Estimating root zone soil moisture at distant sites using MODIS NDVI and EVI in a semi-arid region of southwestern USA

This study investigates the potential of using Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) to estimate root zone soil moisture at native in-situ measured sites, and at distant sites under the same climatic setting. We obtained in-situ data from Soil Climate Analysis Network (SCAN) sites near the Texas-New Mexico border area, and NDVI and EVI products from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Terra satellite. Results show that soil moisture values of the same depth are highly correlated (r = 0.53 to 0.85) among sites as far as 150 km apart, and that NDVI and EVI are highly correlated at the same site (r = 0.87 to 0.91). Correlation based on raw time series of NDVI and soil moisture is in general higher than that based on deseasonalized time series at every depth. The correlation reaches maximum value when vegetation index (VI) lags soil moisture by 5 to 10 days. NDVI shows a slightly higher correlation with soil moisture than EVI does by using the deseasonalized time series of NDVI and soil moisture. It is found that deseasonalized time series of NDVI and soil moisture are correlated at native sites (r = 0.33 to 0.77), but not at sites where soil moisture is very low. Regression analysis was conducted using deseasonalized time series soil moisture and deseasonalized time series NDVI with a 5-day time lag. Regression models developed at one site and applied to a similar distant site can estimate soil moistures, accounting for 50–88% of the variation in observed soil moistures.     

Habitat associations of an insular Wallacean avifauna: A multi-scale approach for biodiversity proxies

The endemic avifauna of Wallacea is of high conservation significance, but remains poorly studied. Identifying priority conservation areas requires a greater understanding of the habitat associations of these bird communities, and of how spatial scale of analysis can influence the interpretation of these associations. This study aims to determine which proxy habitat measures, at which spatial scales of analysis, can provide useful inferential data on the composition of Wallacean forest avifauna. Research was conducted within the Lambusango forest reserve, South-East Sulawesi, using point count surveys to sample avifauna. Habitat properties were characterised in three ways: broad classification of forest type, canopy remotely-sensed response derived from satellite imagery, and in situ measures of vegetation composition and structure. Furthermore, we examined avifauna–habitat relationships at three spatial scales: area (c.400 ha per sample site), transect (c.10 ha) and point (c.0.2 ha). Results demonstrate that broad forest type classifications at an area scale can help to determine conservation value, indicating that primary and old secondary forests are important for supporting many species with lower ecological tolerances, such as large-bodied frugivores. At the transect-scale, significant congruence occurs between bird community composition and several habitat variables derived from vegetation sampling and satellite imagery, particularly tree size, undergrowth density, and Normalised Difference Vegetation Index (NDVI) values; this highlights the importance small scale habitat associations can have on determining α-diversity. Analysis at the point-scale was ineffective in providing proxy indications for avifauna. These findings should be considered when determining future priority conservation areas for Wallacean avifauna.     

Characterization of spatial variability of soil physicochemical properties and its impact on Rhodes grass productivity

Characterization of soil properties is a key step in understanding the source of spatial variability in the productivity across agricultural fields. A study on a 16 ha field located in the eastern region of Saudi Arabia was undertaken to investigate the spatial variability of selected soil properties, such as soil compaction ‘SC’, electrical conductivity ‘EC’, pH (acidity or alkalinity of soil) and soil texture and its impact on the productivity of Rhodes grass (Chloris gayana L.). The productivity of Rhodes grass was investigated using the Cumulative Normalized Difference Vegetation Index (CNDVI), which was determined from Landsat-8 (OLI) images. The statistical analysis showed high spatial variability across the experimental field based on SC, clay and silt; indicated by values of the coefficient of variation (CV) of 22.08%, 21.89% and 21.02%, respectively. However, low to very low variability was observed for soil EC, sand and pH; with CV values of 13.94%, 7.20% and 0.53%, respectively. Results of the CNDVI of two successive harvests showed a relatively similar trend of Rhodes grass productivity across the experimental area (r = 0.74, p = 0.0001). Soil physicochemical layers of a considerable spatial variability (SC, clay, silt and EC) were utilized to delineate the experimental field into three management zones (MZ-1, MZ-2 and MZ-3); which covered 30.23%, 33.85% and 35.92% of the total area, respectively. The results of CNDVI indicated that the MZ-1 was the most productive zone, as its major areas of 50.28% and 45.09% were occupied by the highest CNDVI classes of 0.97–1.08 and 4.26–4.72, for the first and second harvests, respectively.     

Nonlinear features and complexity patterns of vegetation dynamics in the transition zone of North China

Normalized Difference Vegetation Index (NDVI) has been commonly used to estimate terrestrial vegetation distribution and productivity. In this study, we adopted recurrence quantification analysis (RQA) to investigate the spatial patterns of determinism of the vegetation dynamics ecological-geographical transition zones in North China, especially the differences between transition zone and the surrounding areas. The results indicated that there were obvious regional variances in spatial patterns of RQA indices—determinism, laminarity, entropy, and averaged diagonal line length. Remarkable differences of the determinism of NDVI time series also existed between transition zones and the surrounding areas. Moreover, the correlation analysis between the RQA indices and climatic factors suggested that the determinism of the NDVI time series was nonlinearly affected by hydrothermal conditions. Influenced by vegetation patterns, determinism reached the maximum when the annual precipitation is about 400 mm, which is the lower bound of cultivation and forest distribution, and along the 400 mm isohyet is the area where transition zones locate.     

A novel MODIS algorithm to estimate chlorophyll a concentration in eutrophic turbid lakes

A novel approach was developed to estimate phytoplankton biomass in eutrophic turbid lakes, using MODIS bands designed for land and atmospheric studies. The Baseline Normalized Difference Bloom Index (BNDBI) uses the difference of remote-sensing reflectance (Rrs, sr⁻¹) at 555 nm (band 4) and 645 nm (band 1) after baseline correction using bands at 469 nm and 859 nm: (Rrs′(555) − Rrs′(645))/(Rrs′(555) + Rrs′(645)). BNDBI takes advantage of the Chl-a’s absorption minimum near 572 nm and absorption maximum near 667 nm. Using data from Lake Chaohu, the index showed a strong relationship with Chl-a concentrations in conditions that would normally saturate more sensitive ocean-color sensors. Extensive field measurements were used to calibrate and validate the algorithm with unbiased root-mean-square-error (URMSE) of 47.9% when compared to in situ Rrs data. A reduced sensitivity to atmospheric effects was accomplished by using a baseline correction approach, anchored at 469 nm and 859 nm to correct the radiances at 555 nm and 645 nm. Radiative transfer simulations showed that the algorithm can be applied directly to MODIS Rayleigh-corrected reflectance (Rrc) after adjusting algorithm coefficients (URMSE uncertainty of 56.4% for MODIS Rrc data) for Chl-a concentrations <1000 μg L⁻¹. Comparative analyses showed that the index was resistant to changes in turbidity and organic matter concentrations. Theoretical simulations, image comparisons and spectral analyses demonstrated that the index was robust in a range of complex atmospheric and surface conditions, with different aerosol types, optical thickness (τ_a555), solar/viewing geometry, sun glint and thin clouds. A comparison with other MODIS and MERIS Chl-a algorithms for turbid waters showed that BNDBI provided consistent results with the advantage of using MODIS wavebands that remain unsaturated in high turbidity conditions. The BNDBI opens new possibilities to explore bio-optical dynamics in turbid eutrophic lakes using data from a range of satellite sources.     

Mapping paddy rice areas based on vegetation phenology and surface moisture conditions

Accurate and timely rice mapping is important for food security and environmental sustainability. We developed a novel approach for rice mapping through Combined Consideration of Vegetation phenology and Surface water variations (CCVS). Variation of the Land Surface Water Index (LSWI) in rice fields was relatively smaller than that in other crops fields during the period from tillering to heading dates. Therefore, the ratios of change amplitude of LSWI to 2-band Enhanced Vegetation Index 2 (EVI2) during that period were utilized as the primary metric for paddy rice mapping. This algorithm was applied to map paddy rice fields in southern China using an 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) in 2013. The resultant rice cropping map was consistent with the agricultural census data (r² = 0.8258) and ground truth observations (overall accuracy = 93.4%). Validation with Landsat Thematic Mapper images in test regions also revealed its high accuracy (with overall accuracy of 94.3% and kappa coefficient of 0.86). The proposed CCVS method was more robust to intra-class variability and other related uncertainties compared with other related methods in rice mapping. Its successful application in southern China revealed its efficiency and great potential for further utilization.     

Bioconversion of spent coffee grounds into carotenoids and other valuable metabolites by selected red yeast strains

Spent coffee grounds (SCG) represent the main coffee industry residues with a great potential to be reutilized in various biotechnological processes. In this study, several carotenogenic yeasts strains were exploited for the production of vitamin-enriched biomass, cultivating in SCG-based media. The fermentation was firstly carried out in Erlenmeyer flasks in order to select the best biomass and pigment producer. Among four tested strains, Sporobolomyces roseus showed the highest potential for the accumulation of carotenoids. Maximum pigment concentration and yield was obtained when cultivating in SCG-based media, 12.59 mg l⁻¹ and 1.26 mg g⁻¹, respectively. Comparing both, the batch and the fed-batch cultivation modes, the strategy of sequential addition of pre-concentrated SCG media in the bioreactor gave higher biomass yield (maximum 41 g l⁻¹ during 41–48 h after the beginning of fermentation). Thus, SCG can be considered as potentially promising industrial waste stream for economically feasible production of enriched yeasts biomass.     

Forest cover dynamics analysis and prediction modeling using logistic regression model

Forest cover conversion and depletion are of global concern due to their role in global warming. The present study attempted to study the forest cover dynamics and prediction modeling in Bhanupratappur Forest Division of Kanker district in Chhattisgarh province of India. The study aims to examine and analyze the various explanatory variables associated with forest conversion process and predict forest cover change using logistic regression model (LRM). The forest cover for the periods 1990 and 2000, derived from Landsat TM satellite imagery, was used to predict the forest cover for 2010. The predictive performance of the model was assessed by comparing the model-predicted forest cover with the actual forest cover for 2010. To explain the effects of anthropogenic pressure on forest, this study considered three distance variables viz., distance from forest edge, roads and settlements, and slope position classes as explanatory variables of forest change. The highest regression coefficient (β = −26.892) was noticed in case of distance from forest edge, which signifies the higher probability of forest change in areas that are closer to the forest edges. The analysis showed that forest cover has undergone continuous change between 1990 and 2010, leading to the loss of 107.2 km² of forest area. The LRM successfully predicted the forest cover for the period 2010 with reasonably high accuracy (ROC = 87%).     

Estimating biomass and carbon mitigation of temperate coniferous forests using spectral modeling and field inventory data

Realizing the importance of forest carbon monitoring and reporting in climate change, the present study was conducted to derive spectrally modeled aboveground biomass and mitigation using Landsat data in combination with sampled field inventory data in the coniferous forests of Western Himalaya. After conducting preliminary survey in 2009, 90 quadrats (45 each for calibration and validation) of 0.1 ha were laid in six forest types for recording field inventory data viz. diameter at breast height, height, slope and aspect. Biomass carbon (Mg ha^− 1) was worked out for different forest types and crown density classes (open with 10–40% crown density and closed with > 40% crown density) using recommended volume equations, ratios and factors. Biomass carbon map (aboveground + belowground) was generated for the entire region using geospatial techniques. Normalized difference vegetation index (NDVI) was generated and spectral values were extracted to establish relation (R² = 0.72, p < 0.01) with the field inventory data. The model developed was validated (R² = 0.73, p < 0.01) with 45 sample observations not used earlier for predicting and generating biomass carbon map (2009) for the entire region. The data from field based inventory indicates highest total biomass carbon (171.40, σ ± 23.19) Mg ha^− 1 for Fir–Spruce (closed) which has relatively more mature girth classes and low tree density. This value was found to be significantly higher than other forest types. Lowest biomass carbon was observed for Blue Pine (open) (37.15, σ ± 11.82) Mg ha^− 1. The NDVI values for the entire region ranged from 0 to 0.62 and consequently the spectrally derived aboveground biomass carbon varied from 0 to 600 Mg ha^− 1. The study demonstrates the application of mapping, spectral responses and sampled field inventory for type wise assessment of carbon mitigation in temperate coniferous forests of Himalayas.     

Loss of aboveground forest biomass and landscape biomass variability in Missouri,US

Disturbance regimes and forests have changed over time in the eastern United States. We examined effects of historical disturbance (circa 1813 to 1850) compared to current disturbance (circa 2004 to 2008) on aboveground, live tree biomass (for trees with diameters ≥13 cm) and landscape variation of biomass in forests of the Ozarks and Plains landscapes in Missouri, USA. We simulated 10,000 one-hectare plots using random diameters generated from parameters of diameter distributions limited to diameters ≥13 cm and random densities generated from density estimates. Area-weighted mean biomass density (Mg/ha) for historical forests averaged 116 Mg/ha, ranging from 54 Mg/ha to 357 Mg/ha by small scale ecological subsections within Missouri landscapes. Area-weighted mean biomass density for current forests averaged 82 Mg/ha, ranging from 66 Mg/ha to 144 Mg/ha by ecological subsection for currently forested land. Biomass density of current forest was greater than historical biomass density for only 2 of 23 ecological subsections. Current carbon sequestration of 292 TgC on 7 million ha of forested land is less than half of the estimated historical total carbon sequestration of 693 TgC on 12 million ha. Cumulative tree cutting disturbances over time have produced forests that have less aboveground tree biomass and are uniform in biomass compared to estimates of historical biomass, which varied across Missouri landscapes. With continued relatively low rates of forest disturbance, current biomass per ha will likely increase to historical levels as the most competitive trees become larger in size and mean number of trees per ha decreases due to competition and self-thinning. Restoration of large diameter structure and forested extent of upland woodlands and floodplain forests could fulfill multiple conservation objectives, including carbon sequestration.     

Natural and anthropogenic changes to mangrove distributions in the Pioneer River Estuary (QLD,Australia)

We analyzed a time series of aerial photographs and Landsat satellite imagery of the Pioneer River Estuary (near Mackay, Queensland, Australia) to document both natural and anthropogenic changes in the area of mangroves available to filter river runoff between 1948 and 2002. Over 54 years, there was a net loss of 137 ha (22%) of tidal mangroves during four successive periods that were characterized by different driving mechanisms: (1) little net change (1948–1962); (2) net gain from rapid mangrove expansion (1962–1972); (3) net loss from clearing and tidal isolation (1972–1991); and (4) net loss from a severe species-specific dieback affecting over 50% of remaining mangrove cover (1991–2002). Manual digitization of aerial photographs was accurate for mapping changes in the boundaries of mangrove distributions, but this technique underestimated the total loss due to dieback. Regions of mangrove dieback were identified and mapped more accurately and efficiently after applying the Normalized Difference Vegetation Index (NDVI) to Landsat Thematic Mapper satellite imagery, and then monitoring changes to the index over time. These remote sensing techniques to map and monitor mangrove changes are important for identifying habitat degradation, both spatially and temporally, in order to prioritize restoration for management of estuarine and adjacent marine ecosystems.     

Weight gains of meat goat kids on wheat (Triticum aestivum L.) pastures fertilized at different nitrogen levels

Wheat (Triticum aestivum L.) pastures are increasingly being used for cool-season forages to complement range-based goat production systems in southern USA. Because goats are more selective than cattle, ideal nitrogen (N) fertilizer rates already established for wheat grazed by cattle may be different for goats. Weight gains of Boer X Spanish doe kids (average 17 kg) as well as forage yields and crude protein (CP), acid detergent fiber (ADF) and acid detergent lignin (ADL) concentrations were measured for two winter seasons on replicated wheat paddocks fertilized with 0, 56, 112 and 224 kg N/ha per season in split autumn/spring applications at Stephenville, TX, USA. Animals were stocked in the pasture at 20 head/ha from January to April 2003 (478 mm rainfall from September to March) and 2004 (355 mm rainfall). Available forage ranged from 50 to 200 kg/ha in January and from 2300 to 6300 kg/ha in April in the 0 and 224 kg N/ha paddocks, respectively. Crude protein dry matter (DM) concentration ranged from 25 to 34% (0 and 224 kg N/ha, respectively) in January, but down to 13 and 22% across treatments in April. Average daily gains (ADG) over the 90-day trial were similar both years, 68 g per head per day for the 0 N treatment and undifferentiated among the fertilized paddocks, all near 90 g per head per day. Results indicate that N fertilizer rates above 56 kg/ha per season do not increase ADG/kid, but will increase ADG/ha if stocking rates are adjusted for forage production.     

Survival of rapidly fluctuating natural low winter temperatures by High Arctic soil invertebrates

The extreme polar environment creates challenges for its resident invertebrate communities and the stress tolerance of some of these animals has been examined over many years. However, although it is well appreciated that standard air temperature records often fail to describe accurately conditions experienced at microhabitat level, few studies have explicitly set out to link field conditions experienced by natural multispecies communities with the more detailed laboratory ecophysiological studies of a small number of ‘representative’ species. This is particularly the case during winter, when snow cover may insulate terrestrial habitats from extreme air temperature fluctuations. Further, climate projections suggest large changes in precipitation will occur in the polar regions, with the greatest changes expected during the winter period and, hence, implications for the insulation of overwintering microhabitats. To assess survival of natural High Arctic soil invertebrate communities contained in soil and vegetation cores to natural winter temperature variations, the overwintering temperatures they experienced were manipulated by deploying cores in locations with varying snow accumulation: No Snow, Shallow Snow (30 cm) and Deep Snow (120 cm). Air temperatures during the winter period fluctuated frequently between +3 and −24 °C, and the No Snow soil temperatures reflected this variation closely, with the extreme minimum being slightly lower. Under 30 cm of snow, soil temperatures varied less and did not decrease below −12 °C. Those under deep snow were even more stable and did not decline below −2 °C. Despite these striking differences in winter thermal regimes, there were no clear differences in survival of the invertebrate fauna between treatments, including oribatid, prostigmatid and mesostigmatid mites, Araneae, Collembola, Nematocera larvae or Coleoptera. This indicates widespread tolerance, previously undocumented for the Araneae, Nematocera or Coleoptera, of both direct exposure to at least −24 °C and the rapid and large temperature fluctuations. These results suggest that the studied polar soil invertebrate community may be robust to at least one important predicted consequence of projected climate change.     

How far a protected area contributes to conserve habitat species composition and population structure of endangered African tree species (Benin,West Africa)

The Pendjari Biosphere Reserve located in the Sudanian zone of Bénin, is a protected area well managed, but mainly aimed at wild animal conservation. This study assessed its effectiveness to conserve habitat species composition and population structure of three endangered African tree species: Afzelia africana Sm., Pterocarpus erinaceus Poir. and Khaya senegalensis (Desv.) A. Juss. We randomly sampled 120 plots in the protected and surrounding unprotected habitats by inventorying plant species. For the three target species, we estimated adult and juvenile densities and recorded size classes. According to floristic composition four habitats groups were recognized in relation to human disturbance, vegetation type, and moisture. These were protected savannas, unprotected savannas, old fallows and gallery forests. The estimated adult densities of A. africana were similar between protected (14 ± 1.2 tree/ha) and unprotected savannas (17 ± 0.9 tree/ha) while for P. erinaceus the adult density was significantly higher in protected (12 ± 3.7 tree/ha) than in unprotected savannas (5 ± 1.9 tree/ha). Estimated adult density of K. senegalensis was also significantly higher in protected gallery forest (40 ± 5.8 tree/ha) than in unprotected one (29 ± 4.8 tree/ha). Juvenile densities of A. africana, K. senegalensis and P. erinaceus were higher in protected habitats than in unprotected ones but the difference was not significant. Skewness coefficient indicated that populations of investigated trees were declining in their protected habitats. However, in the case of A. africana and K. senegalensis populations seemed to be mostly threatened in the protected area. We concluded that although the studied protected area is effective to conserve some habitats species compositions, protection is not sufficient to guarantee future conservation of some threatened tree species.     

Acoustic patterns at the Samford Ecological Research Facility in South East Queensland,Australia: The Peri-Urban SuperSite of the Terrestrial Ecosystem Research Network

Acoustic signals that emanate from ecosystems are an important ecological variable which can provide evidence of current ecological condition as well as ecological change over time. The Terrestrial Ecosystem Research Network (TERN) established protocols to record sounds in ten SuperSites distributed throughout Australia with the objective of characterizing the soundscape in a representative landscape in different regions of Australia. This acoustic monitoring system enables a comparison of the soundscapes within and between Australian regions to determine similarities and differences in these landscapes and regions.This research quantifies the soundscape patterns in one of these SuperSites, Samford Ecological Research Facility (TERN-SERF), which is part of the South-East Queensland Peri-Urban SuperSite. An analysis and visualization of patterns in the soundscape was conducted using a continuous acoustic recording collected at TERN-SERF. The recording was made using a Song Meter (SM2) in a representative wooded habitat at TERN-SERF from 1 August to 30 September 2013. The recording was made in 16-bit stereo at 44 kHz and stored in wav file format. The recording was split into 1-minute-long recordings comprising 86,196 records and then sub-sampled at a 30-minute interval, providing 2878 one-minute-long recordings every 1/2 h. Soundscape metrics were computed for each of the two recording intervals. Soundscape power values were computed for each of ten frequency intervals (1–11 kHz) for both the 1-minute and the 30-minute interval recordings. In addition, six acoustic indices were computed from each recording.The acoustics metrics derived from the two sets of recordings (1-minute and 30-minute recording intervals) were examined to determine if they revealed different patterns. Several soundscape metrics were calculated for each recording including ten soundscape power values at 1 kHz frequency intervals and six acoustics indices. The soundscape shows a dynamic but consistent pattern over time of day during the monitoring period, depending on the metric examined. The metrics revealed different soundscape patterns. All soundscape power values at 1 kHz frequency intervals defined the dawn and dusk chorus, some more distinctly than others. Three of six acoustic indices also changed abruptly at the dawn chorus. No significant difference was found when soundscape metrics were compared between the 1-minute (high resolution) and 30-minute (lower resolution) recording intervals. A t-test was used to compare the mean values of ten soundscape power frequency intervals (p = 0.44) and the mean values of six acoustics indices (p = 0.41).Sounds were identified in 180 recordings made at 0530 h, 0600 h and 0630 h in the 1-minute long 30-minute interval recordings each day during the recording period (August and September). Sixty-seven species of birds were identified. Soundscape metrics were correlated with avian species counts and calls by all species using a correlation threshold of r > 0.7. This analysis revealed that soundscape power at the frequency interval 3–4 kHz was correlated with both the number of species (r = − 0.927) and total calls (r = − 0.996) over the three time periods. Three indices, the ADI (r = 0.953, r = 0.709), the AEI (r = 0.978, r = 0.774) and (H) (r = 0.795, r = 0.985) were similarly correlated as was an index derived soundscape power, the Shannon-Weaver Index (r = − 0.997, r = − 0.849). Other indices were correlated (r > 0.7) with only the number of avian species or only the number of calls.This methodology establishes an analysis protocol for analyzing large acoustic data sets, and demonstrates the effectiveness of using acoustic metrics for summarizing and interpreting long-term recordings.     

The emergy of metabolism in different ecosystems under the same environmental conditions in the agro-pastoral ecotone of northern China

The sustainability of ecosystem productivity and rules governing ecosystem development are important topics of scientific research. The emergy approach is an effective method for investigating these topics, especially when used to evaluate systems that have developed under the same environmental conditions, such as climate and soil. In this paper, emergy differences between terrestrial ecosystems were studied in Guyuan County, a region representative of the agro-pastoral ecotone in Hebei Province, China. A combination of field tests and a questionnaire survey were carried out between June and August 2015. The ecosystems studied included natural grassland, artificial grassland, field crops and commercial crops. These four ecosystems were further subdivided into a total of ten ecosystems. Natural grassland was divided into free-grazing and mowed ecosystems; artificial grassland consisted of oat, Chinese leymus and corn silage; field crops included naked oats, flax and wheat; and commercial crops consisted of cabbage and potatoes. The results showed that the rain input of 4.78 × 10¹⁴ seJ/ha/yr constituted the highest renewable natural resource emergy and that the purchased emergy inputs of the ten ecosystems ranged from 3.53 to 147.67 × 10¹⁴ seJ/ha/yr. Natural resource emergy input was the basic power to maintain the ecosystem, and purchased emergy input was the direct cause of the development of the ecosystems. Groundwater was the most important non-renewable purchased energy for the production of economic crops. The emergy investment ratios (EIR) for potatoes (27.81) and cabbage (19.03) were higher than those of the other ecosystems, but mowed and artificial Chinese leymus grassland had the higher emergy self-sufficiency rates (ESR). Natural grassland, artificial Chinese leymus grassland and traditional grain crops had a low environmental load and high sustainability, whereas potatoes and cabbage had a high environmental load and low sustainability. Overall, rain-fed artificial grassland has a high development potential from the perspective of environment and productivity.     

Estimation of gross primary production of irrigated maize using Landsat-8 imagery and Eddy Covariance data

A study was conducted to understand the potential of Landsat-8 in the estimation of gross primary production (GPP) and to quantify the productivity of maize crop cultivated under hyper-arid conditions of Saudi Arabia. The GPP of maize crop was estimated by using the Vegetation Photosynthesis Model (VPM) utilizing remote sensing data from Landsat-8 reflectance (GPP_VPM) as well as the meteorological data provided by Eddy Covariance (EC) system (GPP_EC), for the period from August to November 2015. Results revealed that the cumulative GPP_EC for the entire growth period of maize crop was 1871 g C m⁻². However, the cumulative GPP determined as a function of the enhanced vegetation index – EVI (GPP_EVI) was 1979 g C m⁻², and that determined as a function of the normalized difference vegetation index – NDVI (GPP_NDVI) was 1754 g C m⁻². These results indicated that the GPP_EVI was significantly higher than the GPP_EC (R² = 0.96, P = 0.0241 and RMSE = 12.6%). While, the GPP_NDVI was significantly lower than the GPP_EC (R² = 0.93, P = 0.0384 and RMSE = 19.7%). However, the recorded relative error between the GPP_EC and both the GPP_EVI and the GPP_NDVI was −6.22% and 5.76%, respectively. These results demonstrated the potential of the landsat-8 driven VPM model for the estimation of GPP, which is relevant to the productivity and carbon fluxes.     

Suitable sediment fraction for paleoenvironmental reconstruction and assessment of contaminated coastal areas based on benthic foraminifera: A case study from Augusta Harbour (Eastern Sicily,Italy)

Since the 1990s several studies noticed that, along coastal marine areas, the mean size of benthic foraminifera may be reduced due to heavy metal pollution, even if no biometric studies were carried out to quantify this aspect. The Augusta harbour (Sicily, Italy), is characterized by a strong contamination due to several anthropogenic activities, the most important of which are a petrochemical pole and an important industrial harbour. Taking into account the previous studies carried out in the area, which recorded small-sized foraminifera, the present study compared assemblage composition and faunal parameters in the >125 μm and >63 μm fractions of a sediment core collected in the most polluted sector of Augusta harbour. The aim was to understand if the two fractions have comparable environmental significance providing reliable information on the environmental status. In order to quantify the amount of smaller foraminifera in a community and to determine species loss between size fractions, two new indices are used: the Foraminiferal Size Index (FSI) and the Lost Species Index (LSI). Species richness, diversity and composition of the two assemblages were determined to characterize their structure. The results highlighted great depletion and different composition of the >125 μm assemblage with respect to the >63 μm one, showing a selective loss of particular ecological groups (stress-tolerant infaunal taxa). Also the better correlation of Foraminiferal Number (FN) and H’ index of >63 μm fraction with Polychlorobiphenyls (PCBs), Polycyclic Aromatic Hydrocarbons (PAHs), Barium (Ba) and Mercury (Hg), demonstrated the higher reliability of this size fraction for environmental assessment purposes.