Peter A. Palmiotto

Review of root dynamics in forest ecosystems grouped by climate, climatic forest type and species

Patterns of both above- and belowground biomass and production were evaluated using published information from 200 individual data-sets. Data sets were comprised of the following types of information: organic matter storage in living and dead biomass (e.g. surface organic horizons and soil organic matter accumulations), above- and belowground net primary production (NPP) and biomass, litter transfers, climatic data (i.e. precipitation and temperature), and nutrient storage (N, P, Ca, K) in above- and belowground biomass, soil organic matter and litter transfers. Forests were grouped by climate, foliage life-span, species and soil order. Several climatic and nutrient variables were regressed against fine root biomass or net primary production to determine what variables were most useful in predicting their dynamics. There were no significant or consistent patterns for above- and belowground biomass accumulation or NPP change across the different climatic forest types and by soil order. Similarly, there were no consistent patterns of soil organic matter (SOM) accumulation by climatic forest type but SOM varied significantly by soil order—the chemistry of the soil was more important in determining the amount of organic matter accumulation than climate. Soil orders which were high in aluminum, iron, and clay (e.g. Ultisols, Oxisols) had high total living and dead organic matter accumulations-especially in the cold temperate zone and in the tropics. Climatic variables and nutrient storage pools (i.e. in the forest floor) successfully predicted fine root NPP but not fine root biomass which was better predicted by nutrients in litterfall. The importance of grouping information by species based on their adaptive strategies for water and nutrient-use is suggested by the data. Some species groups did not appear to be sensitive to large changes in either climatic or nutrient variables while for others these variables explained a large proportion of the variation in fine root biomass and/or NPP.

Allometric equations for two South American conifers: Test of a non-destructive method

Non-destructive biomass estimation for protected tree species is necessary to understand their population dynamics and the ecological factors affecting species scarcity. We present a method for estimating aboveground biomass of bole, branches and foliage, using data obtained by climbing live trees to collect limited samples and measurements. This method was . applied to 26 individuals of Fitzroya cupressoides Mol. Johnston, a protected Chilean conifer, and to 12 individuals of a . second, morphologically similar, but unprotected species, Pilgerodendron u˝iferum D. Don. Florin. Trees were climbed, ´ basal diameter of all branches ) 1 cm were recorded and four branches per tree were removed for further measurement. The sampled branches were used to develop allometric equations predicting branch, twig and foliar biomass from branch basal diameter. These equations were used to generate whole tree canopy biomass estimates based on climbers measurements of branch basal diameter. Bole biomass was estimated from serial measurements of height, diameter and wood density. Whole tree canopy and bole biomass estimates were then used to develop allometric equations predicting wood and foliar biomass from diameter at breast height. Five of the P. u˝iferum trees were felled and weighed by conventional methods, and the data used to evaluate error in the non-destructive technique. Although the technique was labor intensive, it was found to yield mean estimates for canopy components that are expected to be within 10% of the true mean for large populations of trees .watershed level studies . Accurate estimation of individual trees may be less reliable, as the amount of dispersion about . some of the regressions was quite high ) 20% . q 1998 Elsevier Science B.V.

Science and Management of Ecosystems Synthesis

The ecosystem management paradigm has been chosen as the approach to be used by federal agencies to manage federal lands. Because of the difficulty that federal agencies and academicians have had in defining what these two words mean and because the perception is that this means more data collection than is currently occurring, ecosystem management has a strong potential to be rejected as the approach to use for managing ecosystems. This would be extremely unfortunate because this approach has elements that are crucial to retain for “good” management of ecosystems. The components of ecosystem management (articulated in earlier chapters) are fundamentally important if ecosystems are to be managed where they function within the range of states natural for that system and at the same time produce the values (i.e., species, timber, nontimber forest products, etc.) humans have identified as desirable. Ecosystem management should be used as a tool that identifies what the trade-offs are in accepting a particular management option. It is an approach that will move the management of our natural ecosystems from being solely based on human “values” to one balanced by scientific information helping to clarify the consequences of the chosen values.

Case Studies: Degrees of Ecosystem Management

Not all organizations will want to implement the ecosystem management approach described earlier. However, there exist many different organizations for which the ecosystem management approach holds great utility for managing their resource into the future, including many who presently are not using this approach. Some organizations (i.e., federal agencies) have to implement ecosystem management (see Chapter 2), while others may utilize some aspects of the ecosystem management approach but may not want to adopt the ecosystem management approach in its entirety on their lands (i.e., private timber companies).

Detecting Resistance and Resilience of Ecosystems

Many useful tools exist that can be utilized at appropriate spatial scales to study ecosystems as described in Chapter 3. These methods, as presently utilized, have been very useful for increasing our understanding of the functions, structures, and feedbacks controlling processes at the individual plant to the ecosystem level. However, they have not been particularly effective for early detection of changes in ecosystems due to either chronic pollution or to small changes in abiotic environmental parameters (such as air temperatures). Most of our tools are very effective at detecting sudden, major changes (i.e., pulse perturbations) in the ecosystem in which a part has been dramatically manipulated by either its elimination (e.g., tree removal and herbicide applications to limit plant regrowth; Bormann and Likens 1979) or due to natural disturbances (e.g., hurricanes or landslides; Lugo and Scatena 1995). Difficulties associated with these questions and tools used to answer them include the following: 1. It is difficult to identify the present state of an ecosystem with respect to other ecosystems whose land-use and natural disturbance histories have differed. This difficulty stems from uncertainty as to what type of difference should be expected between impacted and non-impacted sites, and a set of measures that will allow discernment of differences between these ecosystems. Historical land uses can leave a legacy on the site that may or may not be difficult to detect (Hamburg and Sanford 1986, Garcia-Montiel and Scatena 1994). None of the criteria currently available allow us to determine where the site exists along a gradient of potential states and whether two sites with presently very different total productivities should exist in similar states or conditions. For example, one ecosystem may exist at a different state because it was influenced by human disturbances (e.g., pollution or previous land use) that overrides normal abiotic controls on plant growth (see further discussion of this in Section 4.2.1). 2. It is difficult to detect how far the current state of system is from the non—human-impacted condition. 3. It is difficult to identify how past land-use activities and other ecosystem legacies may be modifying how the current ecosystem is responding to disturbances or other manipulations. 4. It is difficult to identify the probability of adverse ecological changes, that is, current tools do not provide estimates of the risks associated with a management activity and/or natural disturbance(s) (i.e., make accurate predictions about future ecosystem state). 5. It is difficult to characterize the resilience and/or resistance of ecosystems to various disturbances. 6. It is difficult to determine if sustainable ecosystem management is being achieved in the short or long term.

Ecosystem Concept: Historical and Present Review of Definitions and Development of Ecosystem Ecology, Ecosystem Management, and Its Legal Framework

Managers and researchers are currently defining and setting objectives for ecosystem management; however, relatively few workers (NRC 1990) have attempted to determine what ecological information is needed to implement this new management strategy. While many workers agree that consideration of the scale of both natural processes and management practices is critically important under the ecosystem paradigm (Franklin and Forman 1987, Clark et al. 1991, Gordon 1993), and while many others have recently developed and refined theories about scale and natural systems (e.g., Allen and Starr 1982, O’Neill et al. 1986, Allen and Hoekstra 1992, 1994), few have directly applied these theories to guide management.

Tools and Knowledge Base Presently Available to Do Ecosystem Management and to Assess Its Success

Managers and researchers are currently defining and setting objectives for ecosystem management; however, it is not clear what ecological information is needed as a basis for setting specific management goals and priorities, or to implement ecosystem-based management in the field. The focus of this chapter is to describe how and what type of data have been collected in the past to assess ecosystems. The objective of this section is to identify what tools and bodies of knowledge are currently available to guide the planning and implementation of ecosystem-based management.