Micro Patch Habitat Ecosystem Landscape Region

Figure 8.5. Spatial scales of functional groups in freshwater systems.

N2-fixers/S-transformers

Furthermore, although terminologies vary between domains, there is a degree of consistency in function of the groupings.

A set of 15 common functional groups may occur in soil, freshwater, and/or sediment environments, representing a wide variety of major taxonomic groups (Table 8.1). Each functional group includes a variable number of species, from one species to relatively species-rich phylogenetic clades (Brussaard et al. 1997). Response traits of the species that comprise these functional groups determine the overall vulnerability of a functional group to perturbation, and also affect the scale of this vulnerability. For example, species with short generation times, high fecundity, and high growth rates are often ecologically tolerant and widely distributed, and they are, characteristically, successful colonists (Sakai et al. 2001).

As an example of an operational spatial scale that is midway between that of soil and marine sediments, the spatial scale of occurrence of these functional groups may be mapped from the microscopic level to landscape to region in freshwater (Figure 8.5). Figure 8.5 shows the scales of operation for our hypothesized set of generic functions. The range is related to the physical system components (levels 1 to 8) given in Figure 8.1b. The macroengineers, for example, can influence the system up to the landscape scale, as clearly illustrated by the beaver's activity in damming streams and changing downstream and lateral flow patterns and movement of materials. Bioturbators can have a small patch/habitat scale effect, as in the case of salmonid reproductive behav-

Table 8.2. Life history traits: Definition and scope of categories.

Trait

States Possible

Small (1-3)*, medium (4-6)*, large (7-8)*. Hours, days, months, years.

Poor, moderate, good. Assessed in terms of the typical distance propagules can travel. Poor = meters, good = kilometers.

Fission, budding, asexual propagules, sexual gametes. Low, medium, high, very high. Fecundity includes offspring/unit time or offspring/individual. Low = single figures yr-1, high = thousands yr-1. Present, absent.

Yes, no. Examples are insect larvae living in different habitats from the adults, and planktonic larvae produced by sedentary adults.

Low, moderate, high. This is a summary character, reflecting the ability of an organism to switch substrates or habitats in response to disturbances or stresses.

*Numbers refer to spatial scale categories in Figures 8.1a-8.1c.

**These would not be the same if there were dormancy.

Size

Life span/

Generation interval* Dispersal capacity

Reproductive mode Fecundity

Facultative dormancy Separate life stages

Ecological flexibility ior, which produce redds to lay their eggs in the substratum. In addition, larger-scale effects can occur, such as those of muskrats or hippos in wetlands. The openness of the freshwater systems allows predators and pathogens to operate over larger scales than might be expected from their size, whereas detritivores tend to operate at the patch to habitat level, associated with the detritus patches. Although primary producers in streams are at fairly small scales, phytoplankton in large lakes function at the full ecosystem scale. Microengineering is illustrated in freshwater systems by algal mats in desert streams, microbes/biofilm stabilizing fine sediment, and even by blackfly larvae that filter fine particles and produce larger-sized fecal particles, which leads to changes in particle size distribution and influences the movement of fine particulate matter downstream (Giller & Malmqvist 1998). Microbial decomposer activity is generally on small scales, although nitrogen fixation by blue-green algal mats can occur at the habitat scale.

Biological response traits of soil, freshwater, and marine species can be classified in eight types: size, potential life span, voltinism, dispersal capability, reproductive mode (e.g., sexual, asexual, facultatively asexual), fecundity, phenotypic plasticity (such as facultative dormancy and occurrence of spatially separated life stages), and ecological flexibility (or tolerance/amplitude of response). These response traits can be scaled against the corresponding functional groups (Table 8.2). One handicap is that life-history traits are poorly known for most species, other than some vertebrates, higher plants, and some invertebrates, (e.g., Brown 1986 for insects; Grime et al. 1988 for plants; Lavelle & Spain 2001 for soil invertebrates). Furthermore, phenotypic plasticity in many populations (such as facultative dormancy and occurrence of spatially separated life stages) and the range of triggers for this plasticity seem to be more extensive than previously expected (Lavelle 1983; Negovetic & Jokela 2001; Jennions & Telford 2002; Mitchell & Carvalho 2002; Peckarsky et al. 2002). This is particularly relevant to the delivery of ecosystem services. For example, phenotypic plasticity is a biological characteristic of successful invaders, just as invasive ant species may be characterized by the formation of supercolonies that lack distinct behavioral boundaries and are, therefore, able to dominate entire habitats (Holway et al. 2002).

Current risk assessment protocols for weeds, invasive plants, and alien fish species in North America are predicated on knowing species characteristics (e.g., Kolar & Lodge 2002), as are conservation efforts (Côte & Reynolds 2002), though similar approaches to soil and sediment organisms are limited to very few cases (Blackshaw 1997; McLean & Parkinson 2000). Recently, Wilby and Thomas (2002) suggested that basic biological insights can "allow more accurate predictions of the effect of species loss on the delivery of ecosystem services," but these are available only for a limited number of soil or aquatic organisms (Lavelle & Spain 2001). Several taxa have a wide range of biological traits, such that the functional group of "litter transformers" can include species with high metabolism, high fecundity, and short life spans (e.g., most microarthropods including Astigmata), and those with low fecundity and long life spans, most taking more than a year to complete their life cycle (e.g., most Oribatida; Walter & Proctor 1999). Insect root herbivores are, likewise, variable in life-history traits and may display variation according to abiotic and biotic conditions (Brown & Gange 1990). For microorganisms, there has been little attention to life-history traits, other than reproductive attributes. More information is available on soil ecosystem engineers and their functional impact on soil processes. Recently, attention has been paid to the structure and composition of the biogenic structures that they produce, and their evolution in time and impact on soil properties at large scales (Le Bayon & Binet 1999; Decaëns et al. 2001). Specific microbial communities generate characteristic organic signatures (based on near infrared spectrometry), which have been characterized to indicate the likely diversity of functional impacts in soil (Hedde, Decaëns, Jimenez, and Lavelle, unpub. data).

Table 8.3 presents our assessment of the most critical set of ecosystem services, listed, respectively, as provisioning, supporting, and cultural services, and the functional groups that are responsible for delivery of each. For the listed services, traits contributing to vulnerability of the service and the desired trait level can be identified. An example is given in Table 8.4 for nutrient cycling in freshwater systems.

Table 8.3. Functional groups involved in the provision of ecosystem services.

Functional Group Involved

Service

Freshwater

Marine

Soil

Provisioning

Animal food production 8,12,11

Plant food production 7,8

Other biological production none

Biochemicals/medicines/models 7

Fresh water production 1,9,10,4

Clean sea water N/A

Fuels/energy 7

Nonliving material

Transport 7,15 Supporting

C sequestration 1,7 Trace gasses/Atmospheric composition 6 Soil and sediment formation + structure 5,14,15 Nutrient cycling 1,3,6,9,10,11 Biocontrol

Detoxification/waste treatment 1,6,9,10,11

Flood/erosion control 7,15 Climate regulation/

Atmospheric composition 3,4,6

Redox 1,6 Trophic support

Habitat provision/refugia/landscape interconnections + structure 5,7,14,15

Cultural

Aesthetic/recreation 7,8,12

II,12,14,15

II,12,14,15

II,12,14,15

II,12,13,14,15

II,12,13,14,15

II,12,13,14,15

1,14,15

Spatial Biotic

Table 8.4. Nutrient cycling in freshwater systems: Functional groups and associated biological traits responsible for the service, scales at which the service is delivered, and optimum intervention levels for management along biotic and spatial scales as defined in Figures 8.1a—8.1c.

Spatial

Biotic

Traits

Desired

Intervention

Intervention

Functional

Contributing

Trait

Scale Level

Scale Level

Group

to Vulnerability

Level

1—6 5—6

1-4 4

1,3,6

DC

7

EF

Generalist

9,10,11

LS

5-6

DC

6-7

PP

No

EF

Generalist

F

4-6

Implications for Management of Ecosystem Services

Based on the eight general levels for spatial and biotic patterns we identified earlier (Figures 8.1a, b, and c), we have been able to consider the scales over which the various ecosystem services are most vulnerable, at what scale we can intervene for management, and which functional groups are the most important for the various services. We can then evaluate which of the response traits (Table 8.2) of species are contributing most to their vulnerability, and what the desired trait level would be to overcome/resist this vulnerability. While this is currently a conceptual exercise, it does offer the possibility for the development of a management tool once we have more objective data on specific vulnerability levels and critical traits. As an example of the approach of identifying biological/ecological traits that contribute to the vulnerability of a particular service for the freshwater domain, we have used the ecosystem service of nutrient cycling. The desired trait levels are "best guesses" at present, until research has rigorously tested the links between traits, the functioning of the ecosystem, and the provision and stability of the services. The approach offers a good basis for the development of better management practices and a method for linking considerations of biodiversity more directly to the management of ecological services.

We conclude with a number of clear patterns that emerge from this analysis. We suggest that these patterns provide a useful basis for considering the appropriate scales of management intervention in soils and sediments, with a focus on the key biodiversity elements involved:

1. The biodiversity in soils and sediments allows the creation of self-organizing systems (SOSs), recognizable by a clearly defined set of interacting organisms and a specifically defined habitat that they create and/or inhabit. SOSs are nested within each other as scale increases.

2. SOSs participate in the regulation and/or delivery of ecosystem services at eight different levels extending over approximately 16 orders of magnitude, from microhabitats to the whole biosphere. Each of these SOSs has a definable buffering capacity against disturbances.

3. All species in SOSs participate in provision of the service to the extent that they contribute certain functional traits and can resist disturbances with adequate response traits.

4. Ecosystem services provided by soils and sediments are more vulnerable as they are provided at a limited number of scales (with a low number of buffers), and because a limited number of scales separate the processes from their delivery.

5. Successful protection and restoration therefore requires a number of specific steps:

• Identify the scales at which processes that sustain a service operate;

• Identify the functional groups that are essential to the service and the species that comprise the functional group;

• List the response traits that allow these species to adapt to disturbance;

• Limit disturbances to acceptable levels (protection) or reintroduce species with acceptable trait levels in a newly recreated ecosystem.

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