NZ population projections through to 2030
For SARINZ
By: Gordon Cessford & Bronek Kazmierow B Kazmierow – Recreation and Tourism Consulting Origins
Sponsors: ◦ SARINZ ◦ NZ Oil and Gas
Supporters - SARINZ stakeholders and broader network
2 Aim: Identify foreseeable patterns & trends in SAR incidents operational responses through to 2030
Primary objectives: Assess how SAR volunteer response will be affected by projected population changes Identify changes in the nature of SAR callouts over the next 20 years Identify how these will impact training needs
3 1. Approach ◦ Model 2. Demand: NZ population 3. Key demographic profiles & projections ◦ Aged & tourism 4. Supply ◦ Agency profile contrasts: Surf v. AREC Coastguard v. LandSAR 5. Incident type profiles 6. Trends 7. Summary ◦ Recommendations
4 Develop and apply a conceptual model
Analyse relevant secondary data sources demographic projections incident records other information sources review of relevant literature
Undertake projections
5 Demand factors Incident profiles – general and targetted Forecasts ○ tourism/recreation ○ other (including census population, age, ethnicity)
Supply factors Volunteer profiles and projections
Outcomes Equilibria or tension? Directions of change Implications for response
6
DEMAND FACTORS OVERALL SAR SUPPLY FACTORS OUTCOMES Overall NZ population demographic characteristics and projections
SAR call-out demographic SAR volunteer demographic characteristics – national , profiles – national, regional and regional and targeted segments targeted segments Projections and trends Projections and trends - related to recreation SAR - related to profiles of different call-out profiles SAR volunteer segments (e.g. - related to non-recreation Surf-lifesaving, amateur radio SAR call-out profiles operators, LandSAR search etc)
NZ recreation – SAR capability/capacity – participation, preferences, existing features & trends profiles and capabilities - National and regional patterns -National and regional EQUILIBRIA or TENSION - Volunteer training, patterns Resulting from the interaction retention, recruitment status -Forecast trend between DEMAND amd and implications SUPPLY factors NZ tourism -activity patterns and trends - international and domestic tourists The INITIAL RESULTS are baseline levels and patterns Supply of SAR incidents Actions Demand Actions
The LONGER TERM OUTCOMES are future readiness, effectiveness and efficiency of SAR response 7 Census ◦ Regional distribution ◦ Projections Regional populations Age and dependency ratios
8 Auckland Region 32.35% 21.94%
Canterbury Region 12.96% 11.49%
Wellington Region 11.15% 8.43%
Waikato Region 9.50% 9.31%
Bay of Plenty Region 6.39% 14.71%
Manawatu-Wanganui Region 5.52% -2.77%
Otago Region 4.81% 4.71%
Northland Region 3.69% 8.33%
Hawke's Bay Region 3.67% 3.50%
Taranaki Region 2.59% -2.31%
Southland Region 2.26% -6.41%
Tasman Region 1.11% 17.52%
Gisborne Region 1.10% -2.81%
Nelson Region 1.06% 6.48%
Marlborough Region 1.06% 10.84%
West Coast Region 0.78% -3.64%
Area Outside Region 0.02% -17.20%
-20% -10% 0% 10% 20% 30% 40%
Regional population as a percentage of NZ overall population (2006) Population change 1996-2006 9 6,000,000
5,000,000
4,000,000
North Island 3,000,000 South Island New Zealand 2,000,000
1,000,000
0 2006(3) 2011 2016 2021 2026 2031
10 Auckland region 573,700
Canterbury region 112,400
Wellington region 75,000
Waikato region 73,100
Bay of Plenty region 58,100
Manawatu-Wanganui region 7,600
Otago region 26,100
Northland region 18,600
Hawke's Bay region 6,200
Taranaki region 1,300
Southland region -5,200
Gisborne region 0
Tasman region 7,400
Nelson region 5,600
Marlborough region 5,200
West Coast region -800
0 500,000 1,000,000 1,500,000 2,000,000
2006(3) Population change 2006-2031 11 2006 2031
41.7 Marlborough region 50.9 40.3 West Coast region 47.3 40.3 Tasman region 47.3 39.4 Nelson region 44.8 38.8 Northland region 45.3 38.0 Southland region 43.4 37.9 Taranaki region 44.0 37.7 Bay of Plenty region 42.6 37.6 Canterbury region 42.3 37.5 Hawke's Bay region 43.2 36.8 Otago region 40.9 36.6 Manawatu-Wanganui … 41.2 35.8 New Zealand(1) 40.2 35.6 Waikato region 40.2 35.3 Wellington region 39.8 34.6 Gisborne region 40.6 33.7 Auckland region 37.7
20.0 25.0 30.0 35.0 40.0 45.0 50.0 55.0
Median age (years) 12 2,500,000 35,000
30,000 4,500 2,000,000 9,200 25,000 323,700 1,500,000 11,700 65+ 20,000 65+ 133,800 581,900 9,100 40–64 15,000 40–64 1,000,000 414,900 15–39 15–39 10,000 9,400 676,000 7,700 524,500 0–14 500,000 0–14 5,000 6,500 5,300 297,700 363,200 0 0 West Coast Region West Coast Region Auckland Region Auckland Region 2006 2031 2006 2031
100.0% 100.0% 90.0% 90.0% 80.0% 80.0% 70.0% 70.0% 60.0% 60.0% 50.0% 50.0% West Coast Region 2006 40.0% Auckland Region 2006 86.3% 40.0% West Coast Region 2031 Auckland Region 2031 30.0% 30.0%
54.8% 52.1% 20.0% 20.0% 54.6%
45.9% 31.5% 10.0% 30.8%
10.0% 31.7%
28.9%
21.3% 25.7% 14.2% 0.0% 0.0% Dependency Dependency Dependency Dependency Dependency Dependency ratio (total) ratio (aged) ratio (young) ratio (total) ratio (aged) ratio (young) 14 Applying the model Baseline data
Some examples Projections for dementia incidents Projections for incidents based on recreation/tourism and population forecasts
15
45
40 NZ SAR Subjects % 35 NZ 65+ SAR Subjects %
30
25
20
% of SAR subjects 15
10
5
0 Tramping Walking Other Hunting (all) SAR Subject Recreation Activities 90
80 Dementia Subjects %
70 NZ Population %
60 % 50
40
30
20
10
0 0-9 10-19 20-29 30-39 40-49 50-59 60-69 70+ Age group (10yr) 60
Dementia % 50 Recreation %
40
30
% of 65+ group age 20
10
0 65-69 70-74 75-79 80-84 85-89 90+ Age groups (5yr)
80 Dementia 70 Recreation
60
50
40
30 % of 65+ group age 20
10
0 Urban Areas Rural Town Rural Natural Urban Fringe Rural Remote Areas Farmland Natural Areas/Park Area Types
30
Dementia Subjects Incident % 25 NZ 65+ Age-group %
20
15
10 % of 65+ Age-group
5
0
BOP Nelson Otago Waikato Taranaki Tasman Auckland Northland Southland Gisborne Wellington Canterbury WestCoast Marlborough Hawkes Bay
Manawatu-Wanganui New Zealand 150 North Island 281 North Island 43 Auckland region 88 Auckland region 41 South Island 73 South Island 30 Wellington region 54 Wellington region 26 Bay of Plenty region 46 Bay of Plenty region 18 Waikato region 33 Waikato region 13 Marlborough region 25 Marlborough region 12 Manawatu-Wanganui region 20 Manawatu-Wanganui region 11 Nelson region 20 Nelson region 11 Northland region 21 Northland region 8 Canterbury region 14 Canterbury region 8 Taranaki region 13 Taranaki region 6 Otago region 10 Otago region 2 Hawke's Bay region 3 Hawke's Bay region 1 Southland region 2 Southland region 1 West Coast region 2 West Coast region 1 Tasman region 2 Tasman region 0 Gisborne region 0 Gisborne region
0 50 100 150 200 250 300 0.00 1.00 2.00 3.00 4.00 5.00 6.00 Dementia SAR callouts Dementia SAR callout index
SAR Callouts Dementia Base (4 year period 2005-09) SCDB index (per 10000 residents based on 2006 pop) Projected SCDB (4 year period 2025-2029) for over 65 year dementia series SCDBI (per 10000 residents based on 2026 pop) 22 Many 65+ SAR subjects have recreation incidents – especially Tramping and Walking in outdoor settings
But at 65+ the occurrence of non-recreation dementia incidents increases
Dementia: Over 92% urban locations near home, rare anywhere else
Closely linked to population home pattern – sustained urban SAR pressure
Tourism is a major variable in incident patterns – impact is uneven
It is independent of NZ population distribution, and impacts more in remote areas
It significantly boosts the recreation component of SAR demand
New Zealanders will keep travelling for recreation, but this may change in locations 100 NZ Subjects % 90 Tourist Subjects % 80
70
60
50
40 % Subjects of SAR 30
20
10
0 Marine SAR Subjects % Land SAR Subjects %
26 100 Recreation Incidents 90 Non-Recreation Incidents 80
70
60
50
40
% of SAR subjects 30
20
10
0 Tourist Subjects % NZ Subjects %
27 100
90 NZ Subjects %
80 Tourist Subjects %
70
60
50
40
30
% of ActivitiesSAR Recreation 20
10
0
4WD Walking Rafting Fishing Tramping Climbing Kayaking
Other Activites SkiingBoarding MountainBikingExtremeSports 28 60
50 Tourist Subjects % NZ Subjects %
40
30
20 % of typesSAR Recreation
10
0
Other Rafting Walking Fishing Tramping Climbing Kayaking Hunting Deer Mountain Biking SkiingBoarding Flying activities Top-10 SAR Recreation Incident types 100
90
80
70
60
50
40
30 % SARof SubjectsLand 20 Tourist Subjects %
10 NZ Subjects % 0
BOP Otago Nelson Tasman Waikato Taranaki Northland AucklandGisborne Southland Canterbury Wellington WestCoast Marlborough HawkesBay
ALL NZ REGIONS ManawatuWanganui 30 100
90
80
70
60
50
40
30
% of SAR subjects 20 Non-Locals % Locals % 10
0
BOP Otago Waikato Taranaki Nelson* Tasman* Gisborne* Northland Auckland Southland Canterbury Wellington West Coast Marlborough Hawkes Bay
Manawatu WanganuiIncident Regions 31 100%
90%
80%
70%
60%
50%
40%
Tourists % % of SAR subjects 30% Other Regions % Locals % 20%
10%
0%
BOP Otago Nelson* Tasman* Waikato Taranaki NorthlandAuckland Southland Gisborne* Canterbury Wellington West Coast Marlborough Hawkes Bay
Manawatu WanganuiIncident Regions 32 READ Columns down SAROP Incident Region (Column) Subject Home Hawkes Manawatu West All Auckland BOP Canterbury Gisborne Marlborough Nelson Northland Otago Southland Taranaki Tasman Waikato Wellington Region (Row) Bay Wanganui Coast Victims Overseas 6 7 25 5 3 14 15 15 12 39 39 26 25 17 5 37 22 Auckland 89 4 2 0 2 2 5 0 2 4 4 9 4 15 1 4 9 BOP 0 64 0 0 0 0 0 0 0 0 0 2 0 8 0 1 5 Canterbury 1 0 61 5 0 0 10 3 0 7 5 0 8 0 1 17 10 Gisborne 0 0 0 33 5 0 0 0 0 0 1 0 0 0 0 0 0 HawkesBay 0 0 0 19 68 2 2 0 0 0 1 0 0 2 0 0 2 ManawatuWanganui 0 2 1 5 9 50 1 0 0 1 0 3 0 1 1 0 5 Marlborough 0 0 0 0 0 0 42 0 0 0 0 0 0 0 0 0 2 Nelson 1 0 0 0 0 0 17 76 0 0 0 0 36 1 0 1 4 Northland 1 0 0 5 0 0 2 0 85 0 1 1 0 5 0 0 2 Otago 0 0 5 0 0 0 2 0 0 41 18 1 0 1 0 8 8 Southland 1 0 2 0 0 0 1 0 0 4 24 0 0 0 0 0 3 Taranaki 0 0 0 0 0 0 0 0 0 0 1 52 0 1 0 0 3 Tasman 0 0 0 0 0 0 2 6 0 0 1 1 20 0 0 1 2 Waikato 2 21 1 29 2 2 2 0 2 0 3 3 1 43 1 0 7 Wellington 0 3 2 0 12 30 2 0 0 3 2 3 4 6 91 2 15 WestCoast 0 0 0 0 0 0 0 0 0 1 1 0 1 0 0 28 2 Total column % 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 100 n= 162 191 334 21 66 254 121 34 52 359 315 145 208 366 356 248 3232
Can show where subjects in any Incident region came from
Can show where subjects from any one home region had their incidents Home Region
Auckland BOP Canterbury Incident region Auckland 94 4 3 BOP 0 69 0 Canterbury 1 0 82 Gisborne 0 0 0 HawkesBay 0 0 0 ManawatuWanganui 0 2 1 Marlborough 0 0 0 Nelson 1 0 0 Northland 1 0 0 Otago 0 0 7 Southland 1 0 2 Taranaki 0 0 0 Tasman 0 0 0 Waikato 2 22 1 Wellington 0 3 2 WestCoast 0 0 0 Total column % 100 100 100 n= 153 178 249 New Zealand North Island South Island Wellington region Wellington region Waikato region Waikato region Otago region Otago region Canterbury region Canterbury region Southland region Southland region Auckland region Auckland region West Coast region West Coast region Manawatu-Wanganui region Manawatu-Wanganui region Tasman region Tasman region Bay of Plenty region Bay of Plenty region Taranaki region Taranaki region Marlborough region Marlborough region Northland region Northland region Hawke's Bay region Hawke's Bay region Nelson region Nelson region Gisborne region Gisborne region
0 100 200 300 400 500 0 20 40 60 80 100 SAR incident callouts SAR incident callout index SCB index (per 10000 residents based on 2006 pop) SAR Callouts Base (4 year period 2005-09) Projected SCB (4 year period 2025-2029) Visitor Nights series SCBI (per 10000 residents based on 2026 pop) Visitor Night series 35 Which profile types are projected for major change in next 20 years? ◦ Dementia – national level and regional ◦ Tourism – particularly at regional level
Which regions are most likely to feel the strain?
36
For Land incidents, NZ as a whole will experience some tension, although there are some regions more affected: ◦ West Coast – major (rec. & tourism) Increased visitor incidents, dwindling volunteer capability/capacity ◦ Most other South Island regions (dementia/rec. & tourism) ◦ Auckland (dementia - although population growth may help)
37
Adaptive responses Resourcing Training Prevention & education
Caution: scale is important when interpreting patterns ◦ national vs. regional
38 Agency profiles ◦ Regional distribution ◦ Impacted also by demographic projections Regional populations Age and dependency ratios
Examples: ◦ Surf vs. AREC ◦ Coastguard vs. LandSAR
39 35 Coastguard 30 LandSAR
Surf Lifesaving 25 AREC
20 NZ Population %
15
10
5
0 Under 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 Over 10 70 Age group (5yr)
40
35
Surf Life Saving % 30 ◦ Surf (maybe? – three slides) NZ Population %
25
20 % 15
10
5
0
BOP Otago Nelson Waikato Tasman Auckland TaranakiNorthland Gisborne CanterburyWellington Southland HawkesBay MarlboroughWestCoast
ManawatuWanganui 42 30
Surf Life Saving % 25 NZ Population%
20
% 15
10
5
0 >10 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70+ 90
80 Female Male
70
60 % 50
40
30
20
10
0 <10 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70+ Age Groups (5yr) Surf has large numbers (15,000)
Extreme proportion of youth (unique) and gender balance (also unique)
An opportunity for cross-over training and increased participation? Coastguard?
Note the large drop off in female retention – an opportunity to learn? Large SAR under- representation of females
Find the drivers for participation and factors influencing drop-off 35 Coastguard 30 LandSAR
Surf Lifesaving 25 AREC Recruitment and 20 Cohort effectNZ or Population Drop-off patterns? % natural peak? 15
10
5
0 Under 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 Over 10 70 Age group (5yr) 46 Opposite to surf – very ‘old’ age profile
Succession issue evident
If AREC role in SAR comms is important, then this requires urgent attention
AREC members note aging membership, recruitment, changing technology and training as key issues of concern
Could this be an extreme model for other SAR sectors as population ages? LandSAR membership vs Land SAR incidents (P130)
Coastguard membership vs Marine SAR incidents (P130)
49 35 ◦ LandSAR (three slides) 30 Coastguard %
NZ% 25
20 % 15
10
5
0
Otago Nelson Waikato Taranaki Tasman Auckland Northland Wellington Southland Gisborne Canterbury West Coast Bay of Plenty Hawkes Bay Marlborough NZ Region Manawatu-Wanganui 50 30.0 Coastguard member % 25.0 Marine SAR Incidents %
20.0
15.0
10.0
5.0
0.0
BOP Otago Nelson Waikato Tasman Auckland Northland Taranaki Gisborne Wellington Canterbury Southland Marlborough Hawkes Bay West Coast
ManawatuWanganui 35.0 Coastguard member % 30.0 Marine SAR Incidents %
25.0 NZ Population %
20.0
15.0
10.0
5.0
0.0
BOP Otago Nelson Waikato Tasman Auckland Northland Taranaki Gisborne Wellington Canterbury Southland Marlborough Hawkes Bay West Coast
ManawatuWanganui 35.0 Coastguard member % 30.0 Marine SAR Incidents %
25.0 NZ Population %
20.0
15.0 Auckland and Wellington
10.0 • Auckland has rough balance
5.0 • Wellington has high incident % and low coastguard %
0.0 • Wellington has low relative population potential here
BOP • Are different operationalOtago environments a factor?Nelson Spatial spread, Waikato Tasman Auckland Northland Taranaki Gisborne Wellington Canterbury Southland police role, reporting differences?Marlborough Is Hawkesthere Bay a problem?West Coast
ManawatuWanganui
54 35 LandSAR member % ◦30 LandSAR (three slides) NZ Population %
25
20 % 15
10
5
0
BOP Otago Nelson Waikato Tasman Auckland Northland Taranaki Gisborne CanterburyWellington Southland Hawkes Bay MarlboroughWest Coast
NZ Regions ManawatuWanganui 55 18.0 LandSAR NZ member % 16.0 Land SAR Incidents % 14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
BOP Otago Nelson Waikato Tasman Auckland Taranaki Northland Gisborne Wellington CanterburySouthland West Coast Marlborough Hawkes Bay
ManawatuWanganui 18.0 LandSAR NZ member % 16.0 Land SAR Incidents % 14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
BOP Otago Nelson Waikato Tasman Auckland Taranaki Northland Gisborne Wellington Canterbury Southland West Coast Marlborough Hawkes Bay
ManawatuWanganui 18.0 LandSAR NZ member % 16.0 Land SAR Incidents % 14.0
12.0 NZ Population %
10.0
8.0
6.0
4.0
2.0
0.0
BOP Otago Nelson Waikato Tasman Auckland Taranaki Northland Gisborne Wellington Canterbury Southland West Coast Marlborough Hawkes Bay
ManawatuWanganui Auckland18.0 LandSAR NZ member % • Membership16.0 < Incidents Land SAR Incidents % 14.0 • BUT population very high 12.0 NZ Population % • Volunteer pool high? 10.0 West Coast • Incident types and 8.0 • Membership > Incidents responses different? 6.0 • BUT population relatively low 4.0 • Incident types different 2.0 • Different future demand trends 0.0
BOP Otago Nelson Waikato Tasman Auckland Taranaki Northland Gisborne Wellington Canterbury Southland West Coast Marlborough Hawkes Bay
ManawatuWanganui Tension and imbalance of supply vs.demand in certain regions Projections have implications ◦ Best addressed through retention/recruitment and adaptive response Cross training suitable candidates Providing alternative one-SAR career paths across multiple agencies
Recap: LandSAR older and smaller #s Surf younger and larger #s Cross pollinate?
60 One example: Shore based fishing ◦ Strong demographic predictor 35
Inshore Shore Fishing-Gathering % 30 Other Marine Activities %
25
20
15 % of SAR subjects
10
5
0 0-9 10-19 20-29 30-39 40-49 50-59 60-69 70+ 62
80
Inshore Shore-Based Activities % 70 Other Activities % 60
50
40
30 % SAR or subjects
20
10
0 European Maori Polynesian Asian Other NZ 63 Ethnicity issue identified previously and work has been done to cut # drownings
Value of targeting
Escalate response with increased demand
Projections are possible
64 Projected ethnic profile - New Zealand 4000000
3500000
3000000
2500000
People 2000000
1500000
1000000
500000
0 European or Other Maori Asian Pacific (including New Zealander) 2006 2011 2016 2021 2026
65
Questions: What will be most likely to change in the next 20 years?
Which trends are considered to be most important?
Scoping opinions to test against our findings and direct us in the last write- up
Method: Expert panel assessing 6 trends assessed via online methods
67 1. Increased cost of travel/transport
2. Growth in tourism and recreation activities
3. Aging population structure
4. Increased use of technology
5. Increased population and urbanisation
6. Different funding/resourcing arrangements
68 95% conf SE TRENDS Mean score interval Increased use of technology 4.1 0.18 (3.7 to 4.5) Aging overall population 3.9 0.17 (3.5 to 4.2) Increased tourism and recreation activities 3.8 0.16 (3.5 to 4.1) Different funding/resourcing arrangements 3.4 0.22 (3.0 to 3.9) Increased population and urbanisation 3.3 0.18 (2.9 to 3.7) Increased cost of travel/transport 2.5 0.22 (2.1 to 3.0)
69 95% conf SE TRENDS Mean score interval Increased use of technology 4.5 0.10 (4.2 to 4.7) Increased tourism and recreation activities 4.3 0.11 (4.0 to 4.5) Aging overall population 4.0 0.15 (3.7 to 4.4) Increased population and urbanisation 4.0 0.13 (3.7 to 4.2) Different funding/resourcing arrangements 3.9 0.19 (3.5 to 4.3) Increased cost of travel/transport 3.0 0.22 (2.5 to 3.4)
70
Extremely 5 likely Possible Priority area overkill of interest Technology
4 Tourism
Urbanisation 3 Funding
Aging Trend LikelihoodTrend (mean) 2
Not urgent - Low priority Travel/Transport cost but monitor Extremely Unlikely 1 1 2 3 4 5 Extremely Unimportant Trend Importance (mean) important
71 There will be greater public expectations for immediate and successful SAR response (Score = 4.5)
There will be reduction in the 'search' component of many SAR call-out due to better beacons, communications and location technology (Score = 4.1)
Some people will put themselves at more risk because of over-dependence on technological devices - resulting in increased SAR callouts (Score = 3.8) Increased numbers of people visiting natural outdoor areas and parks (Score = 4.3)
Increased SAR callouts due to increased numbers of tourists (Score = 4.2)
Increased numbers of people engaged in marine recreation (Score = 4.1)
Increased SAR callouts from people in easily accessible natural areas (Score = 4.0) There will be increasing proportions of non- recreation SAR incidents (e.g. Dementia, Despondent, Missing) (Score = 4.4)
There will be increased diversity in SAR subjects/victims, from greater variety in ethnic and interest groups (Score = 4.0) People will live longer and remain more active, with sustained increase in SAR demands in some areas (Score = 4.1)
There will be increased recreation closer to home and in more accessible areas, with an increase in related SAR demand (Score = 4.0) Increasing 'professionalisation' of SAR will require increased funding sources (Score = 4.1)
Increased costs for SAR operations, training and support (Score = 4.1)
Increased costs for volunteers involved in SAR (Score = 4.0) There will be decreased recreation in more remote areas, with decrease in related SAR demand (Score = 2.2)
SAR incidents will decrease overall as people engage in more urban-based recreation types (Score = 2.3)
Fewer recreation SAR incidents overall as people use the more accessible and less remote areas (Score = 2.4)
Compulsory 'user-pays' types of insurance systems will be introduced as a requirement for anyone using more remote locations (i.e. backcountry or backwaters) in order to cover SAR costs (Score = 2.5)
People travel less often for recreation purposes (Score = 2.7)
There will be increasing reliance on professional SAR response agencies instead of volunteers (Score = 3.0)
80
Examples:
Dementia (aging projections) Inshore (ethnicity projections) Tourism (tourism forecasts)
81 Population growth & regional patterns Ethnically more diverse populations & more diverse activities Changing SAR incident demands Aging population structure Less volunteer capacity/capability in certain hard hit regions (e.g., West Coast) or functions (e.g., Radios - AREC) Impact of technology (a two-edged sword?) Growth in tourism and recreation demands regionally Greater resource competition Aligning information needs
82 Importance of volunteer recruitment and retention Role of women & youth One-SAR – career paths and training to meet future challenges – cross-sector analysis Regional and central resourcing Consider going ‘up-a-cog’ for certain regions in relation to expected growth in demand Balancing volunteer and professional roles Influencing demand – prevention, education and awareness
83 Model provides a useful indicator of the likely future outcome for SAR Volunteer capability cross training and career paths Information drivers integration and management of data fuel projections & strategies for response Opportunities for improving data management and further applied research
84 Main report delivered to SARINZ in June 2010
Included detailed profiles across incident types, subjects and on SAR volunteers
85
Thank you
Contacts Bronek Kazmierow [email protected] Gordon Cessford [email protected]
B Kazmierow – Recreation and Tourism Consulting PO Box 58082, Porirua 5245
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