Geology ReportsSearch

USGS · 70039723

Mapping outdoor recreationists' perceived social values for ecosystem services at Hinchinbrook Island National Park, Australia

Abstract

Coastal ecosystems are increasingly faced with human impacts. To better understand these changing conditions, biophysical and economic values of nature have been used to prioritize spatial planning efforts and ecosystem-based management of human activities. Less is known, however, about how to characterize and represent non-material values in decision-making. We collected on-site and mailback survey data ( n = 209), and analyzed these data using the Social Values for Ecosystem Services (SolVES) GIS application to incorporate measures of social value and natural resource conditions on Hinchinbrook Island National Park, Australia. Our objectives in this paper are to: 1) determine the spatial distribution and point density of social values for ecosystem services; 2) examine the relationship between social values and natural resource conditions; and 3) compare social value allocations between two subgroups of outdoor recreationists. Results suggest that high priority areas exist on Hinchinbrook's land and seascapes according to the multiple values assigned to places by outdoor recreationists engaged in consumptive (e.g., fishing) and non-consumptive (e.g., hiking) activities. We examine statistically significant spatial clustering across two subgroups of the survey population for three value types that reflect Recreation, Biological Diversity, and Aesthetic qualities. The relationship between the relative importance of social values for ecosystem services and spatially-defined ecological data is explored to guide management decision-making in the context of an island national park setting.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Carena J. van Riper, Gerard T. Kyle, Stephen G. Sutton, Melinda Barnes, Benson C. Sherrouse. 2012. Mapping outdoor recreationists' perceived social values for ecosystem services at Hinchinbrook Island National Park, Australia. https://doi.org/10.1016/j.apgeog.2012.06.008

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Estimating forest canopy cover dynamics in Valles Caldera National Preserve, New Mexico, using LiDAR and Landsat data

Increasing tree canopy cover has led to increasing wildfire activity in conifer dominated areas of the southwestern United States. Estimating historical changes in the spatial distribution of tree canopy cover can provide further insights into the dynamics of forest and fuel conditions in these landscapes and help prioritize areas for restoration to mitigate wildfire risks and restore biological functioning. In this study, we explored the relationship between LiDAR derived canopy cover data and Landsat reflectance values, and derived a model to estimate percent canopy cover (PCC) on historical Landsat data from 1987 to 2015 for the Valles Caldera National Preserve (VCNP), located in the southwest Jemez Mountains of New Mexico. We developed a regression model between LiDAR generated canopy cover collected in June 2010 and Landsat Thematic Mapper (TM) reflectance values (bands 1–7 except band 6) and vegetation indices collected for the same date. About 5% (17,000) of the total LiDAR points (329,102) were used as training points and a separate, non-overlapping set of 17,000 points as test points to validate the regression model. A simple linear model with the red band (band 3; R 2 = 0.70) was selected as the best model to predict PCC in the rest of the images for 1987–2015. In general, we found a strong consistency between the spatial dynamics of modelled tree canopy cover based on historical Landsat data, wildfire events and forest management practicesthat occurred during the same period. Results showed that about 11% of the study area experienced an increase in PCC for the period of 1987–2015 while 41% of the study area experienced a reduction in PCC during the same time period, mostly in the areas which were affected by stand replacing wildfires in 2011 and 2013. The results indicate an overall increase in medium and high canopy cover classes in specific regions of the study area, which could lead to hazardous wildfires such as those in 2011 and 2013. In the context of ongoing ecological restoration of these montane forests, predicted PCC of contemporary forests could help local managers to identify the areas in the need of immediate restoration efforts by focusing management practices on the areas with closed canopy.

New Mexico

The sensitivity of ecosystem service models to choices of input data and spatial resolution

Although ecosystem service (ES) modeling has progressed rapidly in the last 10–15 years, comparative studies on data and model selection effects have become more common only recently. Such studies have drawn mixed conclusions about whether different data and model choices yield divergent results. In this study, we compared the results of different models to address these questions at national, provincial, and subwatershed scales in Rwanda. We compared results for carbon, water, and sediment as modeled using InVEST and WaSSI using (1) land cover data at 30 and 300 m resolution and (2) three different input land cover datasets. WaSSI and simpler InVEST models (carbon storage and annual water yield) were relatively insensitive to the choice of spatial resolution, but more complex InVEST models (seasonal water yield and sediment regulation) produced large differences when applied at differing resolution. Six out of nine ES metrics (InVEST annual and seasonal water yield and WaSSI) gave similar predictions for at least two different input land cover datasets. Despite differences in mean values when using different data sources and resolution, we found significant and highly correlated results when using Spearman's rank correlation, indicating consistent spatial patterns of high and low values. Our results confirm and extend conclusions of past studies, showing that in certain cases (e.g., simpler models and national-scale analyses), results can be robust to data and modeling choices. For more complex models, those with different output metrics, and subnational to site-based analyses in heterogeneous environments, data and model choices may strongly influence study findings.

Applied Geography

Sensitivity of tsunami evacuation modeling to direction and land cover assumptions

Although anisotropic least-cost-distance (LCD) modeling is becoming a common tool for estimating pedestrian-evacuation travel times out of tsunami hazard zones, there has been insufficient attention paid to understanding model sensitivity behind the estimates. To support tsunami risk-reduction planning, we explore two aspects of LCD modeling as it applies to pedestrian evacuations and use the coastal community of Seward, Alaska, as our case study. First, we explore the sensitivity of modeling to the direction of movement by comparing standard safety-to-hazard evacuation times to hazard-to-safety evacuation times for a sample of 3985 points in Seward's tsunami-hazard zone. Safety-to-hazard evacuation times slightly overestimated hazard-to-safety evacuation times but the strong relationship to the hazard-to-safety evacuation times, slightly conservative bias, and shorter processing times of the safety-to-hazard approach make it the preferred approach. Second, we explore how variations in land cover speed conservation values (SCVs) influence model performance using a Monte Carlo approach with one thousand sets of land cover SCVs. The LCD model was relatively robust to changes in land cover SCVs with the magnitude of local model sensitivity greatest in areas with higher evacuation times or with wetland or shore land cover types, where model results may slightly underestimate travel times. This study demonstrates that emergency managers should be concerned not only with populations in locations with evacuation times greater than wave arrival times, but also with populations with evacuation times lower than but close to expected wave arrival times, particularly if they are required to cross wetlands or beaches.

Applied Geography