Karina Cenciani1, Andre Mancebo Mazzetto2, Daniel Renato Lammel1, Felipe Jose Fracetto2, Giselle Gomes Monteiro Fracetto2, Leidivan Frazao2, Carlos Cerri1 and Brigitte Feigl1

1Centro de Energia Nuclear na Agricultura/Laboratorio de Biogeoquimica Ambiental

2Escola Superior de Agricultura "Luiz de Queiroz"

Brazil

1. Introduction

Amazonia is a natural region formed by the Amazon River Basin and covered by the largest equatorial forest in the world, covering an area of 6,915,000 km2, of which 4,787,000 km2 are in Brazil. Due to the large size and low population density, it is considered to be the best — well preserved Brazilian biome. Amazonian tropical forest soils are supposed to hold high microbial biodiversity, however the human impact has been extensive in the last decades, coupled with uncontrolled wood removal and the concomitant advancement of agricultural frontier (Fearnside, 2005).

Under the current scenario it is notorious the importance of Amazonia to the Brazilian ecosystem and even worldwide. Precisely because of this the images of slash-and-burn of the forest produce a strong impact on the public opinion. More than 60 million hectares were deforested. Of this total an estimated 35 million hectares were replaced by pastures for beef production, one million hectares were occupied with perennial crops, three million hectares with annual crops, and more than 20 million hectares support secondary vegetation called "capoeira" or fallow (Fig. 1).

What’s occurring in the pastures at the Amazonia, as well in other tropical regions is the loss of the productive capacity after 4 to 10 years of use due to overgrazing, invasion of unpalatable weed species, loss of soil fertility and cultivation of inadequate grass species (Fernandes et al., 2002). It is estimated that 30 to 50% of pastures in the Brazilian Amazon are in advanced stage of degradation, giving rise to the fallow sites. In general, the establishment of pastures is done with simple technology and no use of fertilizers. Its maintenance depends almost exclusively on the nutrients contained in the ashes produced during burning of the original vegetation. Fallows also play an essential role for recovery of native species, as it reassimilates part of carbon and nitrogen that were released when slash — and-burn of native vegetation was used (Fernandes et al., 2002; Schroth et al., 2002).

The quality and soil fertility are defined from the point of view of some essential attributes that maintain the agricultural productivity, namely as: soil ability to promote plant growth, water supply and nutrient processing, efficient gases exchange in the atmosphere-soil interface and the activity of micro and macro organisms (Dilly & Nannipieri, 2001). In this context it is highlighted the role of soil microbial biomass (SMB), defined as the living portion of soil organic matter, excluding roots and larger organisms than, approximately, 5000 pm3 (Cenciani et al., 2009).

In recent years many technological advances and the development of new and independent cultivation techniques led microbiologists to explore more precisely the "black box" of soil microbial diversity. This new knowledge is contributing to our better understanding of the distribution and abundance of soil microorganisms, the effect of community structure on ecosystem functioning, the effects of land use changes on microbial communities and hence in the ecosystem.

Traditional methods were usually based on specific cultivation media in laboratory conditions, in which only 1-3% of the soil microbes present conditions for growth. For this reason much research have been developed using generic properties, such as the microorganisms basal respiration, enzymatic activity, mineralization of soil organic matter, among others, that under controlled laboratory conditions represent rough estimates of the metabolic functions of microbial biomass, reflecting its physiology as whole soil community (Ananyeva et al., 2008).

Considered one of the most important "hot spots" in the world, Amazonia has an important role in the discovery of new species of plants, animals and microorganisms, which may be important for the functionality of different ecosystems. However there are limited studies addressing the impacts of land use changes under the Amazonia microbial communities and their functions in the soil. Within this context bacterial and fungal communities, considered the most abundant groups of microorganisms in the soil, can act as important indicators of environmental stresses induced by the use of Amazonian soils.

Soil microbial diversity is usually assessed as species and genetic diversity rather than as structural and functional diversity. However, in terms of soil quality, these two last forms of diversity may be equally important due to the microorganism’s functional redundancy. The importance of functional and catabolic diversity lies in the fact that only based on changes in the genetic diversity; it is not possible to infer whether some functions of soils were lost or not (Mazzetto et al., 2008).

A soil with high redundancy of functions is probably able to maintain well-balanced its ecological processes, even under a disturbance. This approach, defined as resilience, refers to the buffering effects of external disturbances to the ecosystem. In a soil system the reduction of microbial diversity can be an important indicator of the loss of resilience and, consequently, the soil quality. The abundance of some species of microorganisms seems not to be as important as the maintenance of their genetic and functional diversities. This is because the abundance reflects more immediately the short-term microbial fluctuation, while the diversity reveals the balance between the number of microorganisms and the functional domains in the soil (Kennedy, 1999; Lavelle, 2000).

The main objective of our chapter is to describe the relationship between the genetic and functional diversity approaches to study the microbial ecology and the impact of different land uses under soil microorganisms in Amazonia.

Fatihah Suja’

Universiti Kebangsaan Malaysia Malaysia

1. Introduction

Nitrification is a two step process namely ammoniacal oxidation and nitrite oxidation. Oxidation of ammonium to nitrite is carried out by autotrophic bacterium mainly Nitrosomonas (e. g. N. europaea, N. oligocarbogenes) and Nitrosospira while conversion of nitrite to nitrate is performed by Nitrobacter (e. g. N. agilis, N. winogradski) and Nitrospira. However, ammoniacal oxidation is considered as the limiting or critical process in nitrification since the ammonia-oxidizing bacteria (AOB) has very low growth rate (Metcalf and Eddy 1991). Various approaches, both culture dependent and independent have been applied to analyze and compare the microbial structure of biomass. However, culture dependent methods are biased by the selection of species which obviously do not represent the real dominant structure (Wagner et al 1995; Lipponen et al 2002). Recently, the development of culture independent molecular techniques, like fluorescence in situ hybridization (FISH), polymerase chain reaction (PCR) or denaturing gradient gel electrophoresis (DGGE) improved the analysis of environmental samples.

Whole cell fluorescene in situ hybridization (FISH) is a technique that uses fluorescently labelled phylogenetic oligonucleotide probes to detect specific whole cells/organisms in biological samples. It can be a valuable tool for the study of microbial dynamics in natural environments (Li et al 1999; Liu et al 2002, Eschenhagen et al 2003). These probes could be designed using the wealth of 16S and 23S rDNA sequence data available to target species, genera subdivisions or divisions in-situ and could be labelled with fluorescent groups, radioactive groups or antigens for immunological detection (Amann 1995).

A combination of the FISH approach with the application of scanning confocal laser microscopy (SCLM) allows non-destructive studies of the three dimensional arrangements of bacterial population identified and out-of-focus fluorescence (Wagner et al 1995). Biological Aerated Filters (BAFs) also have a long history of successfully removing nitrogen in wastewater treatment plants (Chen et al 2000; Quyang et al 2000; Chui et al 2001). Biofilm in the reactors bears great potential for simultaneous and efficient removal of nitrogen (Fdz — Polanco et al 2000). Therefore, an assessment of nitrogen removal efficiency has been made to detect any deterioration to the performance. A possible adverse effect of reduced mass of biofilm in the partial-bed reactor was foreseen for the reason that the slow-growing nitrifiers

will be more easily washed out at lower mean solids retention times (SRT) (Gieseke et al 2002). The denitrification process may also be disrupted because the biofilm provides potential anaerobic conditions in which denitrification flourishes.

Fdz-Polanco et al (2000) pointed out the importance of understanding the spatial distribution of the microbial population, and its activity, for the optimisation of nitrogen removal performance in reactors treating wastewater. The performance of the full and partial-bed reactors for nitrogen removal has been examined (Fatihah 2004). It was verified that the full — and partial-bed reactors have the capacity to remove 79.3 ±7.7 % and 79.4 ±3.6 % nitrogen at carbon organic loadings of 5.71 ±0.16 kg COD/m3.d, corresponding to nitrogen loadings of 0.24 ± 0.02 kg N/m3.d. At this condition, the organic carbon removal efficiency was 5.34 kg COD/m3.d for the full-bed and 5.22 kg COD/m3.d for the partial-bed. The successful removal of nitrogen indicates the existence of ammonia-oxidizing bacteria (AOB) in both reactors.

From the perspective of engineering design, it is important to be able to predict the functional groups of bacteria that are most favoured by various applied reactor conditions. In this respect, knowledge of their activities is more important than that of the detailed microbial population (Beer and Muyzer 1995). The nitrogen removal process in such systems is typically initiated by chemoliautotrophic ammonia-oxidizing bacteria converting ammonia to nitrite and traces of oxidized nitrogen gases. Subsequently nitrite-oxidizing bacteria catalyse the oxidation of nitrite to nitrate, and the process is then completed by denitrification (Metcalf and Eddy 1991). Clearly the oxidation processes of nitrification are an essential prerequisite for the whole removal process. In addition, retaining a large amount of nitrifying bacteria within the reactor can be difficult to achieve, due to their relatively low rates of respiration, and their subsequent sensitivity to DO and temperature, thereby making nitrification the rate-determining microbial system in the entire nitrogen removal process (Tsuneda et al 2003).

Since the number and the physiological activity of the ammonia oxidizers are generally the rate-limiting parameters, the rapid and reliable identification of this autotrophy is an important task. The aerobic ammonia oxidizers belong to a very restricted group of autotrophs with Nitrosomonas and Nitrosospira being the best-known oxidizers (Sliekers et al 2002), dominated by P-Proteobacteria (Wagner et al 1995; Eschenhagen et al 2003). Rowan et al (2003) found that detection of ammonia-oxidizing bacteria using PCR amplified 16S rRNA gene in a laboratory-scale BAF reflects the dominant AOB within a full-scale plant.

If the partial-bed reactor exhibited comparable nitrogen removal performance, intriguing questions would arise: would the slow-growing nitrifying bacteria’s preference for attachment on biofilm thereby enhancing sludge retention time (SRT), be challenged by bacterial growth in suspension: or would there be other factors related to reactor configuration that satisfied the need for nitrifying bacteria to grow in the partial-bed reactor. Since, for any high rate system, the AOBs need to reside within the biofilm that has a longer SRT than the suspended growth, it is interesting to locate the microorganisms along the height of both the full- and partial-bed reactors. The detailed aspects to be evaluated in this part include:

• to detect and enumerate the presence of AOBs in the biofilm and suspended growth biomass using fluorescence in situ hybridization (FISH) technique in combination with confocal laser scanning microscopy (CLSM)

• to correlate changes in the proportion of AOBs to all bacteria along the reactor heights in relation to the reactor configuration

• to associate factors that contribute to the changes in the AOB proportion

The most important factors affecting the colonization of open areas by plants are: the year and season of abandonment; the physical state of the site; climate; soil; the existing flora and fauna; proximity and position of source material; opportunities for vegetative regeneration;

and the presence, within a range possible for seed dispersal, of an efficient generative reproduction and a rapid, rich and long-distance dispersal of seeds (Falinski, 1980; Harmer et al., 2001). Reviews by Osbornova et al. (1990) and Myster (1993) report many studies of tree generation on abandoned farmland. Natural colonization by trees and other species have been recorded since 1882 at the Broadbalk Wilderness, UK, which has established on former farmland (Harmer et al., 2001). The first tree plants were recorded 30 years after abandonment, i. e. in 1913. The main species regenerating in the area were: common ash (Fraxinus excelsior L.); sycamore (Acer pseudoplatanus L.); field maple (Acer campestre L.); suckers of wild cherry (Prunus avium L.); blackthorn (Prunus spinosa L.); pedunculate oak (Quercus robur L.) and hazel (Corylus avellana L.). In 1998 the dominant and most frequent tree species were pedunculate oak, common ash, wild cherry and sycamore.

The area of farmland no longer in agricultural production increases as land owners cease activities or direct their energies towards other forms of management. When farmland is abandoned it is invaded by herbs and broadleaved tree species (alder, aspen and birch). In general, one species dominates in the new stand. Most such farmland areas are owned by private individuals. In Sweden, Johansson (1999a) found up to 10,000 broadleaved tree stems ha-1 on about 100,000 hectares of former farmland.

Natural tree establishment in an open area is a slow process, and it may be 5-10 years before trees 2-5 old are seen (Werner and Harbeck, 1982). Most such areas in Northern Europe are small, amounting to 0.5-2.0 ha. In the initial phase, the areas are not noticeable from the surroundings, but later a dense stand is established and the landscape is changed. In general, these areas continue to develop unnoticed by the owner or the public. Eventually, former open areas become covered by forest. Such ingrowth can be the result of natural seeding, sprouting or suckering (Fig. 2).

Interpolation is necessary to produce digital models from Lidar point cloud. The simple idea of the interpolation is referred to the nearest neighbor interpolation method to estimate the elevation (Maune, 2007). It searches for the set of nearest points, thus the new elevation value is selected as the same value of the nearest point instead of taking the average of all points. An important problem here is the zigzag appearance of the surface. This is in fact due to the selecting of the nearest point method by defining Voroni diagrams or Theissen polygons. For this reason, some kinds of averaging methods should be applied to the set of known nearest elevation points. Therefore, a weighted average like inverse distance weighting (IDW) is introduced which is working with the distances between these points (Monnet et al, 2010; Bater and Coops, 2009).

In Lidar data especially in vegetated areas distances are not related to the elevations. In contrast, kriging or geostatistical approaches provide better results (Heritage and Large,

2009) . However, they require more mathematically complex and computationally intensive algorithms. Since dense data is always available, rapid interpolation methods such as the nearest neighbor are prefered to use for the rough surfaces in the forest areas (Fallah Vazirabad and Karslioglu, 2010).

Riano et al. (2003) investigated the performances of spline and nearest neighbor interpolation methods to generate DTM. Spline interpolation is a special form of piecewise polynomial. The interpolation error in the DTM can be small even applying the low degree polynomial. They concluded that there were no large differences between the spline and nearest neighbor results while the spline computation was three times slower. Hollaus et al. (2010) described the derivation of DSM employing the least square fitting method to compare it with kriging interpolation. They introduced a moving least square fitting technique which selects the highest points in the search window as surface points. This technique finds the best fitting surface to the set of points by minimizing the sum of squares of the residuals of the points from surface. The results of this study showed that the least square fitting technique produced high precision DSM on rough surfaces while it needs more computational time.

Metabolic pathways that lead to the degradation of all the carbon sources that are discussed in this study were determined with KEGG. Metabolic intermediates that were common between different pathways were used to construct metabolic maps. Pathways for both strains were combined in Figures 5 and 6.

2. Results

2.1 Strain selection using electron micrographs

To determine the ability to form biofilm, electron microscopy was performed with the five strains that were listed in Materials and Methods. Figure 3 depicts one representative illustration of the 10 to 15 images that were obtained per bacterial strain. Most of these strains formed biofilm despite mutations affecting cell surface organelles of either reversible (flagella) or irreversible (type I fimbriae) attachment. The sole exception was the fimH mutant which only showed a small number of scattered bacteria attached across the slide. The fimA mutant exhibited a large number of filamentous appendages. We are currently unable to explain these appendages.

We wanted a strain for the phenotype microarray experiment that was able to form biofilm on complex media, while lacking one of the cell surface organelles. Since the amount of biofilm formed by the flhD mutant was similar to that of the parental strain in the electron micrographs, the flhD mutant was selected for further testing using the PM1 plates. The flhD mutant has as an additional advantage that much of the regulation by FlhD/FlhC has been previously described. This vast amount of information will help us to analyze the complex metabolic data.