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A Review of the Florida Keys Carrying Capacity Study 9 Terrestrial Module The Terrestrial Module is a series of spatially explicit models that measure impacts from changes in land use categories. Impacts are measured as changes in habitat area, direct and indirect effects on an index of species richness, and direct effects on habitat requirements for seven single species. In general, the Terrestrial Module is both simple and straightforward, and can assist in evaluating impacts on terrestrial ecosystems and species and in guiding future land use in the Florida Keys. The apparent simplicity of the models in this module belie the amount of effort that went into their creation, and the contractors at URS Corporation, Inc., are to be congratulated for their efforts. The brief and effective narrative of the history of habitat fragmentation makes it clear that so much habitat has been lost that the majority of damage from development has already been done to the Florida Keys terrestrial ecosystems and communities. It is not surprising, therefore, that the Smart Growth scenario describes minimal or negligible changes in the module’s numerical outputs. From the outset of their work on this module, the contractors have described their intention to measure impacts using a GIS to depict shifts in land use categories. They have indeed produced a system that maps and measures changes in the space occupied by single species or groups of species (as measured by their species richness outputs) given changes in land use categories. In doing so, the contractors recognize that certain arbitrary assumptions were made regarding shifts in conditions or circumstances. Once these arbitrary assumptions and their limitations are understood and accepted, the module can be seen to meet its intended objectives.
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A Review of the Florida Keys Carrying Capacity Study The contractors did an excellent job of summarizing existing ecological and natural history for both ecosystems and specific species in the document prepared as part of Delivery Order #2 for Tasks 3, 4, 6, and 7 (URS Corporation, Inc., 2000). While this information provides useful background material, it is clear that most of it could not be incorporated into model elements for the module given the degree of technical information available. The module’s habitat model is very straightforward, resulting in an easy-to-follow set of outputs: the number and size of habitat patch fragments. This model calculates the number and size of patches after land use changes have occurred and presumes that more and smaller habitat patches indicate increased habitat fragmentation, a worsening of conditions for terrestrial ecosystems and species. The narrative uses an appropriate level of scientific references to fully justify this approach in the Draft CCAM report. Outputs include summary statistics as well as detailed tables of changes in habitat types (e.g., freshwater marsh, mangrove, hammock). Seventeen species are used to calculate the measures of species richness. Individual species chosen are all well studied, and the bibliography and previous deliverables include extensive references on their habitat requirements. URS Corp has made a strong effort to include species whose habitat requirements cover the complete range of habitat types, including upland hardwood and pine forests, mangrove forests, fresh water communities, and coastal herbaceous communities, including dunes. The existing models were developed by the Florida Fish and Wildlife Conservation Commission, the United States Fish and Wildlife Service, or both, to evaluate habitat use and habitat requirements, and they are sensitive to critical habitat types measured in the module. Important changes in land use in any traditional Florida Keys species’ habitat type are incorporated in the model. For many of these models the contractors made an additional effort to reduce grid size to a 30 by 30-ft grid cell system for evaluating changes in land use. Direct impacts due to changes in land use are measured using the change in the sum of the number of species present in every habitat patch based upon the habitat requirement models. The attempt to develop an indirect impact measure for species richness using a Relative Habitat Degradation Index (RHDI) was less successful (see below). Finally, GIS overlay analysis is used to evaluate the direct effects on the published habitat requirements of seven single species: the Lower Keys marsh rabbit, the white-crowned pigeon, and five forest interior bird species. Habitat requirement models for the rabbit and pigeon incorporated multiple factors, while those for the five forest interior birds were based solely on the minimum hammock patch size requirements given in published studies. The model presumes that a species is extirpated from a patch when size and/or conditions are reduced below the minimum standard as set in the existing models for that the species. Effects of land use changes are thus measured using change in the number of patches and total acres of habitat available for each species.
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A Review of the Florida Keys Carrying Capacity Study Much of the potential criticism of this module could focus on the lack of dynamic measurements of processes, the lack of connections between land use and other types of human population impacts, the use of a constant decay coefficient for indirect impacts for each land use type, and the lack of temporal modifiers, such as lag times. The amount of background material that the contractors reviewed in Delivery Order # 2 (URS Corporation, Inc., 2000) and in the Draft CCAM report might suggest that the development of much more sophisticated models may have been possible. It is easy to see that attempts to add such process-oriented functions and/ or temporal conditions to the models would have resulted in even more assumptions and complications. URS Corp’s approach may not have resulted in the most sophisticated models possible, but the results produced are easy to comprehend. The recommended correction of the RHDI will allow this module to remain straightforward while allowing it to provide a better measure of the impacts of development on species remaining in habitat fragments. MAJOR CONCERNS Limitations and Assumptions The overarching criticism of this module must be its lack of clarity with regard to the limitations and arbitrary assumptions used in the component models. Explicitly stating and discussing these limitations and assumptions in the CCAM narrative can readily solve most of these problems. Status of Vacant Land The contractors produced a clear and effective database for the GIS analyses based upon the Florida Marine Research Institute’s Advanced Identification of Wetlands (ADID) map, along with historical aerial photographs and ground-truthing at random points (URS Corporation, Inc., 2001c). The remote mapping approach, however, is not able to detect variation in the quality of natural habitat in large contiguous patches or remaining habitat on portions of developed lots. Exotic pest plant invasion, feral cat populations, trash, and other human related impacts have degraded some of this habitat. A major concern is that the mere switch in land use classification from “vacant land with buildable lots” to “open space purchased by a conservation organization” does not automatically make this land good habitat regardless of the ADID cover code. If this ‘open space’ habitat is not really very good, as measured using some independent method other than the ADID label, then the results may be misleading or unrealistic. The problem with the actual status of vacant lots cannot be addressed without an updated inventory of the status of natural habitat lands and “vacant land with buildable lots” and developing a classification system for the relative costs and
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A Review of the Florida Keys Carrying Capacity Study lag times (or recovery times) required for restoration. Since such additional data collection is outside of the scope of work of the project, it seems most reasonable to simply recommend that the narrative section identify this uncertainty as one of the module’s limitations. Sea Level Rise (SLR) The use of a historical approach to establish the magnitude and distribution of change in terrestrial habitat is valuable in recognizing the extent of the human manipulation of the cover within the span of a few centuries. It is important, however, to recognize that the natural system is undergoing changes during this same time period and that human alteration of the landscape will occur with natural system dynamics to limit recovery of some of the island habitats in the growth scenarios. An important variable in all coastal environments is rising sea level. Data from the Key West tide gauge on a web-site maintained by the National Oceanic and Atmospheric Administration (NOAA) indicate that the rate of SLR is 2.3 mm/yr for the past 90 years. According to Wanless et al. (1994), this rate is about six times the mean rate of rise during the past 3200 years and is causing a breakdown in the coastal habitats created during an earlier slow rate of rise. Furthermore, the rate of SLR is expected to increase in the twenty-first century (National Research Council, 1987; Titus and Narayanan, 1995) with continuing modification of shoreline habitats, and increased exposure to hurricane surge and inundation throughout the Keys. Hardening of the shoreline by bulkheads, walls, and roadbeds, and the emplacement of landfill at the water’s edge in the Keys is placing an artificial barrier on the migration of near-shore habitats of mangrove and marshland and will therefore limit space for recovery of these lowland resources (Wanless et al., 1994; Titus, 1998). The result is that the landscape cannot revert to a predisturbed condition when it is converted to public land because the topography has been altered. The historical perspective of the change in the terrestrial habitat is appropriate in the Florida Keys to portray the scale of manipulations. It is likewise appropriate to portray the scale of the change in sea level as an element in the planning for revisions of land use and habitat restoration. If relationships between sea level rise and shifts in habitat status and quality cannot be accomplished based upon the data available, then the module should emphasize the above limitations in a narrative section. Fiscal Consequences of Scenarios as Outputs In both the Terrestrial and the Fiscal Modules, the implications of the assumptions about shifts in land use categories to “conservation lands” must be made clear. The amounts of money that would be required to purchase, restore,
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A Review of the Florida Keys Carrying Capacity Study and manage all of the vacant land presumed to be “100% restored” in a scenario need to be made explicitly clear in the narrative, and should be listed as explicit outputs in the Draft CCAM’s Fiscal Module. Decay Coefficients for Habitat Degradation In an effort to extend the species richness model and make it sensitive to the indirect impacts of various adjacent land use practices, the contractors included a modifier called the Relative Habitat Degradation Index (RHDI). The contractors thoroughly reviewed the scientific literature and mentioned in brief the complexities and diversity of opinions regarding the nature and distances from natural habitat at which various types of human activities would impact wildlife (URS Corporation, Inc., 2000; Table 3.16 of Draft CCAM). They could not, however, find a method for incorporating all that information into a single set of decay coefficients for land use categories. In the Draft CCAM, a set of constant decay coefficients for land use categories was taken from studies in which impacts were measured as changes in emergy in landscape development (the contractors cite a number of reports by Brown et al.). While the work on emergy is both detailed and scientifically valid, there are serious problems with its use in this model for the purpose of evaluating habitat degradation for a suite of 17 species. The contractors listed no refereed, published reports on the use of this measure, in this particular fashion, and the validity of using emergy to measure the effects of adjacent land uses and human activities such as noise pollution, house cats, and automobiles on wildlife is currently unknown. The decay coefficients chosen resulted in impacts dissipating at very short distances (e.g., 90% decay at 35.5 feet for low density residential and 211 feet for a 4-lane highway). These short distances are at odds with the many distances quoted in the extensive literature review used in the Draft CCAM narrative. As it stands now, the RHDI does not realistically track the distances most types of impacts are actually thought to travel. Alternative decay coefficients based upon recognized midrange or modal distance values for major types of impacts such as microclimate, noise pollution and/or habitat buffer zones might be considered. The contractors are currently trying to find an alternative set of decay coefficients. If they cannot, the Committee recommends deleting the indirect impact model for species richness from the Draft CCAM. Removing this measure will not severely alter the use of the species richness measure, since the difference between direct and indirect impacts noted in the model runs for scenarios is a constant (Draft CCAM Tables 4.20–4.21). Habitat Degradation Index and Human Population The use of constant decay coefficients for the measurement of the RHDI is inappropriate for at least some of the land use types, including recreational/open
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A Review of the Florida Keys Carrying Capacity Study space, commercial and two and four lane highways. These land use types could be expected to have increasing indirect impacts on adjacent conservation lands due to increases in the functional human population that are not captured in a static decay coefficient. The Committee does not feel that the current method of measuring functional human population in relation to land use categories does an effective job of capturing the increasing numbers of day-trippers and their impact on and near recreational lands. Since recreational lands are frequently in or adjacent to “conservation lands,” such an impact is important. Again in this case, it would be better to delete the use of the RHDI and the indirect impacts element of the model. Habitat Requirements of Single Species Results of model runs for the Lower Keys marsh rabbit and the white-crowned pigeon clearly identify losses in additional habitat from changes in land use categories, even in the Smart Growth scenario. The contractors were recalculating the results for the forest interior birds in the Draft CCAM at the time of this review due to inconsistencies between the text and Table 4.22 of the Draft CCAM. It is expected, however, that these simple GIS overlay analyses of habitat requirements should also show clear, if small, effects in the Smart Growth scenario run as well. Florida Key Deer This species was excluded from the module’s single species element because a detailed habitat conservation plan for future land development and management now exists for the Florida Key deer. One of the 17 species included in the species richness model, the deer’s habitat requirements were taken into consideration to some extent. Carrying capacity discussions revealed, however, that the species’ popularity and prominence meant that its inclusion as a single species had been expected and would improve the model’s appeal. Including the Key deer into the CCAM’s final single species element should be a simple task. Species-Area Habitat and Thresholds The species-area habitat equation, along with its threshold values, is vaguely referenced in Appendix C of the Draft CCAM (Draft CCAM Section 6.0) as being calculated based upon equations 167 and 169. It is presumed that this equation was deleted from the text purposefully, in which case the equation and threshold should also be deleted from the appendix. If not, some significant explanatory text for the equation must be added to the main text of the Final CCAM report. As mentioned in other parts of this review, color-coded thresholds should either be completely deleted from the CCAM or should be able to be user-defined.
Representative terms from entire chapter: