Seguridad en el manejo de la electricidad

In this study, the effect of forestry on small headwater stream metabolism varied according to the spatial and organisational resolution at which metabolism was observed. This illustrates the need for multiple metabolic measures to assess the response of different parts of the metabolic community to disturbance. At a habitat- patch scale, the influence of forestry was detectable regardless of geological setting for productivity and respiration. On average a five-fold increase in productivity and a doubling in respiration between unlogged and logged streams was observed. This substantial increase in metabolism was similar to observations from south eastern Queensland streams, where the GPP and R24 of sediment and cobble patches were shown to increase by two orders of magnitude across a disturbance gradient based on the clearance of catchment vegetation (Fellows et al. 2006). Environmental variables that best predicted patterns in patch scale metabolic measures were catchment scale descriptors of disturbance, and this was also observed in the study by Fellows and colleagues (2006).

The overwhelming effect of disturbance was to increase the autotrophic potential of headwater streams, and this was best illustrated by the increased biomass of algae. It appears that small headwater streams are primarily light limited and that in the short- term, logging reduces canopy cover thereby increasing the standing biomass of algae. Secondary nutrient limitation of primary productivity, as observed in larger lotic systems (e.g.Udy et al. 2006), was not evident in these small headwater streams because the biomass of algae was not enhanced by nutrient additions. Increased algal biomass at a patch scale is likely to contribute greatly to increased GPP at a whole system scale following disturbance (e.g. riparian disturbance, Ulrich et al. 1993; hydrological disturbance, Reid et al. 2006; nutrient enrichment, Mosisch et al. 2001). It was found that geology affected cellulose decomposition potential in sediment patches and this may be due to distinct differences in sediment and water chemistry between the geological settings. CTSL almost doubled in logged dolerite streams, which are characterised by relatively poorly sorted sediments, high concentrations of sediment nutrients and low concentrations of water nutrients. By contrast, CTSL

decreased slightly in logged granite streams, which are characterised by well-sorted larger sediments, low concentrations of sediment nutrients and high concentrations of water nutrients. While no previous studies have adopted cellulose decomposition potential as a method to assess anthropogenic disturbance in stream sediments, CTSL has been shown to be lower in coarse than fine sediments (Boulton and Quinn 2000, Claret et al. 2001, Chapter 3). Therefore, any disturbance that alters sediment qualities at a patch scale is likely to influence cotton decomposition potential. Forestry resulted in increased sediment nutrient status in both geologies, which may explain increased CTSL in dolerite streams, but it is unclear what factors contributed to decreased CTSL in granite. Forestry also altered the relative quantity of sediment at a reach scale, with increased sediment in dolerite streams compared to decreased sediment in granite streams. Hence, the cotton decomposition potential of the whole system is affected by logging.

The size of the effects of forestry on metabolism at a patch scale was amplified at the whole system scale. When scaled to reach estimates, metabolism showed a 10-fold increase in GPP and a doubling of R24 in logged versus unlogged streams. This was due to an increase in the occurrence of habitats with high metabolic rates, such as depositional sediment. Similarly, reach scale sediment respiration rates obtained from the slurry method in logged streams were almost double that observed in unlogged streams. Previous studies of whole system metabolism have observed similar

responses to catchment and riparian disturbance. For example, GPP in reaches of the La Trobe River (Victoria, Australia) subject to catchment and riparian clearing for agriculture was up to twelve times greater than relatively undisturbed headwater reaches, but a less than two-fold increase was observed in respiration (Chessman 1985). Similarly, catchment and riparian clearing for agriculture in the Taieri River catchment (New Zealand) was shown to result in GPP over four times greater than minimally-disturbed streams, however in this instance, a two-fold decrease in respiration was observed (Young and Huryn 1999). Each of these studies observed strong relationships between metabolic response and catchment scale descriptors of disturbance, as was observed in this study. Therefore, whilst the effect of

anthropogenic disturbance at the whole system level appears situation dependent, catchment scale descriptors of disturbance can be used to predict changes in the

environmental variables, such as light and temperature, are not identified at this scale, yet several studies have illustrated the hierarchical nature of disturbance, where catchment scale disturbance leads to direct changes in physical and chemical properties in-stream (Poff 1997, Royer and Minshall 2003).

The data presented here demonstrate that the effects of disturbance on metabolism are evident at a patch scale, and were amplified at the larger spatial scale, i.e. the effect size was greater at higher rather than lower levels of organisation. There was no evidence of incorporation of lower level responses into responses at high levels (O'Neill et al. 1986, Pickett et al. 1989). However, in this study, metabolic rates at different organisational scales are confounded by measurement at hierarchical spatial scales. As such, it is possible that the increased complexity of the system, as we move from patch to reach scale, allows for the accumulation of multiple levels of response to disturbance. This concurs with Fisher and colleagues (1998) who suggest that patch configuration and connectivity will affect the response to disturbance at an ecosystem level.

5.4.2 Assessing the suitability of metabolic methods to evaluate the impact of