A Use of the Theory of Planned Behaviour to Determine the Social Barriers to the Implementation of Stormwater Green Infrastructure on Private Properties in Dundas, Hamilton, Ontario

Climate change has resulted in more extreme rainfall events and most municipalities’ stormwater infrastructure is not prepared to deal with the increased flooding instances that may be associated with the increased rainfall. Updating inferior stormwater infrastructure would put a strain on municipalities’ budgets and require space that is not readily available. A potential option for municipalities is to implement green infrastructure options such as green space, green roofs and bioretention swales. Municipalities may be able to construct some green infrastructure options on publically owned space, however most of the responsibility for implementation will fall on private residents. Previous research has investigated methods of motivating private residents in the implementation of green infrastructure, however very little research has been done on whether residents respond to motivation and what the social barriers to implementation are. This project study focused on three neighbourhoods in the Town of Dundas (Hamilton, ON, Canada) as a case study. Dundas is in a position of pronounced flooding risk because of its location at the valley bottom of a break in the Niagara Escarpment and its past history of flooding. Through a partnership with the Hamilton Conservation Authority, this study used a questionnaire to attempt to elucidate the social barriers to the implementation of green infrastructure on private properties. The questionnaire was theoretically informed using the Theory of Planned Behaviour and analyzed using partial least squares path modelling. The results indicated that behavioural beliefs, attitude, normative beliefs, subjective norm and perceived behavioural control all contributed to the participant’s intention to install green infrastructure and ultimately their final behaviour. The model was able to predict 57% of the variance in intention, based on the associated constructs. Subjective norm contributed the strongest to intention with a path coefficient of 0.542. Attitude had the weakest contribution to intention with a path coefficient of 0.034. Individual question results indicated that time and finances were not statistically significant barriers to the implementation of green infrastructure on private properties. A comparison between the neighbourhoods showed no significant differences in questionnaire answers between any of the three neighbourhoods, however there were differences in income and response rate between the three neighbourhoods. The results from this study can be used to help conservation authorities and municipalities develop engagement and education programs to promote the use of green infrastructure on private properties in order to mitigate the negative effects of climate change

Predicting potential global distributions of two Miscanthus grasses: implications for horticulture, biofuel production, and biological invasions.

In many regions, large proportions of the naturalized and invasive non-native floras were originally introduced deliberately by humans. Pest risk assessments are now used in many jurisdictions to regulate the importation of species and usually include an estimation of the potential distribution in the import area. Two species of Asian grass (Miscanthus sacchariflorus and M. sinensis) that were originally introduced to North America as ornamental plants have since escaped cultivation. These species and their hybrid offspring are now receiving attention for large-scale production as biofuel crops in North America and elsewhere. We evaluated their potential global climate suitability for cultivation and potential invasion using the niche model CLIMEX and evaluated the models' sensitivity to the parameter values. We then compared the sensitivity of projections of future climatically suitable area under two climate models and two emissions scenarios. The models indicate that the species have been introduced to most of the potential global climatically suitable areas in the northern but not the southern hemisphere. The more narrowly distributed species (M. sacchariflorus) is more sensitive to changes in model parameters, which could have implications for modelling species of conservation concern. Climate projections indicate likely contractions in potential range in the south, but expansions in the north, particularly in introduced areas where biomass production trials are under way. Climate sensitivity analysis shows that projections differ more between the selected climate change models than between the selected emissions scenarios. Local-scale assessments are required to overlay suitable habitat with climate projections to estimate areas of cultivation potential and invasion risk

Observed (circles) and modelled (shaded) native and introduced plant distributions.

<p>Circles indicate native (red), native inferred (yellow), introduced (green), and introduced inferred (blue) geolocations. The density of shading represents the bioclimatic suitability of a region for plant population persistence, with white areas indicating no suitability, lighter grey areas indicating low suitability, and darker grey areas indicating high suitability. (a) <i>Miscanthus sacchariflorus</i>. Geolocations: native (n = 94), native inferred (n = 171), introduced (n = 119), and introduced inferred (n = 43). (b) <i>Miscanthus sinensis.</i> Geolocations: native (n = 335), native inferred (n = 52), introduced (n = 297), and introduced inferred (n = 81).</p

Fitted parameter values used to generate bioclimatic envelope models of <i>Miscanthus sacchariflorus</i> and <i>M. sinensis</i> distributions using CLIMEX.

a<p>Proportion soil capacity.</p>b<p>°C.</p>c<p>Week⁻¹.</p>d<p>°D.</p

Areas of agreement and disagreement in the projected potential distribution of <i>Miscanthus sacchariflorus</i> and <i>M. sinensis</i> (all area classified as suitable, favourable, and highly favourable, or EI >10) as modeled by CLIMEX.

<p>The upper model shows areas of agreement between the BCM and CGCM models for a given scenario and year. The lower panel shows areas of agreement between the A2 and B1 scenarios for a given model and year. Areas shown in blue indicate suitable climate under both projections; areas shown in red indicate that only one of the two projections predicts suitable climate.</p

Percent change in climatically suitable area for the World and for North America projected using the BCM and CGCM models and the A2 and B1 emissions scenarios relative to the baseline projections.

<p>The column EI>10 (bold) indicates a composite analysis combining all area classified as suitable, favourable, and highly favourable for each species.</p

Sensitivity analysis results for <i>Miscanthus sacchariflorus</i> and <i>M. sinensis</i> indicating the proportional change in area from that of the baseline model global distribution for each category of ecoclimatic index (EI) modelled using CLIMEX software.

a<p>Parameter value used in the sensitivity analysis. The percent change from the original model parameter value was 10%, except for temperature variables, which were changed by 1°C and for which percent change is indicated in parentheses. Changing temperature variables by 10% gave qualitatively similar results (data not shown).</p><p>Parameter values were each decreased and increased by 10% from the baseline value (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0100032#pone-0100032-t001" target="_blank">Table 1</a>) unless indicated otherwise^a. Changes in area that exceed the percent change in parameter value are shown in boldface font; positive and negative proportions respectively indicate increases and decreases in area.</p

Projected changes in the global climatically suitable area for <i>Miscanthus sacchariflorus</i> and <i>M. sinensis</i> under the BCM and CGCM models run using the A2 and B1 scenarios.

a<p>Potential future suitable area is defined as EI>10.</p>b<p>Overlap is calculated as the portion of the baseline range that overlaps with the projected range.</p

The index of agreement^a between different models run under the same scenario and between different scenarios run within the same model, for projected distributions of <i>M. sacchariflorus</i> and <i>M. sinensis</i> in 2050 and 2080.

a<p>The index is calculated as the ratio of the area of overlap between the two projections to the area of non-overlap.</p