Patterns arise in any landscape as a result of the underlying processes Disturbance and fragmentation are closely allied, and have significant impacts on the environment Heterogeneity is the main pattern in any landscape, & is inherent at all scales “The uneven, non-random distribution of objects” (Forman, 1995) Since every pattern in a landscape results from, and produces new processes, heterogeneity is important for landscape function The analysis of heterogeneity is fundamental to the understanding of landscape functions and spatial ecological processes non-random
Heterogeneity Three types to be considered: –Spatial: variation in space, either horizontally (as under human disturbance regimes) or vertical (uneven vegetation distribution above ground – generally natural) –Temporal: similar to spatial, but implies variation for a single point over time. Two areas may have the same spatial variation, but differ in time. –Functional: variation in distribution of communities/ populations. Linked to life history of organisms Soil composition is a strong driver of heterogeneity, & it varies strongly from individual plots (1-10m) to the full landscape (Becher, 1995). It can also vary vertically in the soil profile The effect of geological heterogeneity is unpredictable, and a probabilistic approach is used when modelling it
Heterogeneity By creating borders and edge effects, additional processes are set up in the landscape, influencing the flux of materials Since plant and animal species respond fairly rapidly to changes in mosaic heterogeneity, minor variations can often be observed with remote sensing techniques. Effectively, heterogeneity can exaggerate biological- environment interactions (eg: skylarks avoid small prairie spaces, even though they are functionally similar to larger patches) (Farina, 1998) Heterogeneous landscapes can show several different stable configurations, and can shift between them rapidly given sufficient incitement. This is termed a polyclimactic state, and it is determined by variations in deterministic & stochastic factors (wind, climate extremes, climate change, edaphic conditions) and internal factors (disease, predation, invasion)
Disturbance Hence disturbance can play a role in maintaining heterogeneity and preventing stable equilibria developing. A moderate disturbance regime can increase heterogeneity, but it depends on the initial conditions Homogeneous system: heterogeneity increases to the midpoint, then falls Highly heterogeneous: after an initial gain in heterogeneity, there is a rapid dropoff (Kolasa & Rollo, 1991)
Disturbance Obviously, some disturbance can be useful for maintaining heterogeneity. Likewise, heterogeneity can impact on the disturbance regime: –fires spread less readily in a mixed woodland than in a pure coniferous matrix (reduced disturbance) –predators (eg: foxes) in woodlots & parklands in an agricultural environment can impact on livestock (increased disturbance) Species distribution depend on community heterogeneity: large sample areas include more species, and thus should be more similar than smaller ones with a limited selection of species.
Structure Three main types of heterogeneity structure (Addicot et al., 1987) : –Divided homogeneous (suitable patches in an unsuitable matrix) –Undivided heterogeneous (patches of varying suitability) –Divided heterogeneous (varying suitability patches in an unsuitable matrix
Scale Fire, grazing & the two in combination were tested in grasslands (Glenn et al, 1992) Locally, burning seemed to have higher heterogeneity than grazing, whilst the corollary was true at a regional scale. Overall, untreated local plots had the most heterogeneity, but regional responses varied to a large degree, depending on season of burning (spring burning then grazing increased heterogeneity, autumn burns reduced it) This variation makes studies complicated – some processes depend on patchiness, but not all. General, organismal responses are a good measure by which to assess relevant scale. (neighbourhood scale) Neighbourhood for vagile species is obviously their territory or resource area For sessile species it is more complex, but it can be estimated according to the areas from which food, predators and other foragers come.
Animals Spatial heterogeneity is one of the main factors determining bird species diversity in the landscape (MacArthur et al., 1962) Bird diversity was also higher in shrubby areas because shrubs have higher heterogeneity than tree areas (even though trees have more variation in canopy structure) Animals also drive heterogeneity: 05/pics/1HWANGE1badland.jpg grazing animals at high densities can permanently alter vegetation cover by compacting soil and removing vegetation (eg: rural goat grazing in Zimbabwe) Animals can even alter geomorphology, & all sizes can impact heterogeneity: –Insects (ants & termites shift soil, dung beetles enrich soil) –Small mammals (moles & rabbits digging soil, other rodents distributing seed) –Medium mammals (beaver dams, pigs rooting) –Large mammals (elephants/buffalo opening up cover) –All sizes of birds affect seed distribution & enrich soil with droppings
Foraging Species-level heterogeneity requires individuals to modify their foraging habits – in larger patches they can afford to spend less time foraging Time spent within a patch varies as the square of the linear dimension of the patch, whilst travel time between them varies linearly (ie): large patches are preferable and used in a more specialised way than small patches. (MacArthur & Pianka, 1966) For large species, it has been found that they respond to landscape-level heterogeneity, but not locally (bison, Wallace et al., 1995 ) Thus, they move in a determined manner (non-randomly) between patches, but within patches move randomly, minimising energy use (optimal foraging) Similar observations of sheep grazing showed that they generally moved directly to the nearest plant, whilst occasionally moving between plants It is possible that heterogeneity therefore plays a role in determining optimal foraging strategies for species, and may even enhance the efficiency
Animal movements Certainly, movement within a matrix is determined by suitable/unsuitable patches, preventing animals from moving in straight lines (Johnson et al., 1992) It may also play a role in the recollection of routes in a home range (homing ability) Bumble bees’ foraging routes are generally longer in uniform stands, whilst in a varied stand they tend to backtrack more often Certainly digger wasps (small range) use landmarks to find their way about, and are prepared to fly further in a varied landscape
Animal movements Bees exhibit a similar behaviour Homing ability drops off fairly quickly in flat or uniform landscapes (Plowright & Galen, 1985) In comparison, in mountainous areas they can return from as far off as 9km, due to increased landmarks
Metrics of heterogeneity We can measure the heterogeneity of a landscape in terms of any resource (soil structure, plant diversity, biomass, thicket structure, animal distributions…) The variation in structure hence reflects changing functions and processes in the landscape In order to assess this, we use several different metrics, each of which considers different aspects of the structure. –Fractal dimension (measures the complexity of edges) –Contagion (the extent of aggregation of patches) –Evenness (measures number of different patch types & their proportions in the landscape) –Patchiness (contrasts neighbouring patches in a matrix) Li & Reynolds (1994) measured these different metrics against four components of heterogeneity
(Li & Reynolds, 1994)
Summary Heterogeneity is the principal characteristic of any landscape It varies due to underlying processes, and affects these processes in turn, by initiating or amplifying biological interactions Can be considered in terms of temporal, spatial or functional components Affects disturbance, although in both a positive & a negative manner Heterogeneity affects animal processes (eg, grazing efficiency of ungulates) and is likewise affected by the interactions of animals with landscape functional components Measured using different indices, including contagion, fractal dimension, evenness & patchiness
References Addicot, J.F., Aho, J.M. & Antolin, M.F. (1987) Ecological neighbourhoods: scaling environmental patterns. Oikos 49: Becher, H.H. (1995) On the importance of soil homogeneity when evaluating field trials. Journal of Agronomy & Crop Science 74: Farina, A. (1998) Principles and Methods in Landscape Ecology. Chapman and Hall, London, UK Forman, R.T.T. (1995) Land Mosaics. The ecology of landscapes and regions. Cambridge University Press, Cambridge. Glenn, S.M., Collins, S.L. & Gibson, D.J. (1992) Disturbance in tallgrass prairies: local and regional effects on community heterogeneity. Landscape Ecology. 7: Johnson, A.R., Wiens, J.A., Milne, B.T. & Crist, T.O. (1992)Animal movements and population dynamics in heterogeneous landscapes. Landscape Ecology 7: Kolasa, J. & Rollo, C.D. (1991) Introduction: the heterogeneity of heterogeneity: a glossary. In: Kolasa, J. and Pickett, S.T.A. Ecological heterogeneity. Springer- Verlag, New York, pp 1-23 Li, H. & Reynolds, J.F. (1994) A simualtion experiment to quantify spatial heterogeneity in categorical maps. Ecology 75: MacArthur, R.H., MacArthur, J.W. & Preer, J. (1962) On bird species diversity. II. Prediction of bird census from habitat measurements, American Naturalist 96: MacArthur, R.H. & Pianka, E.R. (1966) On optimal use of patchy environment. American Naturalist 100: Plowright, R.C. & Galen, C/ (1985) Landmarks or obstacles: the effect of spatial heterogeneity on bumblebee foraging behaviour. Oikos 44: