NZ population projections through to For SARINZ. By: Gordon Cessford & Bronek Kazmierow B Kazmierow Recreation and Tourism Consulting

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1 NZ population projections through to 2030 For SARINZ By: Gordon Cessford & Bronek Kazmierow B Kazmierow Recreation and Tourism Consulting

2 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

3 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

4 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

5 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

6 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

7 DEMAND FACTORS OVERALL SAR OUTCOMES SUPPLY FACTORS Overall NZ population demographic characteristics and projections SAR call-out demographic characteristics national, regional and targeted segments Projections and trends - related to recreation SAR call-out profiles - related to non-recreation SAR call-out profiles SAR volunteer demographic profiles national, regional and targeted segments Projections and trends - related to profiles of different SAR volunteer segments (e.g. Surf-lifesaving, amateur radio operators, LandSAR search etc) NZ recreation participation, preferences, profiles and capabilities -National and regional patterns -Forecast trend NZ tourism -activity patterns and trends - international and domestic tourists Demand Actions EQUILIBRIA or TENSION Resulting from the interaction between DEMAND amd SUPPLY factors The INITIAL RESULTS are baseline levels and patterns of SAR incidents SAR capability/capacity existing features & trends - National and regional patterns - Volunteer training, retention, recruitment status and implications Supply Actions The LONGER TERM OUTCOMES are future readiness, effectiveness and efficiency of SAR response 7

8 Census Regional distribution Projections Regional populations Age and dependency ratios 8

9 Auckland Region 21.94% 32.35% Canterbury Region Wellington Region Waikato Region 12.96% 11.49% 11.15% 8.43% 9.50% 9.31% Bay of Plenty Region 6.39% 14.71% Manawatu-Wanganui Region Otago Region Northland Region Hawke's Bay Region Taranaki Region Southland Region -6.41% -2.77% -2.31% 5.52% 4.81% 4.71% 3.69% 8.33% 3.67% 3.50% 2.59% 2.26% Tasman Region 1.11% 17.52% Gisborne Region Nelson Region -2.81% 1.10% 1.06% 6.48% Marlborough Region 1.06% 10.84% West Coast Region -3.64% 0.78% Area Outside Region % 0.02% -20% -10% 0% 10% 20% 30% 40% Regional population as a percentage of NZ overall population (2006) Population change

10 6,000,000 5,000,000 4,000,000 3,000,000 2,000,000 North Island South Island New Zealand 1,000, (3)

11 Auckland region 573,700 Canterbury region Wellington region Waikato region Bay of Plenty region Manawatu-Wanganui region Otago region Northland region Hawke's Bay region Taranaki region Southland region 112,400 75,000 73,100 58,100 7,600 26,100 18,600 6,200 1,300-5,200 Gisborne region Tasman region Nelson region Marlborough region West Coast region 0 7,400 5,600 5, ,000 1,000,000 1,500,000 2,000, (3) Population change

12 Marlborough region West Coast region Tasman region Nelson region Northland region Southland region Taranaki region Bay of Plenty region Canterbury region Hawke's Bay region Otago region Manawatu-Wanganui New Zealand(1) Waikato region Wellington region Gisborne region Auckland region Median age (years) 12

13 21.3% 30.8% 31.5% 14.2% 25.7% 52.1% 54.8% 45.9% 31.7% 28.9% 54.6% 86.3% 35,000 2,500,000 30,000 25,000 20,000 15,000 10,000 5, ,500 11,700 9,400 9,200 9,100 7,700 6,500 5,300 West Coast Region 2006 West Coast Region ,000,000 1,500,000 1,000, , , , , , , , , ,200 Auckland Region 2006 Auckland Region % 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Dependency ratio (total) Dependency ratio (aged) Dependency ratio (young) West Coast Region 2006 West Coast Region % 90.0% 80.0% 70.0% 60.0% 50.0% 40.0% 30.0% 20.0% 10.0% 0.0% Dependency ratio (total) Dependency ratio (aged) Dependency ratio (young) Auckland Region 2006 Auckland Region

14 Applying the model Baseline data Some examples Projections for dementia incidents Projections for incidents based on recreation/tourism and population forecasts 15

16 % of SAR subjects NZ SAR Subjects % NZ 65+ SAR Subjects % Tramping Walking Other Hunting (all) SAR Subject Recreation Activities

17 Dementia Subjects % NZ Population % % Age group (10yr)

18 % of 65+ age group Dementia % Recreation % Age groups (5yr)

19 % of 65+ age group Dementia Recreation Urban Areas Rural Town Rural Natural Areas Area Types Urban Fringe Rural Farmland Remote Natural Areas/Park

20 % of 65+ Age-group Dementia Subjects Incident % NZ 65+ Age-group % Auckland Wellington BOP Waikato Marlborough Manawatu-Wanganui Nelson Northland Canterbury Taranaki Otago Hawkes Bay Southland Tasman WestCoast Gisborne

21 New Zealand North Island Auckland region South Island Wellington region Bay of Plenty region Waikato region Marlborough region Manawatu-Wanganui region Nelson region Northland region Canterbury region Taranaki region Otago region Hawke's Bay region Southland region West Coast region Tasman region Gisborne region North Island Auckland region South Island Wellington region Bay of Plenty region Waikato region Marlborough region Manawatu-Wanganui region Nelson region Northland region Canterbury region Taranaki region Otago region Hawke's Bay region Southland region West Coast region Tasman region Gisborne region Dementia SAR callouts Dementia SAR callout index SAR Callouts Dementia Base (4 year period ) Projected SCDB (4 year period ) f or over 65 year dementia series SCDB index (per residents based on 2006 pop) SCDBI (per residents based on 2026 pop) 22

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

24 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

25 % of SAR Subjects NZ Subjects % Tourist Subjects % Marine SAR Subjects % Land SAR Subjects % 26

26 % of SAR subjects Recreation Incidents Non-Recreation Incidents Tourist Subjects % NZ Subjects % 27

27 % of SAR Recreation Activities NZ Subjects % Tourist Subjects % 0 SkiingBoarding Tramping Climbing Walking Rafting Fishing MountainBiking ExtremeSports 4WD Kayaking Other Activites 28

28 % of SAR Recreation types Tourist Subjects % NZ Subjects % Tramping Walking Climbing Mountain Biking Fishing Rafting SkiingBoarding Hunting Deer Kayaking Flying activities Other Top-10 SAR Recreation Incident types

29 % of Land SAR Subjects Tourist Subjects % NZ Subjects % 0 Southland Otago WestCoast Taranaki Canterbury Tasman ALL NZ REGIONS Waikato Marlborough Nelson ManawatuWanganui Northland BOP Auckland Gisborne Wellington HawkesBay 30

30 % of SAR subjects Non-Locals % Locals % 0 Tasman* Southland West Coast Gisborne* Otago Marlborough Waikato Manawatu Wanganui Taranaki Canterbury Incident Regions BOP Hawkes Bay Nelson* Northland Auckland Wellington 31

31 % of SAR subjects 100% 90% 80% 70% 60% 50% 40% 30% 20% Tourists % Other Regions % Locals % 10% 0% Tasman* Southland West Coast Gisborne* Otago Marlborough Waikato Manawatu Wanganui Taranaki Canterbury Incident Regions BOP Hawkes Bay Nelson* Northland Auckland Wellington 32

32 READ Columns down Subject Home Region (Row) SAROP Incident Region (Column) Auckland BOP Canterbury Gisborne Hawkes Bay Manawatu Wanganui Marlborough Nelson Northland Otago Southland Taranaki Tasman Waikato Wellington West Coast Overseas Auckland BOP Canterbury Gisborne HawkesBay ManawatuWanganui Marlborough Nelson Northland Otago Southland Taranaki Tasman Waikato Wellington WestCoast Total column % n= Can show where subjects in any Incident region came from All Victims Can show where subjects from any one home region had their incidents

33 Home Region Incident region Auckland BOP Canterbury Auckland BOP Canterbury Gisborne HawkesBay ManawatuWanganui Marlborough Nelson Northland Otago Southland Taranaki Tasman Waikato Wellington WestCoast Total column % n=

34 Wellington region Waikato region Otago region Canterbury region Southland region Auckland region West Coast region Manawatu-Wanganui region Tasman region Bay of Plenty region Taranaki region Marlborough region Northland region Hawke's Bay region Nelson region Gisborne region SAR incident callouts SAR Callouts Base (4 year period ) Projected SCB (4 year period ) Visitor Nights series New Zealand North Island South Island Wellington region Waikato region Otago region Canterbury region Southland region Auckland region West Coast region Manawatu-Wanganui region Tasman region Bay of Plenty region Taranaki region Marlborough region Northland region Hawke's Bay region Nelson region Gisborne region SAR incident callout index SCB index (per residents based on 2006 pop) SCBI (per residents based on 2026 pop) Visitor Night series 35

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

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

37 Adaptive responses Resourcing Training Prevention & education Caution: scale is important when interpreting patterns national vs. regional 38

38 Agency profiles Regional distribution Impacted also by demographic projections Regional populations Age and dependency ratios Examples: Surf vs. AREC Coastguard vs. LandSAR 39

39 35 Coastguard % LandSAR Surf Lifesaving AREC NZ Population Under Over 70 Age group (5yr) 40

41 Surf (maybe? three slides) Surf Life Saving % NZ Population % % Auckland BOP Waikato Canterbury Wellington Taranaki Northland Otago HawkesBay Gisborne ManawatuWanganui Southland Marlborough WestCoast Nelson Tasman 42

42 30 25 Surf Life Saving % NZ Population% 20 % >

43 90 80 Female Male 70 % < Age Groups (5yr)

44 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 underrepresentation of females Find the drivers for participation and factors influencing drop-off

45 35 Coastguard 30 LandSAR 25 Surf Lifesaving % 20 Recruitment and Drop-off patterns? AREC Cohort effect or natural peak? NZ Population Under Over 70 Age group (5yr) 46

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?

47 LandSAR membership vs Land SAR incidents (P130) Coastguard membership vs Marine SAR incidents (P130)

48 49

49 LandSAR (three slides) Coastguard % NZ% 20 % Auckland Waikato Northland Bay of Plenty Canterbury Wellington NZ Region Otago Hawkes Bay Southland Gisborne Manawatu-Wanganui Taranaki West Coast Marlborough Nelson Tasman 50

50 Coastguard member % Marine SAR Incidents % Auckland Wellington Waikato Northland Canterbury BOP Otago Tasman Southland Marlborough Taranaki ManawatuWanganui Hawkes Bay Nelson West Coast Gisborne

51 Coastguard member % Marine SAR Incidents % NZ Population % Auckland Wellington Waikato Northland Canterbury BOP Otago Tasman Southland Marlborough Taranaki ManawatuWanganui Hawkes Bay Nelson West Coast Gisborne

52 Coastguard member % Marine SAR Incidents % NZ Population % Auckland Wellington Waikato Auckland and Wellington Auckland has rough balance Wellington has high incident % and low coastguard % Wellington has low relative population potential here Are different operational environments a factor? Spatial spread, police role, reporting differences? Is there a problem? Northland Canterbury BOP Otago Tasman Southland Marlborough Taranaki ManawatuWanganui Hawkes Bay Nelson West Coast Gisborne

53 54

54 35 30LandSAR (three slides) LandSAR member % NZ Population % 25 % Auckland Canterbury Wellington Waikato BOP ManawatuWanganui Otago Northland Hawkes Bay Taranaki Southland NZ Regions Tasman Gisborne Nelson Marlborough West Coast 55

55 LandSAR NZ member % Land SAR Incidents % Wellington Waikato Otago Canterbury Southland Auckland ManawatuWanganui West Coast Tasman BOP Taranaki Marlborough Northland Hawkes Bay Nelson Gisborne

56 LandSAR NZ member % Land SAR Incidents % Wellington Waikato Otago Canterbury Southland Auckland ManawatuWanganui West Coast Tasman BOP Taranaki Marlborough Northland Hawkes Bay Nelson Gisborne

57 LandSAR NZ member % Land SAR Incidents % NZ Population % Wellington Waikato Otago Canterbury Southland Auckland ManawatuWanganui West Coast Tasman BOP Taranaki Marlborough Northland Hawkes Bay Nelson Gisborne

58 Auckland Membership < Incidents 14.0 BUT population very high 12.0 Volunteer pool high? 10.0 Incident types and 8.0 responses different? LandSAR NZ member % Land SAR Incidents % NZ Population % West Coast Membership > Incidents BUT population relatively low Incident types different Different future demand trends Wellington Waikato Otago Canterbury Southland Auckland ManawatuWanganui West Coast Tasman BOP Taranaki Marlborough Northland Hawkes Bay Nelson Gisborne

59 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

60 One example: Shore based fishing Strong demographic predictor

61 % of SAR subjects 35 Inshore 30 Shore Fishing-Gathering % Other Marine Activities %

62 % or SAR subjects Inshore Shore-Based Activities % Other Activities % European Maori Polynesian Asian Other NZ 63

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

64 Projected ethnic profile - New Zealand People European or Other (including New Zealander) Maori Asian Pacif ic

66 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 writeup Method: Expert panel assessing 6 trends assessed via online methods 67

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

68 TRENDS Mean score SE 95% conf interval Increased use of technology (3.7 to 4.5) Aging overall population (3.5 to 4.2) Increased tourism and recreation activities (3.5 to 4.1) Different funding/resourcing arrangements (3.0 to 3.9) Increased population and urbanisation (2.9 to 3.7) Increased cost of travel/transport (2.1 to 3.0) 69

69 TRENDS Mean score SE 95% conf interval Increased use of technology (4.2 to 4.7) Increased tourism and recreation activities (4.0 to 4.5) Aging overall population (3.7 to 4.4) Increased population and urbanisation (3.7 to 4.2) Different funding/resourcing arrangements (3.5 to 4.3) Increased cost of travel/transport (2.5 to 3.4) 70

70 Trend Likelihood (mean) Extremely likely 5 Possible overkill Priority area of interest Technology 4 Tourism Urbanisation 3 Funding 2 Aging Extremely Unlikely 1 Low priority Unimportant Trend Importance (mean) Not urgent - but monitor Extremely important Travel/Transport cost 71

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)

72 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)

73 There will be increasing proportions of nonrecreation 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)

74 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)

75 Increasing 'professionalisation' of SAR will require increased funding sources (Score = 4.1)

76 Increased costs for SAR operations, training and support (Score = 4.1) Increased costs for volunteers involved in SAR (Score = 4.0)

77 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)

78 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)

79 80

80 Examples: Dementia (aging projections) Inshore (ethnicity projections) Tourism (tourism forecasts) 81

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

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

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

84 Main report delivered to SARINZ in June 2010 Included detailed profiles across incident types, subjects and on SAR volunteers 85

85 Thank you Contacts Bronek Kazmierow Gordon Cessford B Kazmierow Recreation and Tourism Consulting PO Box 58082, Porirua

86 87

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