Benthic primary productivity in the KimberleyDR RENAE HOVEY - UWA

AcknowledgmentsWA State Government and WAMSI partners for supporting this research.

Links with sub-projects:

2.2.3 – Benthic community production (Ryan Lowe)

2.2.4 – Seagrass (Gary Kendrick)

1.3.1 – Reef geomorphology (Mick O’Leary)

1.2.5 – Dugong (Peter Bayliss)

Raw data: Gary Kendrick, Ryan Lowe, Renee Gruber, Jim Falter, Mat Vanderklift, Doug Bearham, James McLaughlin, Lucie Chovrelat, (CSIRO), Andrea Zavala Perez, Bonnie Laverock (UWA), Christin Säwström (ECU), and the Bardi JawiRangers

Analysis: Leonardo Ruiz Montoya

AIMS

Develop a GIS for spatially and temporally explicit baseline information on habitats and processes.

Develop benthic habitat distribution maps

Map benthic primary production◦ Effects of season and grazing

Mapping MethodsBayesian Belief Network – GIS framework

◦ Framework underpins project

◦ Quantitative and qualitative data

◦ Captures both scientific and traditional ecological knowledge

◦ Interdisciplinary tool – policymakers, planners, managers

◦ Effective in storing data

◦ Visual representation of relationships

Spatial modelling (traditional method)

◦ Develop statistical models that explain the relationship between benthic primary producers and environmental conditions (= predictive model)

◦ Upscale and extend across areas that we not visited

Mapping coastal seagrasses

GBR: Bayesian belief network for coastal seagrass habitats

(seagrass: present and absent) (Grech and Coles 2010)

Collating spatially explicit data

Bathymetry Light climate Sediment

Also Benthic Shear StressREI – Fetch (wind velocity, direction and % frequency)Tides (range)

Related to seagrass presence –> predictor variables

Benthic habitats – presence/absence data

Collating spatially explicit data

Seagrass Distribution Map

Probably seagrass

Possible seagrass

Substrate veg - seagrass &/or algae

Probably coral/reef

Probably sand

1.2.5 DugongsPeter Bayliss and Chris Wilcox

Depth driven model based on seagrass depth distributions from literature

*Benthic shear and REI models are almost ready to add to the BNN

- Final seagrass distribution map

Validation using animal tracking data

Possibly more data:• 2.2.4 – turtle tagging• Chris Wilcox, Richard Campbell,

Peter Bayliss

Historical data:

Mapping biomass production

Geo-referenced photo quadrats

Mapping biomass production

Validation

Mapping biomass production

Effects of grazing

Biomass Production

Map of primary production on intertidal reef

Points of interest: Not a strong seasonal signalInter-annual variability needs further investigation*Sargassum (algae) estimates need converting to biomass

Data from projects 2.2.3 and 2.2.4

&

GPP

Mapping biomass production- seagrass

(Max)0.0050.005 – 0.010.014

Biomass production per day

Per shoot Per m2 (shoot density)

Mapping biomass production- seagrass

Biomass production per day

Annual DW biomass (t)

Annual DW biomass (t) Consumed

Enhalus 19.7 3.2

Thalassia 48.5 3.2

Mix seagrass 152.9 17.9

Thalassia mix 0.146 0.009

Total 221.2 24.3

(Conservative values)

Can covert to carbon production using literature derived values

Next step: spatially extend productivity estimates

Kordi & O’Leary 2016-> ReefKIM

Next step: spatially extend productivity

1.3.1 Geomorphology (Mick O’Leary)

*Seagrass and Algae a single category

Management implications

•Seagrasses in the Kimberley deal with extreme physical conditions, yet maintain high productivity

•This productivity supports a diverse animal community

•Growth rates and productivity more valuable than traditional biomass or cover measurements

•Even more important to understand the spatial extent and arrangement of benthic productivity • appropriate monitoring designs and spatial

management

•These maps provide a baseline – a starting point or base layer to which more information can be added to improve accuracy and understanding of processes driving productivity in the region• Community outreach and citizen science will

be critical

Questions?

THANK YOU…

Halophila Thalassia Enhalus Cymodocea

WAMSI 2.2.4WAMSI 2.2.4