Essay on “Ecological Complexity”
Ecological complexity and ecosystem functioning likely depend on factors that govern species coexistence. Many such factors are predicted to be altered under global change.
Theories currently under discussion can be categorized into those that relate coexistence to:
(i) competitions and differential colonization
(ii) partitioning of resources across space
(iii) partitioning of resources across time
(iv) multiple trophic level interactions and
(v) some or all of above.
Complexity of landscapes is determined by number of ecosystem types, their characteristics, their sizes and shapes and associated connectivity. Complexity at this scale would have large consequence on regional to global scale processes.
Presence and arrangement of keystone ecosystem types, such as, wetlands often determine total carbon and nitrogen balance of a region. Productivity, biogeochemical cycling, water and energy exchange operate at a number of scales. Understanding ecosystem processes should be extended to global scale.
Many global models on ecosystem processes are based on direct extrapolations of process, understanding at patch scale, ignoring potential confounding effects or landscape scale phenomena.
Changes in average environmental conditions or extreme environmental events and intense land use management are believed to increase species extinction rate in isolated habitat fragments.
Isolation shall make it too difficult for many taxa to migrate to suitable environment. Changes in land use, land cover and landscape complexity compound this problem. Loss of key species, such as top predators, unit dispersers and pollinators from habitat may severely disrupt ecosystems functioning.
Landscape patterns, such as forest patches of different successional, age are consequences of regional disturbance regime, e.g., through changes in land use. Studies on disturbance in past have focused on patch-scale with an emphasis on community or ecosystem responses to disturbance and recovery from disturbance with relatively little attention to impact of landscape patterns.
Thus understanding of interaction of landscape pattern and disturbance regime should be improved. Studies on global and regional changes in past focused on climate or atmospheric chemistry and short term studies.
Urgent need for long term experiments across a wide range of climates to measure the interactive effects of changing climate and atmospheric composition on ecosystems of contrasting biodiversity and ecological complexity worldwide is now recognized.
Land use changes are due to expanding urbanization, concomitant landscape fragmentation and intensification of production systems. Such change results in transformation of an ecosystem from one state to another state via, a transition, and phase.
This translation is believed to confer impoverishment of ecological complexity. Belowground diversity decline during such transitions which ultimately lead to declines in aboveground biodiversity. That transition can also induce a restoration process and thereby increases biodiversity.
Global change such as physiological and compositional responses to elevated C02 should be formalized into integrated models for predicting response of ecological complexity to global changes. Simple analytical- and complex simulation models predict changes in climate and atmospheric composition.
Similar models need to be developed to formalize and predict likely or at least plausible overall effects of global change on ecological complexity. Changes in ecosystem complexity/ functioning, due to global changes could diminish stability, resistance and resilience of managed terrestrial ecosystems and jeopardize important food and fibre sources and ability of natural ecosystems both to provide natural resources and to remove pollutants from atmosphere.
Understanding and predicting diversity are fundamental goals in ecology. Relationship between richness and biomass is commonly unimodal or monotonic (Mittlebach et al., 2001). Most ecologists have used a univariate approach focusing directly on, effects of biomass (or some other measure of production) even though biomass itself may or may not be the direct causal factor affecting richness. Univariate methods tend to explain about half as much variation as do multivariate studies (Grace, 1999).
Grace and Pugesek (1997) presented a structural equation model that addressed multiple factors affecting species richness. They found that species richness was most strongly affected by light, reaching the soil surface and by abiotic stress related to soil quality.
They also presented a general model for understanding variation in species richness in response to stress and disturbance. They proposed that negative effects of biomass on species richness are both direct and indirect, by reducing light at soil surface. Similarly, disturbance should tend to affect light levels both directly and indirectly via, biomass. The conceptual model was more fully described by Grace (1999).
Disturbance and biomass had the strongest effects on species richness. Grace and Pugesek’s (1997) general model was not confirmed. Emergence of soil effects shows the strength of structural equation modeling. Using correlations and multiple regression, soil factors appeared to have very weak, if any effect on species richness.
Structural model shows that soil quality effect on species richness and an opposing direct effect and these effects are of similar magnitude. While this kind of result seems at first counter intuitive, other structural models deconstructing soil quality into two components have shown that two soil components may have opposing effects on richness. These effects can be explained as being caused by a positive effect on fundamental species pools and by a negative effect of biotic interactions.
At global or continental scales, energy related climatic variables have been proposed as driving factors of diversity patterns for some groups of vertebrates (Currie, 1991). Decrease in available energy as a consequence of altitude and its effect on species richness need to be considered as a driving factor.
That altitude and subsequent reduction in energy supply as a constraint limits number of vertebrate species (Danell et al., 1996), is also suggested although this role is not so evident at intermediate scales (Fraser, 1988). A study show that number of mammalian species increases with area of alpine cover in each cell but only until 20% of alpine cover. Cell probably includes several different cover types, thus allowing higher habitat diversity.
Above 20%. Proportion of alpine cover is too large and corresponding cells belonging mainly to high mountain areas have fewer mammalian species, almost certainly because of environmental limitations of alpine habitats. These alpine biotopes are suitable for certain mammalian species such as Pyrenean vole, Microtus gerbei, snow vole, Chionomys nivalis or Iberian desman, Galemys pyrenaicus.
Similarly, specific richness of birds decreases notably in areas with alpine habitats (Turner et al., 1988), although a few species are found only in that habitat (Tychodroma muraria, Montifringilla nivalis, Lagopus mutus, etc.).
Environmental diversity has been tested as a driving factor of diversity in different groups of vertebrates (Bohning- Gaese, 1997). An increment of environmental diversity normally produces an increase in species richness as a consequence of higher number of habitats and availability of different resources.
Moreover, there is a correlation between area of Eurosiberian cover and mammalian species richness, when spatial structure of environmental variable is removed. This suggest that cells geographically located in Eurosiberian region containing a mixture of Eurosiberian and Mediterranean covers and show higher levels of species richness as a consequence of land cover diversity. Mammals are the only group seemingly related to level of human occupation, after detrending.
However, contrary to expected results, relationship seems to be direct, i.e., more intense is the human occupation, more is the mammalian species there (Bravo and Martinez-Rica, 2004).