Analysis of changes in land use in the St. Catherines-Niagara area,

Transcription

1 Analysis of changes in land use in the St. Catherines-Niagara area, De Wet van Niekerk Student # GEOB 479: Research in GIScience Professor Brian Klinkenberg University of British Columbia 1 February 2011

2 van Niekerk 2 Executive Summary There is a conflict in land uses in the St. Catherines-Niagara area. In the period , the region saw a shift in land use from a landscape dominated by cropland to a diversity of uses. While the amount of built-up urban land has increased, it has not been at the expense of one single, other land use, but rather a variety of different uses. With greater diversity of land use, there has also been a loss of cohesion; this is of ecological concern. It was shown that some natural land uses, particularly woodland, are unstable that is, while are is gained, specific patches are not conserved. The constructed Markov model may be used to predict future land use patterns, with the assumption that current processes governing land use transition continue.

3 van Niekerk 3 1 Introduction In the St. Catherines-Niagara region, there is conflict between urban, agricultural and natural land uses (Muller and Middleton, 1994). Furthermore, with increasing population size and shifts in lifestyle in Canada, there has been concern surrounding the loss of agricultural land to built-up urban areas in the period from (Hansen, 1984). This report examines the transition of land use in the St. Catherines-Niagara area during this period, with an emphasis on natural land uses, as well as fragmentation of land use. Fragmentation may degrade habitat quality, partially through increasing edge effects (CITATION). Spatial data were manipulated using ESRI ArcMap 10.0, and fragmentation analysis was carried out using FRAGSTATS 3.4. Information on landscape and class metrics is from the FRAGSTATS online help file (UMass Land. Eco., 2011). 2 Discussion 2.1 Spatial Resolution While the data would be more efficient to collect and process, 500 metre cell size was found to be an inadequate resolution for use in detailed analysis. 100 metre cells are more appropriate. In table 1, for example, it can be seen that the number of distinct landscape patches detected was much lower, and thus many areas would be inappropriately interpreted. Indices of diversity and evenness are also distorted (table 1). A visual representation of the difference in resolution is attached for reference. While total area of land use type does not change to a great extent (figure 2), it can be seen in the comparative map that an unacceptable amount of detail is lost, and small patches become indistinguishable from larger, more prevalent surrounding patches. 2.2 Landscape Metrics Landscape metrics calculated using FRAGSTATS are number of patches, patch density, Shannon s diversity and evenness, and Simpson s diversity and evenness. Number of patches (NP) and patch density (PD) are correlated for a given area over time, as PD is merely the number of patches divided by the area. Both these metrics are of limited use, but the trend in both NP and PD does indicate a degree of increased fragmentation from 1966 to 1976 (table 1). Two measures of diversity were calculated Shannon s and Simpson s. Both are functions of both the richness of land use, as well as the equality of distribution between land use classes. However, Shannon s index shows increased sensitivity to rare land uses in comparison to Simpson s. Furthermore, Simpson s index is more intuitively understandable, since it ranges from 0 to 1, and thus represents the probability that two randomly chosen cells will have different associated land use codes. Both metrics increased over the 10-year period studied (table 1), and this is indicative of the landscape becoming less dominated by cropland. Rather, as can be seen in the full-page maps, a diversity of land uses became more prominent.

4 van Niekerk 4 In addition, the same indices of evenness were calculated. Evenness refers only to the distribution of area between land uses, not number of land uses. These confirm the above observation, in that both Shannon s and Simpson s evenness increased over this time period. Year Cell size (m) Number of Patches Patch Density Shannon s Diversity Simpson s Diversity Shannon s Evenness Simpson s Evenness Table 1: Summary of landscape metrics for the St. Catherines-Niagara region. Data source: Canada Land Use Monitoring Program, via GeoGratis. 2.3 Class Metrics Measures of area Both total area and percent-of-landscape area are simple measures of land use by category. The former is absolute while the latter is relative. However, in comparing the statistic in a fixed area over time, they will give identical information. Notable changes in the St. Catherines-Niagara data include the increase in urban area, the decrease in cropland and orchards/vineyards, and the increases in productive and nonproductive woodland (figure 1). While a good starting point, these metrics are uninformative as to how the transitions are occurring. For this information, the transition matrix must be consulted (table 5). In comparison to total area, it can be seen that land uses tend to become more fragmented as total area is lost. For example, agricultural land became more fragmented, occupying over 16% of the landscape in 1966, with 444 patches, but decreasing to under 4% of the landscape in 1976, while almost doubling patch number. With increasing fragmentation comes increased total edge. Total edge refers to the length of the boundary of patches of the land use. In an ecological context especially, increased edge degrades habitat, since more area is subject to edge effects. This can change the ecological processes of the environment. For example, there is increased access to light at forest edges, and thus species composition may be altered. Furthermore, natural habitat which borders on urban areas may be more prone to invasion by ornamental species. Another metric of fragmentation is the patch cohesion index, which measures how contiguous the patches of a specific land use are. It ranges from 0 to 100. Ecologically, cohesion is important for the distribution of species a contiguous area is necessary for species to disperse in the event of a disturbance. Island Biogeography Theory states that smaller patches that are further away from other patches will have decreased species richness. Notable

5 van Niekerk 5 Class Area % Lndscp. # Patches Total edge T. Core A. Patch Cohsn. Water areas Cropland U/I pasture & range Orchards and vineyards Urban built-up area Productive woodland Non-productive woodland Horticulture Swamp marsh or bog Outdoor recreation Mines etc Unproductive land - rock Unproductive land - sand Table 2: Full FRAGSTATS results for the St. Catherines-Niagara data, 1966, 100m cell size. Class Area % Lndscp. # Patches Total edge T. Core A. Patch Cohsn. Water areas Cropland U/I pasture & range Orchards and vineyards Urban built-up area Productive woodland Non-productive woodland Horticulture Swamp marsh or bog Outdoor recreation Mines etc Unproductive land - rock Unproductive land - sand Table 3: Full FRAGSTATS results for the St. Catherines-Niagara data, 1966, 500m cell size.

6 van Niekerk 6 Class Area % Lndscp. # Patches Total edge T. Core A. Patch Cohsn. Water areas Cropland U/I pasture & range Orchards and vineyards Urban built-up area Productive woodland Non-productive woodland Horticulture Swamp marsh or bog Outdoor recreation Mines etc Unproductive land - rock Unproductive land - sand Table 4: Full FRAGSTATS results for the St. Catherines-Niagara data, 1976, 100m cell size.

7 van Niekerk 7 changes in cohesion index are the decrease in cohesion of orchards and vineyards, cropland and horticultural land, as well as the increase in cohesion of non-productive woodland and unimproved pasture and range land (figure 3). While cohesion is a more sophisticated measure of fragmentation, it does tend to increase with a simple increase in area allocated to a specific land use. Figure 1: Land use in the St. Catherines-Niagara area from Data source: Canada Land Use Monitoring Program, via GeoGratis. 2.4 Transition Matrix The transition matrix (table 5) is a more detailed description of the changes in land use, since it does not merely report an increase or decrease in area, but also contains information concerning how commonly one land use transitions to another land use. The transition matrix can also be used to describe a first-order Markov model (Muller and Middleton, 1994). This allows prediction of future changes in land use, given the current composition of the landscape, and assuming continued operation of current patterns. Using the transition matrix, it can be seen, for example, that non-productive woodland is being lost to a variety of other land uses, but that it is also gaining new area from other land uses. This gives a more detailed picture than the earlier observation that woodland increased in area. The fact that only 41% of the original non-productive woodland remained assigned to this land use code by 1976 indicates that much of the non-productive woodland in the area was less than 10 years old in 1976, which could not be inferred from aggregated aspatial data. The instability of various natural land uses is of concern because of the time taken to establish ecological communities, and the presence of different successional stages. Instability of human-managed land uses is of a different nature, since commercial investment

8 van Niekerk 8 Figure 2: Land use in the St. Catherines-Niagara area in 1966, using 100 m and 500 m raster resolution. Data source: Canada Land Use Monitoring Program, via GeoGratis. Figure 3: Land use cohesion in the St. Catherines-Niagara area from , using 100 m raster resolution. Data source: Canada Land Use Monitoring Program, via GeoGratis.

9 van Niekerk 9 Figure 4: Land use class total edge in the St. Catherines-Niagara area from , using 100 m raster resolution. Data source: Canada Land Use Monitoring Program, via GeoGratis. may offset the time required to transition to a fully functional land use, while natural land uses vary greatly due to age. 3 Conclusion During the period , the St. Catherines-Niagara area saw a shift in land use away from agricultural land towards a variety of industrial, urban and natural land uses. This shift has led to a greater diversity of land use and increased fragmentation of many land uses. Using a Markov model approach, it was shown that many of the land uses in the area are unstable, i.e. while are may be conserved or even gained, specific patches are not necessarily preserved. This may be problematic, especially for natural land uses, as early vs. late successional communities have diverging ecological behaviour.

10 van Niekerk 10 Cr Ho Im Mi No Or Ou Pr Sw Uni Unm Unp-r Unp-s Ur Wa (empty) Cropland Horticulture Imp. Pasture Mines NP Woodl Orch. & Vin Outdoor rec Pr. woodland Swamp etc U/I Pastr Unmapped Unp rock Unp sand Urban Water Table 5: Transition matrix showing percentage transition from the land use indicated in the first column to the land use indicated in the first row, from 1966 to 1976.

11 van Niekerk 11 4 References Hansen, J.A.G. (1984). Canadian small settlements and the uptake of agricultural land, Social Indicators Research 15(1): Muller, M.R. and J. Middleton. (1994). A Markov model of land-use change dynamics in the Niagara Region, Ontario, Canada. Landscape Ecology 9(2): UMass Landscape Ecology Lab. (2012). FRAGSTATS Metrics. [ Accessed January 30, 2012.