The biodiversity model measured the change in potential habitat area for a species in each future scenario and the 1850 Land cover map by calculating the ratio of future or past habitat area to the present habitat area, using the present as the baseline for comparison. The water quality model, a non-point source GIS model, simulated a series of five storm events to calculate the mean pollutant load for each of the five possible futures, 1990 and 1850 Land use/Land cover maps. The model assessed flows, and non-point source sediment levels of total suspended solids, phosphorous and nitrate, using field data collected from two storm event flows and base line flows monitored in 1996.
There are many ways to evaluate the possible futures generated by the stakeholder group. The choice of evaluation models was constrained by existing data about the area in question, and a desire to use these models as broad measures of environmental health.
Costanza and Sklar (1985) have noted that mathematical models such as the evaluative models used in this project can be rated according to three criteria:
They argue that it is not possible to simultaneously optimize both articulation and accuracy, and that an effective model must balance the two:
"In the past, scientists have tended to narrow their questions in order to achieve higher accuracy. This leads to models with low articulation but high descriptive accuracy. They say much about little. More recently, scientists have begun to take a 'systems view' that looks at phenomena more comprehensively. This strategy leads to highly articulated models with low accuracy. These models say little about much."
In addition to these criteria, the effectiveness of scientific evaluative models used within a public forum is dependent on their ability both to predict and to explain differences between the possible futures. In the context of decision-making by an informed lay audience, the "explanatory power" of a model is not merely a technical matter: it can be thought of as a form of communication between the authors of a model and its intended audience. If the results of an evaluation model are lost on its audience, the model is of little practical use.
The evaluation models developed in this project were designed to be as spatially and categorically articulate as possible, within the constraints of available data. Results were then spatially or categorically aggregated to the degree deemed necessary to meet our accuracy goals.
In the context of strategic planning, an evaluation model must be able to defensibly distinguish between possible futures, so required accuracy is a function of possible landscape change, as well as of spatial scale. Even a model of low articulation could distinguish between two radically different possible futures. The landscape changes explored by the stakeholder group were partially constrained by the number of categories used in the land use / land cover maps and by our ability to describe the impacts of these potential transitions, but more importantly they were constrained by their sense of what is possible in this watershed in the next 30 years.
In order to be useful in landscape planning, evaluation models must be spatially explicit at a level of articulation which can be affected by the planning process in question. In our case, this meant that the evaluation models had to be spatially articulate at the scale of sub-basins within the Western Muddy Creek watershed. Because many land use design decisions are made at the parcel scale, it would be preferable to have evaluative models which operate at that scale, but data constraints made this impractical to do within this study.
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| Figure 15: Changes in Native Species Richness from Present to High Development Future | Figure 16: Changes in Native Species Richness from Present to Moderate Development Future | Figure 17: Changes in Native Species Richness from Present to Plan Trend Future | Figure 18: Changes in Native Species Richness from Present to Moderate Conservation Future | Figure 19: Changes in Native Species Richness from Present to High Conservation Future | Figure 20: Changes in Native Species Richness from Present to 1850s Survey |
Maps of the Muddy Creek watershed were constructed showing changes in species richness (number of species) for each possible future (and the past), compared to the present. For each future or past map, the number of species present in each pixel of habitat for the future (or past) scenario was subtracted from the number of species present in the same pixel in the present. A positive number indicates a gain in species richness, while a negative number indicates a loss in species richness. These species richness change maps aid in the identification of landscape changes that contribute most to changes in species richness in the futures (and past).
| Figure 11 |
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The average risk of habitat loss for the 214 native vertebrate species (excluding extirpated species) is highest in the High Development future, with lower risk in the Moderate Development and Plan Trend, and improvement in the Moderate and High Conservation and the Pre Settlement past. The number of native species at risk varies for each future scenario: 75% of native species are at risk in the High Development future, decreasing to 69% in the Moderate Development future and 56% in the Plan Trend future, with only 31% at risk in the Moderate Conservation future, and 40% at risk in the High Conservation future. A similar proportion, 42% are "at risk" in the Presettlement land cover past.
In summary, the average risk to all 214 native species is lowest in the Moderate and High Conservation futures and the number of species at risk is also smallest in the Moderate and High Conservation futures. This overall trend of greater risk with development and less risk with conservation is also reflected in trends within individual species: 39% (83/214) of native species show a steady trend of increasing or level risk with increased development, while only 14% (29/214) show a steady trend of increasing or level risk with increasing conservation. The High Development scenario is a greater threat to habitat loss and resulting loss of biodiversity than the other futures.
Grouping the species by their status (e.g. rare, introduced, extirpated) also shows that there is a correlation between some groups' status and their magnitude of risk. The introduced species (I) are at risk in all the futures, but also show a trend towards more risk in the conservation futures, which is consistent with their preference for human-dominated (developed) landscapes. The extirpated (E), rare (R), and vulnerable (V) species show the common trend of high risk with development and improvement with conservation, with improvement (more habitat) in the Pre Settlement past compared to today (figures 11 , 15-20 ).
The water quality model, calibrated by field measured values of pollution loads from the two monitored storm events and baseline flows from previously recorded field monitoring, uses the different possible future scenarios' land use/land cover data as the variable in the five simulated storm events. The model results for the five possible futures, and 1850 vegetation land cover are all reported in relation to 1990 values, the baseline data set.
Surface water runoff volume, a critical factor in estimating pollution loads, generally increased with increasing development. The 1990 landscape was used as the baseline data set, to examine changes in water volume in each future. The amount of discharge from the watershed increased from the High and Moderate Conservation futures to the Moderate and High Development futures. The amount of discharge from the 1850 vegetation decreased from the 1990 baseline conditions. Most of the increase in runoff was seen in the southern end of the watershed in the moderate and high development scenarios, associated with increased residential development located there under those scenarios. By contrast, in the moderate and high conservation scenarios, relatively low impact to water discharge was observed. The most dramatic changes are seen in the area around the town of Alpine under Plan Trend, and the High Development possible future.