Spatial and temporal scale issues in determining biomass burning regimes in Bolivia and Peru

ATSR-2 active fire data from 1996 to 2000, TRMM VIRS fire counts from 1998 to 2000 and burn scars derived from SPOT VEGETATION ( the Global Burnt Area 2000 product) were mapped for Peru and Bolivia to analyse the spatial distribution of burning and its intra- and inter-annual variability. The fire season in the region mainly occurs between May and October; though some variation was found between the six broad habitat types analysed: desert, grassland, savanna, dry forest, moist forest and yungas (the forested valleys on the eastern slope of the Andes). Increased levels of burning were generally recorded in ATSR-2 and TRMM VIRS fire data in response to the 1997/1998 El Nino, but in some areas the El Nino effect was masked by the more marked influences of socio-economic change on land use and land cover. There were differences between the three global datasets: ATSR-2 under-recorded fires in ecosystems with low net primary productivities. This was because fires are set during the day in this region and, when fuel loads are low, burn out before the ATSR-2 overpass in the region which is between 02.45 h and 03.30 h. TRMM VIRS was able to detect these fires because its overpasses cover the entire diurnal range on a monthly basis. The GBA2000 product has significant errors of commission (particularly areas of shadow in the well-dissected eastern Andes) and omission (in the agricultural zone around Santa Cruz, Bolivia and in north-west Peru). Particular attention was paid to biomass burning in high-altitude grasslands, where fire is an important pastoral management technique. Fires and burn scars from Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM) data for a range of years between 1987 and 2000 were mapped for areas around Parque Nacional Rio Abiseo (Peru) and Parque Nacional Carrasco (Bolivia). Burn scars mapped in the grasslands of these two areas indicate far more burning had taken place than either the fires or the burn scars derived from global datasets. Mean scar sizes are smaller and have a smaller range in size between years the in the study area in Peru (6.6-7.1 ha) than Bolivia (16.9-162.5 ha). Trends in biomass burning in the two highland areas can be explained in terms of the changing socio-economic environments and impacts of conservation. The mismatch between the spatial scale of biomass burning in the high-altitude grasslands and the sensors used to derive global fire products means that an entire component of the fire regime in the region studied is omitted, despite its importance in the farming systems on the Andes.

Assessment of the effect of time and temperature on the availability of residual phosphate in a glasshouse study of four soils using the Olsen method

The Olsen method is an indicator of plant-available phosphorus (P). The effect of time and temperature on residual phosphate in soils was measured using the Olsen method in a pot experiment. Four soils were investigated: two from Pakistan and one each from England (calcareous) and Colombia (acidic). Two levels of residual phosphate were developed in each soil after addition of phosphate by incubation at either 10degreesC or 45degreesC. The amount of phosphate added was based on the P maximum of each soil, calculated using the Langmuir equation. Rvegrass was used as the test crop. The pooled data for the four soils incubated at 10degreesC showed good correlation between Olsen P and dry matter yield or P uptake (r(2) = 0.85 and 0.77, respectively), whereas at 45 degreesC, each soil had its own relationship and pooled data did not show correlation of Olsen P with dry matter yield or P uptake. When the data at both temperatures were pooled, Olsen P was a good indicator of yield and uptake for the English soil. For the Pakistani soils, Olsen P after 45 degreesC treatment was an underestimate relative to the 10 degreesC data and for the Colombian soil it was an overestimate. The reasons for these differences need to be explored further before high temperature incubation can be used to simulate long-term changes in the field.

Comparing sampling needs for variograms of soil properties computed by the method of moments and residual maximum likelihood

It has been generally accepted that the method of moments (MoM) variogram, which has been widely applied in soil science, requires about 100 sites at an appropriate interval apart to describe the variation adequately. This sample size is often larger than can be afforded for soil surveys of agricultural fields or contaminated sites. Furthermore, it might be a much larger sample size than is needed where the scale of variation is large. A possible alternative in such situations is the residual maximum likelihood (REML) variogram because fewer data appear to be required. The REML method is parametric and is considered reliable where there is trend in the data because it is based on generalized increments that filter trend out and only the covariance parameters are estimated. Previous research has suggested that fewer data are needed to compute a reliable variogram using a maximum likelihood approach such as REML, however, the results can vary according to the nature of the spatial variation. There remain issues to examine: how many fewer data can be used, how should the sampling sites be distributed over the site of interest, and how do different degrees of spatial variation affect the data requirements? The soil of four field sites of different size, physiography, parent material and soil type was sampled intensively, and MoM and REML variograms were calculated for clay content. The data were then sub-sampled to give different sample sizes and distributions of sites and the variograms were computed again. The model parameters for the sets of variograms for each site were used for cross-validation. Predictions based on REML variograms were generally more accurate than those from MoM variograms with fewer than 100 sampling sites. A sample size of around 50 sites at an appropriate distance apart, possibly determined from variograms of ancillary data, appears adequate to compute REML variograms for kriging soil properties for precision agriculture and contaminated sites. (C) 2007 Elsevier B.V. All rights reserved.

Morphology, biomass and nutrient status of fine roots of Scots pine (Pinus sylvestris) as influenced by seasonal fluctuations in soil moisture and soil solution chemistry

A field monitoring study was carried out to follow the changes of fine root morphology, biomass and nutrient status in relation to seasonal changes in soil solution chemistry and moisture regime in a mature Scots pine stand on acid soil. Seasonal and yearly fluctuations in soil moisture and soil solution chemistry have been observed. Changes in soil moisture accounted for some of the changes in the soil solution chemistry. The results showed that when natural acidification in the soil occurs with low pH (3.5-4.2) and high aluminium concentration in the soil solution (> 3-10 mg l(-1)), fine root longevity and distribution could be affected. However, fine root growth of Scots pine may not be negatively influenced by adverse soil chemical conditions if soil moisture is not a limiting factor for root growth. In contrast, dry soil conditions increase Scots pine susceptibility to soil acidification and this could significantly reduce fine root growth and increase root mortality. It is therefore important to study seasonal fluctuations of the environmental variables when investigating and modelling cause-effect relationships.

Estimating the spatial scales of regionalized variables by nested sampling, hierarchical analysis of variance and residual maximum likelihood

The variogram is essential for local estimation and mapping of any variable by kriging. The variogram itself must usually be estimated from sample data. The sampling density is a compromise between precision and cost, but it must be sufficiently dense to encompass the principal spatial sources of variance. A nested, multi-stage, sampling with separating distances increasing in geometric progression from stage to stage will do that. The data may then be analyzed by a hierarchical analysis of variance to estimate the components of variance for every stage, and hence lag. By accumulating the components starting from the shortest lag one obtains a rough variogram for modest effort. For balanced designs the analysis of variance is optimal; for unbalanced ones, however, these estimators are not necessarily the best, and the analysis by residual maximum likelihood (REML) will usually be preferable. The paper summarizes the underlying theory and illustrates its application with data from three surveys, one in which the design had four stages and was balanced and two implemented with unbalanced designs to economize when there were more stages. A Fortran program is available for the analysis of variance, and code for the REML analysis is listed in the paper. (c) 2005 Elsevier Ltd. All rights reserved.

Impacts of forestry on nitrogen in upland and lowland catchments: a comparison of the River Severn at Plynlimon in mid-Wales and the Bedford Ouse in south-east England using the INCA Model

The impacts of afforestation at Plynlimon in the Severn catchment, mid-Wales. and in the Bedford Ouse catchment in south-east England are evaluated using the INCA model to simulate Nitrogen (N) fluxes and concentrations. The INCA model represents the key hydrological and N processes operating in catchments and simulates the daily dynamic behaviour as well as the annual fluxes. INCA has been applied to five years of data front the Hafren and Hore headwater sub-catchments (6.8 km(2) area in total) of the River Severn at Plytilimon and the model was calibrated and validated against field data. Simulation of afforestation is achieved by altering the uptake rate parameters in the model. INCA simulates the daily N behaviour in the catchments with good accuracy as well as reconstructing the annual budgets for N release following clearfelling a four-fold increase in N fluxes was followed by a slow recovery after re-afforestation. For comparison, INCA has been applied to the large (8380 km(2)) Bedford Ouse catchment to investigate the impact of replacing 20% arable land with forestry. The reduction in fertiliser inputs from arable farming and the N uptake by the forest are predicted to reduce the N flux reaching the main river system, leading to a 33% reduction in N-Nitrate concentrations in the river water.

Cross-hemispheric transport of Central African biomass burning pollutants: Implications for downwind ozone production

Pollutant plumes with enhanced concentrations of trace gases and aerosols were observed over the southern coast of West Africa during August 2006 as part of the AMMA wet season field campaign. Plumes were observed both in the mid and upper troposphere. In this study we examined the origin of these pollutant plumes, and their potential to photochemically produce ozone (O3) downwind over the Atlantic Ocean. Their possible contribution to the Atlantic O3 maximum is also discussed. Runs using the BOLAM mesoscale model including biomass burning carbon monoxide (CO) tracers were used to confirm an origin from central African biomass burning fires. The plumes measured in the mid troposphere (MT) had significantly higher pollutant concentrations over West Africa compared to the upper tropospheric (UT) plume. The mesoscale model reproduces these differences and the two different pathways for the plumes at different altitudes: transport to the north-east of the fire region, moist convective uplift and transport to West Africa for the upper tropospheric plume versus north-west transport over the Gulf of Guinea for the mid-tropospheric plume. Lower concentrations in the upper troposphere are mainly due to enhanced mixing during upward transport. Model simulations suggest that MT and UT plumes are 16 and 14 days old respectively when measured over West Africa. The ratio of tracer concentrations at 600 hPa and 250 hPa was estimated for 14–15 August in the region of the observed plumes and compares well with the same ratio derived from observed carbon dioxide (CO2) enhancements in both plumes. It is estimated that, for the period 1–15 August, the ratio of Biomass Burning (BB) tracer concentration transported in the UT to the ones transported in the MT is 0.6 over West Africa and the equatorial South Atlantic. Runs using a photochemical trajectory model, CiTTyCAT, initialized with the observations, were used to estimate in-situ net photochemical O3 production rates in these plumes during transport downwind of West Africa. The mid-troposphere plume spreads over altitude between 1.5 and 6 km over the Atlantic Ocean. Even though the plume was old, it was still very photochemically active (mean net O3 production rates over 10 days of 2.6 ppbv/day and up to 7 ppbv/day during the first days) above 3 km especially during the first few days of transport westward. It is also shown that the impact of high aerosol loads in the MT plume on photolysis rates serves to delay the peak in modelled O3 concentrations. These results suggest that a significant fraction of enhanced O3 in mid-troposphere over the Atlantic comes from BB sources during the summer monsoon period. According to simulated occurrence of such transport, BB may be the main source for O3 enhancement in the equatorial south Atlantic MT, at least in August 2006. The upper tropospheric plume was also still photochemically active, although mean net O3 production rates were slower (1.3 ppbv/day). The results suggest that, whilst the transport of BB pollutants to the UT is variable (as shown by the mesoscale model simulations), pollution from biomass burning can make an important contribution to additional photochemical production of O3 in addition to other important sources such as nitrogen oxides (NOx) from lightning.

Plant species diversity, plant biomass and responses of the soil community on abandoned land across Europe: idiosyncracy or above-belowground time lags

The relationship between plant species diversity, productivity and the development of the soil community during early secondary succession on former arable land across Europe is investigated. The enhancement of biomass production due to the increase in initial plant species diversity and the consequent stimulation of soil microbial biomass and abundance of soil invertebrates are examined.

Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.