A spatial design for monitoring the health of a large-scale freshwater system Melissa Dobbie, Charis Burridge (CMIS) and Bill Senior (Qld Environment and Resource Management) Biometrics 2009, Taupo, NZ

Spatial design for monitoring health of large-scale river system FARWH: a national approach to monitoring river health Framework for the Assessment of River and Wetland Health  Developed to provide methods for comparing and integrating existing river and wetland health outputs to facilitate national reporting from comparable state, territory and regional NRM assessments  Funded by the National Water Commission  Desktop trial conducted in Victoria, Tasmania & South Australia  Field trial in Queensland, New South Wales, and Northern Australia currently underway.

Spatial design for monitoring health of large-scale river system Trialling FARWH in Queensland  Queensland Department of Environment and Resource Management won tender to undertake the fieldwork trial of FARWH in Qld  Will test FARWH against current monitoring programs in Queensland, examining correlations and redundancies between them, and recommending improvements to facilitate the Framework’s national applicability  CSIRO Mathematics, Informatics and Statistics provides statistical input for the field trials, mostly with regard to spatial design. Stream and Estuary Assessment Program (SEAP)

Spatial design for monitoring health of large-scale river system The why and what of SEAP – briefly!  Monitoring of Queensland’s rivers and estuaries is currently undertaken by numerous organisations for a variety of reasons and at different scales (Regional, State, Federal).  There is a need for better integration across objectives, organisations, and programs to monitor aquatic ecosystem health across the state from headwaters to, and including, estuaries. The Stream and Estuary Assessment Program (SEAP) will attempt to provide a better conceptual, operational and statistically-valid framework for an integrated water quality monitoring system across the State.

Spatial design for monitoring health of large-scale river system Objectives of SEAP 1.Assess the condition of the state’s aquatic ecosystems 2.Evaluate trends – are they deteriorating, remaining healthy or improving? 3.Improve our understanding of river health processes and stressors. 4.Guide natural resource management decisions.

Spatial design for monitoring health of large-scale river system Focus on Cooper Creek catchment (in Lake Eyre Basin)

Spatial design for monitoring health of large-scale river system Cooper Creek sampling frame Sampling unit: waterhole Sampling frame: waterholes that are within 100 m buffer from a road, track or stock route. have ≥ 70% permanency have ≥ 400 m perimeter Þ158 waterholes Waterhole perimeter (m) Min st Qu Median Mean rd Qu Max

Spatial design for monitoring health of large-scale river system What do sampling units look like?

Spatial design for monitoring health of large-scale river system Spatial design requirements  Assess (ambient) condition of waterholes in Cooper Creek through various types of indicators of ecosystem health  biological  physical  chemical  ecosystem processes  etc.  Operational considerations  vast distances/terrain  logistical issues  intended sampling period  staffing  etc.  Sampling considerations  spatial  temporal  sample size + oversample?

Spatial design for monitoring health of large-scale river system  Good spatial representation (regularity / balance)  Allow for adjustment of sample sizes dynamically  e.g. for non response or augment as needed  Accommodate variable inclusion probabilities Generalization of stratified sampling that allows selection probabilities to vary continuously, instead of being constant within discrete strata and only varying among strata. e.g. account for travel time / costs e.g. levels of an environmental stressor e.g. target particular habitats Desirable attributes of a spatial design spatially-balanced sampling

Spatial design for monitoring health of large-scale river system Stevens & Olsen (2004) - GRTS Developed a unified strategy for selecting spatially-balanced probability samples of natural resources Generalised Random-Tessellation Stratification Accommodates regular issues that occur in natural resource populations  variable probability  poor frame information  inaccessibility  uneven spatial pattern  missing data  panel structures

Spatial design for monitoring health of large-scale river system Other relevant papers Stevens and Olsen (2003): due to Horvitz-Thompson variance estimator being unsuitable for spatially-balanced designs, they developed a neighbourhood variance estimator to improve accuracy in reporting precision of the survey Stevens and Jensen (2007): on sample design, execution and analysis for wetland assessment – promotes GRTS and demonstrates application of techniques discussed on two watersheds.

Spatial design for monitoring health of large-scale river system GRTS implementation in a nutshell  Create a function that maps 2D space into 1D space, thereby defining ordered spatial address  Use a restricted randomisation (hierarchical randomisation) to randomly order the address (preserving spatial relationships as much as possible)  Apply transformation that induces an equi- probable linear structure.  Carry out systematic sampling along the randomly ordered linear structure – resulting in a spatially well-balanced sample.  Variable probability sampling is implemented by giving each point a length proportional to its inclusion probability

Spatial design for monitoring health of large-scale river system Software GRTS design and analysis software has been developed and tested in S Plus and R and is available to download for free from Examples are also provided for download – one for each population type (points, lines, areas). Implementation Extract sample frame from appropriate GIS E.g. using ArcMAP,…. Select sample: R program Input: Survey design specification (number of sample sites, inclusion probabilities), sample data frame Output: Data frame with sample

Spatial design for monitoring health of large-scale river system In summary …. GRTS design approach ….. Ensures spatial balance prevails Enables dynamic adjustment of sample size non-response imperfect sample frame formation Sub-populations of interest may change over time Accommodates variable inclusion probability Legacy sites Political, economic, scientific reasons affecting site selection Is implemented by US EPA in their EMAP and in other countries outside of the USA Can be applied to monitoring of 0-, 1-, or 2-dimensional (natural) resources for regional, continental or global monitoring problems

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