Remotely sensed hydrological isolation : a key factor predicting plant species distribution in fens

M.E. Sanders

Research output: Thesisinternal PhD, WU


<p>In fens the species composition, vegetation structure and succession rate are determined by vegetation management and water chemistry, particularly by the base status and nutrient status. Base-rich and nutrient-rich surface water causes fens to become eutrophied, which leads to an increased biomass production. When part of fens becomes isolated from this surface water (hydrological isolation), it acidifies due to acidic and oligotrophic rainwater dominance. One consequence of decreasing water quality due to continuing acidification and eutrophication, is the disappearance of the rare plant species that depend on base-rich but oligotrophic water. It is important to obtain quantitative information on the influence of these processes on vegetation structure types and the distribution of rare plant species to support management planning and evaluation. The usual method to obtain this information is fieldwork, but this is time consuming and thus very expensive, especially in large, inaccessible areas like wetlands. The aim of this study was therefore to investigate the efficiency of remote sensing and geographical information systems (GIS) to identify hydrological isolation in order to predict the distribution of rare plant species.</p><H3>De Weerribben study area</H3><p>Dutch inland wetlands are characterized human impacts. The peat cutting and dredging in the 18th and 19th centuries formed a landscape of extensive rectangular bodies of open water (ca. 30 by 1000 m) called <em>petgaten</em> . After the <em>petgaten</em> were abandoned, a process of terrestrialization from open water to fen vegetation began, in which the first stage is the formation of a floating raft of vegetation. The reeds on the floating rafts were mown every year for thatch. When not mown, the open fen becomes a woodland within a few years. During the 20th century most of the fens were drained and reclaimed for agricultural use. De Weerribben (3600 ha), now a nature reserve, is one of the remaining fen areas in the north of The Netherlands (6 <sup>o</SUP>0 <sup>'</SUP>E and 52 <sup>o</SUP>45 <sup>'</SUP>N).</p><p>Hydrology strongly influences the species composition in De Weerribben. Water loss caused by this infiltration to the surrounding polders that have a lower water table and by evapotranspiration is compensated for by an influx of surface water, precipitation and (locally) by irrigation. This influx creates a complex of gradients from surface water dominance to rainwater dominance.</p><H3>Remote sensing</H3><p>False colour aerial photographs contain detailed information that can be extracted by an interpreter with good field knowledge. The best and most objective combination of methods was used to derive significant information from the photographs without relying too much on the skill of an interpreter. Analogue photo interpretation was suitable to map water, peat baulks, open fen and woodland because they were easily recognized thanks to their contrasting reflectance, texture and sharp boundaries. These classes were used for stratifying the landscape. Within the strata digital image processing was used to derive information on gradients. Interpretation based on expert knowledge of the spectral values coincidence with differences in biomass of the vegetation and wetness of the floating raft.</p><p>Vegetation scientists and nature management organizations are mainly interested in species composition. Although species composition and reflectance are both characteristics of a vegetation type, it was not possible to map the desired vegetation types of the entire area solely with aerial photographs. The vegetation types mapped in the field are based on species composition and structural differences that are indicative of environmental conditions to a certain extent. They were grouped into vegetation structure types indicative of differences in biomass, wetness and vegetation management. The reliability and accuracy of the remote sensing classification were determined as an 'indication' of the ecological significance of the spectral classes. It could be concluded that the spectral classes corresponded reasonably well with the grouped vegetation types of the vegetation map. Subsequently, the results of the remote sensing interpretation were used to model hydrological isolation and to predict species distribution.</p><H3>Hydrological isolation in a GIS environment to predict plant species distribution</H3><p>Field information on base status and nutrient status was only available for a few selected sample points in De Weerribben. Information on water chemistry covering the entire area was, therefore, obtained by modelling hydrological isolation spatially. The water balance and Darcy's law were used to define a spatial mathematical model for hydrological isolation. A GIS was used determine topological relations and data integration. The variables input into this model were: precipitation, infiltration, evapotranspiration, permeability, distance to the surface water and hinterland area. Permeability values were obtained by reclassifying the raft thickness classes of the soil map on the basis of literature. Average values for precipitation, infiltration and evapotranspiration were used as input constants because the spatial variation of these variables was not known. The results of the remote sensing interpretation were used as hydrological source (watercourses) and hydrological barriers (peat baulks). Wetness was assumed to be a hydrological short cut, decreasing the influence of the hydrological isolation model. A wet site received surface water by irrigation or flooding instead of an influx through the floating raft.</p><p>The hydrological isolation was used to predict the species distribution. Two plant species indicative of opposite environmental conditions in relation to base status were selected to model species distribution: <em>Scorpidium scorpioides</em> (Hedw.) Limpr and <em>Erica tetralix</em> L. <em>Scorpidium</em> is a rare moss characteristic of base-rich conditions and an early stage of terrestrialization. <em>Erica</em> is a dwarf shrub that is not very rare. It is indicative of base-poor conditions and an advanced stage of terrestrialization.</p><p>Regression analysis was used to determine how <em>Erica</em> and <em>Scorpidium</em> are related to environmental variables and to predict their occurrence. The regression analysis was adapted to take account of the specific conditions of this study. A major problem was 'missing absences' on the point distribution maps of the plant species, i.e. points representing the absence of a species had not been recorded. These absences, which were necessary to apply logit regression, were obtained by generating random points. The distribution of absence points had to be representative of the area of all site factor class combinations, to prove that species distribution is not evenly distributed over all classes. Therefore, there had to be very many such points. As a result, the predicted probabilities of occurrence were relative instead of absolute, because they depended on the number of random points.</p><p>Environmental variables that appeared to have a statistical significant effect on the occurrence of either species agreed well with the environmental needs of these species reported in literature. Hydrological isolation significantly explained the species occurrence. It can be concluded that the remote sensing and GIS techniques turned out to be very suitable for determining hydrological isolation to identify potential habitat for plant species; information can be used to optimize field sampling, for management planning and evaluation, and in scenario studies.</p>
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Molenaar, M., Promotor
  • Pedroli, G.B.M., Promotor, External person
Award date1 Oct 1999
Place of PublicationS.l.
Print ISBNs9789058080738
Publication statusPublished - 1999



  • plants
  • species
  • distribution
  • wetlands
  • remote sensing
  • aerial surveys
  • vegetation types
  • management
  • maps
  • national parks
  • netherlands
  • overijssel
  • nature

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