found that a transect of five equally distributed sensors across the interrow accurately represented the area-average SHF given by the 11-sensor array, particularly during the growing season.

Evaluating the Met Office Unified Model land surface temperature in Global Atmosphere/Land 3.1 (GA/L3.1), Global Atmosphere/Land 6.1 (GA/L6.1) and limited area 2.2 km configurations

Abstract. A limitation of the Met Office operational data assimilation scheme is that surface-sensitive infrared satellite sounding channels cannot be used during daytime periods where numerical weather prediction (NWP) model background land surface temperature (LST) biases are greater than 2 K in magnitude. The Met Office Unified Model (UM) has a significant cold LST bias in semi-arid regions when compared with satellite observations; a range of UM configurations were assessed with different model resolutions, land surface cover datasets and bare soil parameterisations. UM LST biases were evaluated at global resolution and in a limited area model (LAM) at a 2.2 km resolution over the SALSTICE (Semi-Arid Land Surface Temperature and IASI Calibration Experiment) experimental domain in south-eastern Arizona. This validation is in conjunction with eddy-covariance flux tower measurements. LST biases in the Global Atmosphere/Land 3.1 (GA/L3.1) configuration were largest in the mid-morning with respect to Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (-13.6±2.8 K at the Kendall Grassland site). The diurnal cycle of LST in Global Atmosphere/Land 6.1 (GA/L6.1) showed a significant improvement relative to GA/L3.1 with the cold LST biases reduced to -1.4±2.7 K and -3.6±3.0 K for Terra and Aqua overpasses, respectively. The higher-resolution LAM showed added value over the global configurations. The spatial distribution of the LST biases relative to MODIS and the modelled bare soil cover fraction were found to be moderately correlated (0.61±0.08) during the daytime, which suggests that regions of cold LST bias are associated with low bare soil cover fraction. Coefficients of correlation with the shrub surface fractions followed the same trend as the bare soil cover fraction, although with a less significant correlation (0.36±0.09), and indicated that the sparse vegetation canopies in south-eastern Arizona are not well represented in UM ancillary datasets. The x component of the orographic slope was positively correlated with the LST bias (0.41±0.05 for MODIS Aqua) and identified that regions of cold model LST bias are found on easterly slopes, and regions of warm model LST bias are found on westerly slopes. An overestimate in the modelled turbulent heat and moisture fluxes at the eddy-covariance flux sites was found to be coincident with an underestimate in the ground heat flux.

Land use\u2212land cover changes and Mopani worm harvest in Mangwe District in Plumtree, Zimbabwe

BackgroundMopani worms have been considered a critical food security resource as people living in Mopani woodlands depend on the worms both as a food source and as an income generating resource. These become a readily available substitute if agriculture fails and droughts loom. However the yields from these worms have been dwindling over the years and this has been associated with land use−land cover changes as the worms depend on vegetation. This research sought to investigate the relationship between land use−land cover changes and Mopani worm harvests in Mangwe District in Plumtree from the period 2007 to 2016 in Zimbabwe.MethodsSatellite imagery was collected using LandSat 5 and LandSat 8 satellite and then classified using the Semi-Automatic Classification plugin in Quantum Geographic Information System to identify trees, dams, bare soil and settlements. Thematic maps were then produced and used to quantify extent of Land Use–Land Cover changes in the period from 2007 to 2016. Ground control data was collected using hand held Global Positioning System. Harvests trends (and reasons thereof) were estimated through usage of interviewer administered questionnaires on selected Mopani worm harvesters and harvest data kept by the community leaders.ResultsResults showed that settlements and bare soil cover had greatly increased from 2007 to 2016. There was a significant decline on vegetation cover from 2007 to 2016. There was also decline in the Mopani worm harvest over the years. Reasons for reduction of harvest were cited as deforestation, drought, overharvesting, cooking with lids on and occurrence of veld fires.ConclusionsFindings of this study highlight that land use−land cover changes impacted negatively on Mopani worm harvests over the period 2007 to 2016. It is also of paramount importance to note that major reasons for this decline has been associated with Land Use changes that are associated with human activities. There is need for Natural Resource Conservation Agencies to embark on awareness campaigns to encourage reforestation and also control cutting down of Mopani woodlands. Research needs to be conducted to determine the association between cultural beliefs and Mopani worm conservation and utilisation.

The terrestrial invertebrate fauna of Edge\xf8ya, Svalbard: Arctic landscape community composition reflects biogeography patterns

Colonisation and immigration history is often neglected as a factor when investigating community or species distribution patterns. However, for dynamic systems that are still reacting to large-scale environmental change, such as the retreat of the ice since the last glacial maximum, colonisation history may explain a large amount of the variation between geographically distinct communities. The High Arctic archipelago of Svalbard presents an opportunity to test whether it is possible to observe the effects of large-scale biogeographical patterns on species distribution at landscape scales. Svalbard has one of the best described inventories of the invertebrate fauna in the Arctic. Nonetheless, the majority of the species records originate from the more accessible west coast and the invertebrate fauna of the whole eastern region, including Edgeøya, is virtually unknown. Edgeøya is located at the eastern fringe of the archipelago on the boundary between Palaearctic and Nearctic faunas. It was expected that post-colonisation dispersal within Edgeøya would conceal routes to the archipelago. Samples were obtained from six locations along the coast of Edgeøya between 2009 and 2010. 140 invertebrate species were identified belonging to 69 different genera of which 16 are new records for Svalbard. Most new species present an eastern Palaearctic distribution. Habitat variables (percentage cover of moss, lichen, vascular plant, or bare soil) fail to explain 35.5% of the differences among sites. However, cluster analysis reveals a clear east–west distribution pattern across the island suggesting that pan-Arctic dispersal routes can be identified even at relatively short geographical scales.

Bare soil cover and arbuscular mycorrhizal community in the first montane forest restoration in Central Argentina

Soil erosion affects extensive areas worldwide and must be urgently reduced promoting plant cover and beneficial microorganisms associated with plants, including arbuscular mycorrhizal fungi (AMF). In mountain environments, plant cover is difficult to enhance due to harsh conditions during the dry season and steep slopes. Our objective was to evaluate the percentage of the soil surface covered by plants and the AMF community associated with trees 12.5 years after planting during forest restoration efforts in microsites at different levels of soil degradation. The study was performed in the first montane forest restoration initiative of Central Argentina, where one of the trials consisted of planting Polylepis australis saplings at microsites with different levels of soil degradation: high, intermediate, and low. After 12.5 years, percentage of bare soil cover was significantly reduced by 36 and 37% in the high and intermediate degradation microsites, respectively. Low degradation microsites were initially very low in bare soil and did not significantly change. Mycorrhizal colonization, hyphae, vesicles, arbuscules, AMF diversity, and community structure were similar among microsite types. Percentage of hyphal entry points was higher at microsites with low degradation, number of spores was higher in high and intermediate degradation, and species richness was higher in high degradation. Acaulospora and Glomus were the most abundant genera in all microsites. We conclude that even in the most degraded microsites around 2.8% of the bare soil is covered by vegetation each year and that the arbuscular mycorrhizal community is highly tolerant and adapted to soils with different disturbance types.

Discrimination of Senescent Vegetation Cover from Landsat-8 OLI Imagery by Spectral Unmixing in the Northern Mixed Grasslands

The mixed grasslands of North America are ecosystems with a high volume of dead biomass. This characteristic underlies key ecosystem features such as the rate of carbon and nutrient uptake, heat flux exchange between the surface and the atmosphere, and wildlife habitat. Senescent vegetation is an important forage resource for grazing animals and is related to natural fire frequency and intensity. Therefore, quantitative estimation of photosynthetic vegetation (PV), senescent vegetation (NPV), and bare soil (BS) fraction is important for natural resource management. The authors propose an approach for extracting PV, NPV, and BS endmembers from the normalized difference vegetation index–dead fuel index (NDVI–DFI) plane by using the Landsat-8 imagery. The constrained linear spectral unmixing model was applied to discriminate NPV, PV, and BS using original spectral bands, NDVI–DFI indices, and original spectral plus NDVI and DFI indices. As a comparison, the traditional NDVI–SWIR32 was also investigated. Results showed that the DFI performed better than the SWIR32 to predict NPV from spectral unmixing. Index selection has a significant effect on NPV and BS cover fraction estimation. Choice of equation setup has a significant effect on the PV estimation. The methods proposed here can be applied to grassland ecosystems across the northern mixed grasslands region.

Hydrologic Response of Meadow Restoration the First Year Following Removal of Encroached Conifers

This study examines the hydrologic response of a montane meadow the first winter following restoration by removal of encroached conifers. Hydrologic change was evaluated through statistical comparison of soil moisture and water table depths between the restored meadow, Marian Meadow, and a Control Meadow before and after restoration. Meadow water budgets and durations of water table depths during the growing season were evaluated. Electrical resistivity tomography profiles were collected to improve the spatial interpretation of subsurface water beyond well measurements. The first year following restoration Marian Meadow had a statistically significant increase in volumetric soil moisture content of 4% with depth to the water table decreasing on average by 0.15 m. The water budget for the meadows demonstrated that the hydrologic change following removal of encroached conifers was primarily due to a reduction of vegetation interception capture. Soil evapotranspiration rates in both the Control and Marian Meadows were relatively stable ranging from 268–288 mm/yr with the exception of the year following conifer removal in Marian Meadow with 318 mm/yr. The increase in soil evapotranspiration in the first post restoration year is attributed to loss of vegetation cover and higher proportions of bare soil created from the harvest operations. The duration of post-restoration water table depths during the growing season at Marian Meadow were less than or equal to 0.7 m and 0.3 m for 85 days and 50 days, respectively, indicating hydrologic conditions conducive to meadow vegetation.

Soil nitrogen response to shrub encroachment in a degrading semi-arid grassland

Abstract. Transitions from grass- to shrub-dominated states in drylands by woody plant encroachment represent significant forms of land cover change with the potential to alter the spatial distribution and cycling of soil resources. Yet an understanding of how this phenomenon impacts the soil nitrogen pool, which is essential to primary production in arid and semi-arid systems, is poorly resolved. In this study, we quantified how the distribution and speciation of soil nitrogen, as well as rates of free-living biological nitrogen fixation, changed along a gradient of increasing mesquite (Prosopis velutina Woot.) cover in a semi-arid grassland of the southwestern US. Our results show that site-level concentrations of total nitrogen remain unchanged with increasing shrub cover as losses from inter-shrub areas (sum of grass and bare-soil cover) are proportional to increases in soils under shrub canopies. However, despite the similar carbon-to-nitrogen ratio and microbial biomass of soil from inter-shrub and shrub areas at each site, site-level concentrations of inorganic nitrogen increase with shrub cover due to the accumulation of ammonium and nitrate in soils beneath shrub canopies. Using the acetylene reduction assay technique, we found increasing ratios of inorganic nitrogen to bioavailable phosphorus inhibit rates of biological nitrogen fixation by free-living soil bacteria. Overall, these results provide a greater insight into how grassland-to-shrubland transitions influence the soil N pool through associated impacts on the soil microbial biomass.

Global meta‐analysis of soil‐disturbing vertebrates reveals strong effects on ecosystem patterns and processes

AbstractAimOrganisms that disturb the soil while foraging or creating shelter (ecosystem engineers) can have profound effects on ecosystems. Soil ejecta from these disturbances can enhance surface nutrients and the resulting depressions accrue organic matter and develop into biological hotspots. Here, we describe a global meta‐analysis of studies that assessed the impacts of vertebrate soil disturbance on both biotic and abiotic components of ecosystems.LocationGlobal land surface.Time period1941–2016.Major taxa studiedVertebrates.MethodsAfter conducting a systematic literature search, we quantitatively synthesized the findings of 149 published studies that compared disturbed and undisturbed surfaces. Our meta‐analysis included 64 engineer species, primarily comprised of rodents and a subset of other mammals.ResultsWe found that vertebrate soil disturbance significantly enhanced soil nitrogen (by 77%) and phosphorus (35%), and the productivity (32%) and recruitment (32%) of vascular plants. Disturbances had a greater cover of bare soil (126%) than undisturbed controls, and higher abundances of secondary vertebrates (1,233%), that use pre‐constructed burrows as shelter and foraging grounds. Soil disturbance significantly reduced water run‐off (63%) and the abundance of biocrusts (82%). Soil disturbance effects generally intensified with increasing aridity, and the magnitude of soil disturbance effects was not moderated by the area of the disturbance. Disturbances older than 12 months were more distinct from the surrounding matrix than fresh disturbances. The phylogeny of engineers was unrelated to their ecosystem effects, indicating that the same functionality could readily evolve in different taxa.Main conclusionsIn general, disturbances become localized patches of elevated functioning, providing strong evidence that vertebrate engineers, especially those in drylands, are an important source of environmental heterogeneity.

Monitoring opencast mine restorations using Unmanned Aerial System (UAS) imagery

Open-pit mine is still an unavoidable activity but can become unsustainable without the restoration of degraded sites. Monitoring the restoration after extractive activities is a legal requirement for mine companies and public administrations in many countries, involving financial provisions for environmental liabilities. The objective of this contribution is to present a rigorous, low-cost and easy-to-use application of Unmanned Aerial Systems (UAS) for supporting opencast mining and restoration monitoring, complementing the inspections with very high (<10 cm) spatial resolution multispectral imagery, and improving any restoration documentation with detailed land cover maps. The potential of UAS as a tool to control restoration works is presented in a calcareous quarry that has undergone different post-mining restoration actions in the last 20 years, representing 4 reclaimed stages. We used a small (<2 kg) drone equipped with a multispectral sensor, along with field spectroradiometer measurements that were used to radiometrically correct the UAS sensor data. Imagery was processed with photogrammetric and Remote Sensing and Geographical Information Systems software, resulting in spectral information, vegetation and soil indices, structural information and land cover maps. Spectral data and land cover classification, which were validated through ground-truth plots, aided in the detection and quantification of mine waste dumping, bare soil and other land cover extension. Moreover, plant formations and vegetation development were evaluated, allowing a quantitative, but at the same time visual and intuitive comparison with the surrounding reference systems. The protocol resulting from this research constitutes a pipeline solution intended for the implementation by public administrations and privates companies for precisely evaluating restoration dynamics in an expedient manner at a very affordable budget. Furthermore, the proposed solution prevents subjective interpretations by providing objective data, which integrate new technologies at the service of scientists, environmental managers and decision makers.

Estimating the fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil from MODIS data: Assessing the applicability of the NDVI-DFI model in the typical Xilingol grasslands

Quantitative estimations of the fractional cover of photosynthetic vegetation (fPV), non-photosynthetic vegetation (fNPV) and bare soil (fBS) are critical for soil wind erosion, desertification, grassland grazing, grassland fire, and grassland carbon storage studies. At present, regional and large-scale fPV, fNPV and fBS estimations have been carried out in many areas. However, few studies have used moderate resolution imaging spectroradiometer (MODIS) data to perform large-scale, long-term fPV, fNPV and fBS estimations in the Xilingol grassland of China. The objective of this study was to quantitatively estimate the time series of fPV, fNPV and fBS in the typical grassland region of Xilingol from MODIS image data. Field measurement spectral and coverage data from May and September 2017 were combined with the 8-day composite product (MOD09A1) acquired during 2017. We established an empirical linear model of different non-photosynthetic vegetation indices (NPVIs) and fNPV based on the sample scale. The linear correlation between the dead fuel index (DFI) and fNPV was best (R2 = 0.60, RMSE = 0.15). A normalized difference vegetation index (NDVI)-DFI model based on MODIS data was proposed to accurately estimate the fPV, fNPV and fBS (estimation accuracies of 44%, 71%, and 74%, respectively) in the typical grasslands of Xilingol in China. The fPV, fNPV and fBS values for the typical grassland time series estimated by the NDVI-DFI model were consistent with the phenological characteristics of the grassland vegetation. The results show that the application of the NDVI-DFI model to the Xilingol grassland is reasonable and appropriate, and it is of great significance to the monitoring of soil wind erosion and fires in grasslands.

Opposing Indirect Effects of Domestic Herbivores on Saltmarsh Erosion

Herbivores can sometimes influence the geomorphology of landscapes, particularly in systems dominated by hydrology. Salt marshes deliver globally valuable benefits, including coastal protection, yet they sometimes rapidly erode. Triggers for erosion are often unknown, but livestock grazing is a suspected cause in many regions of the world where agricultural use of saltmarshes is pervasive. To understand the influence of grazing on saltmarsh erosion, we sampled the plant community, soil chemistry and soil mechanical properties along 2–5 creeks in grazed and ungrazed marshes. Erosion was quantified as: (1) the rates of erosion of extracted soil–plant cores in a hydrological flume and (2) the number of erosional break-offs (‘slump blocks’) per creek. We found that domestic herbivores influenced saltmarsh geomorphology via two indirect and opposing pathways: one involving soil mechanical properties and the other mediated by plant traits and bare soil cover, all within a soil physico-chemical environment. The net effect of grazing results in a reduction in saltmarsh lateral erodibility and thus an increase in marsh resilience. Our results highlight the role of herbivores not only as controllers of the flow of energy and materials through the trophic web, but also as modifiers of the abiotic environment. Managers and scientists must remain vigilant to both the obvious direct and the more nuanced indirect pathways, which can influence grazed ecosystems. This study calls for a closer look to the biological side of the equation when assessing biogeomorphic feedbacks and plant–soil–animal interactions.

Forest restoration monitoring through digital processing of high resolution images

Monitoring and evaluating forest restoration projects is a challenge especially in large-scale, but the remote monitoring of indicators with the use of synoptic, multispectral and multitemporal data allows us to gauge the restoration success with more accurately and in small time. The objective of this study was to elaborate and compare methods of remote monitoring of forest restoration using Light Detection and Ranging (LIDAR) data and multispectral imaging from Unmanned Aerial Vehicle (UAV) camera, in addition to comparing the efficiency of supervised classification algorithms Maximum Likelihood (ML) and Random Forest (RF). The study was carried out in a restoration area with about 74 ha and five years of implementation, owned by Fibria Celulose S.A., in the southern region of Bahia State, Brazil. We used images from Canon S110 NIR (green, red, Near Infrared) on UAV and LIDAR data composition (intensity image, Digital Surface Model, Digital Terrain Model, normalized Digital Surface Model). The monitored restoration indicator was the land cover separated in three classes: canopy cover, bare soil and grass cover. The images were classified using the ML and RF algorithms. To evaluate the accuracy of the classifications, the Overall Accuracy (OA) and the Kappa index were used, and the last was compared by Z test. The area occupied by different land cover classes was calculated using ArcGIS and R. The results of OA, Kappa and visual evaluation of the images were excellent in all combinations of the imaging methods and algorithms analyzed. When Kappa values for the two algorithms were compared, RF presented better performance than ML with significant difference, but when sensors (UAV camera and LIDAR) were compared, there were no significant differences. There was little difference between the area occupied by each land cover classes generated by UAV and LIDAR images. The highest cover was generated for canopy cover followed by grass cover and bare soil in all classified images, indicating the need of adaptive management interventions to correct the area trajectory towards the restoration success. The methods employed in this study are efficient to monitor restoration areas, especially on a large scale, allowing us to save time, fieldwork and invested resources.

Estimating green biomass ratio with remote sensing in arid grasslands

It is difficult to estimate green biomass ratio (GBR), the ratio of green aboveground biomass to total aboveground biomass, using common broad-band vegetation indices in arid grasslands due to similar spectral features between bare soil and non-photosynthetic vegetation in near-infrared (NIR) and visible bands. We evaluated the performance of the broad-band RVI (ratio vegetation index), NDVI (normalized difference vegetation index), SAVI (soil-adjusted vegetation index), MSAVI (modified soil-adjusted vegetation index), OSAVI (optimized soil-adjusted vegetation index), NDVIgreen (green normalized difference vegetation index), CI (canopy index), and NCI (normalized canopy index) for GBR estimation in the desert steppe of Inner Mongolia, China. We also explored best narrow-band hyperspectral vegetation indices for GBR estimation using hyperspectral remotely sensed data and GBR measurements during 2009 and 2010 growing seasons in the desert steppe. Broad-band vegetation indices were not suitable for GBR estimation. The best narrow-band vegetation indices used reflectance at 2069 and 2042 nm; particular 1.5 × (R2069 − R2042)/(R2069 + R2042 + 0.5). The index could partially overcome the influence of bare soil cover. It explained 68% of the variance of GBR and dramatically improved GBR estimation accuracy over common broad-band indices. More importantly, the accuracy was not affected by varying bare soil cover. Nevertheless, caution is required for the index application within varying growing seasons. The development of this index is an important resource for future spectral sensors that will permit GBR monitoring at regional scales in arid grasslands. Our results show that remote imagery can monitor GBR in the desert steppe and potentially in many arid grasslands.