7. Discusión
7.1. Implicación del estado diferenciado de los oligodendrocitos en una mayor susceptibilidad a HSV-1
Natural conditions Diked flooding
Soil
Clay-loam, saturated Clay-loam, flooded
Vegetation (No. of species)
37 12 Dominant species
Panicum laxum Hymenachne amplex.
Leersia hexandra Leersia hexandra
Paspalum chaff.
Axonopus comp.
Above-ground primary production (t ha–1)
7±1 10 Landscape response units 99
Two LRUs were chosen to exemplify the differences observed in response to flooding.
Tables 7.2 and 7.3 the different variables that were used in comparing the response to regulated flooding by the dikes of the ‘Bajio’ unit in the recent savanna, versus the ‘silty Bajio’ in the ancient savanna. In both cases there was a significant decrease in the diversity of the plant species that invade under flooded conditions, both in terms of the total number of species and in terms of the species that account for most of the above-ground biomass. The response in total above-above-ground biomass due to regulated flooding was marked by a significant increase in the Bajio of the recent savanna, in contrast to the very slight increase in the above-ground biomass of the silty Bajio of the ancient savanna.
The differences in the productivity of the two landscapes can be explained in terms of the relatively lower levels of soil nutrients found in the ancient savanna (Ramia, 1980), and probably in terms of the differences between the two landscapes in the effect that spatial patterns have on the dynamics of nutrient flows.
Table 7.3. Effect of regulated flooding on the Silty-Bajio of the ancient savanna.
Natural conditions Diked flooding
Soils Silty, saturated Silty, flooded
Vegetation (No. of species)
20 10 Dominant species
Mesosetium chasae Paratheria prostata
Axonopus anceps Leersia haexandra
Andropogon brevifolius
Axonopus purpusii
Sorghastrum parvifl.
Leersia hexandra
Bare soil 35%
Above-ground primary production (t ha−1)
2.5 3.5
Discussion
The central idea of this chapter is that landscapes are part of complex natural systems that can be characterized by three major features which determine the context in which a methodological framework can be developed. Such systems are the product of an evolutionary process, they display spatial structure that is self-generated (at least in part), and they possess non-linear dynamics that explain the unpredictable nature of the response to man’s accumulated impacts. Because these systems are the product of an on-going evolutionary process, their dynamics follow trajectories that are far from equilibrium. The system components are therefore the product of a long process of mutual adjustment and coevolution, and they are characterized by non-linear responses to changes in the environment, or as a result of human intervention.
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The interaction between the biotic, the abiotic, and the human processes is what creates and maintains the structure and flows in the landscape. Plant and animal populations are dealing simultaneously with problems of obtaining their requirements for growth and reproduction (sunlight, nutrients and water) whilst being embedded within an interconnected network of interacting populations. At a local level, physical and mechanical forces tend to shape certain types of soil and sediment into units with specific characteristics (soil texture, nutrient contents and water retention). As plants and animals colonize each of these units they tend to change some of these characteristics. As organic matter accumulates, the water-holding capacity may increase. The initial conditions of the site and the history of the community will determine the direction and rate of change of the characteristics in each unit. The members of the present community of a site may change these characteristics just enough to make the site better suited for other populations to become established. These interactions go on within and between populations, generating some spatial pattern that might be recognized and used to characterize the landscape in terms of LRUs.
It is evident that social and cultural factors as well as government policies and subsidies influence land-use practices. What are not well understood are the mechanisms and causal links that govern the interactions among these physical, climatic, biological and human factors that might lead to changes in the patterns of the landscape and even land degradation. For example, the land degradation occurring in many regions can be attributed to changes in agricultural practices. The impact of these practices has been further aggravated by government subsidies that provide an economic incentive which makes these new land-use practices much more attractive. The ecological and environmental responses that are being observed result from the complex interactions between changing value systems and economic incentives on the part of farmers and national or international policies.
It is the dialogue between local dynamics and global patterns that produce the seemingly stable spatial patterns of the landscape. The spatial patterns that are observed in a system cannot be explained in terms of exogeneous changes, in fact they are a natural consequence of the biotic-abiotic interactions of the components in the system. For example, fire is a part of the ecology of many landscapes. If it was conceived as a
‘disturbance’ to some current equilibrium, it would imply that the equilibrium communities in the landscape would resist its impact. But, inevitably, the impact of fire would lead to a complete denudation of the landscape, reduction of diversity, and eventual degradation. In studying landscapes that have been sub-jected to fire in their evolution, what is observed is the colonization and gradual adaptation of soil organisms and plant communities that ‘learn’ to coexist with periodic fire.
The LRU concept can be a useful way of gaining further understanding of the complex linkages between the physical, ecological, climatic and human components of the landscape ecosystem. Overlaying techniques are a powerful tool for visualizing these interactions (Burrough, 1986; Goulter and Forrest, 1987; Bailey, 1988; Agee et al., 1989). However, these techniques could benefit from considering landscape flows and structures that make up the LRU. In this way the difficult task of combining different types of spatial information for gaining further understanding of the complex dynamics of the landscape may be achieved.
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