Tomer Gueta, Avi Bar-Massada and Yohay Carmel Using GBIF data to test niche vs. neutrality theories at a continental scale, and the value of data cleaning Faculty of Civil and Environmental Engineering Technion – Israel Institute of Technology 1

2 Testing ecological theories

This case study What determine species’ distribution pattern at a continental scale?

The Niche theory ( Grinnell 1924) Environment! Niche theory Topography Veg. cover Land-use Niche

The Neutral theory ( Hubbell 2001) (Neutral theory) Stochastic processes and/or dispersal limitation predominant

Niche vs. Neutrality The continuum hypothesis Niche and neutral theories are located at the two ends of a continuum (Gravel et al 2006) Niche Neutral

7 The continuum hypothesis  Species-rich communities are driven more strongly by neutral processes  Species-poor communities are driven more strongly by the niche Modeling studies suggested that species richness is a main determinant species richness gradient Species-poor communities Species-rich communities The continuum hypothesis Niche and neutral theories are located at the two ends of a continuum (Gravel et al 2006) Niche Neutral

Prediction Species richness gradient Species richness High Low

9 Prediction- the missing link The effect of environmental factors on species distribution High effect Low effect Neutral theory Niche theory species richness gradient Species-poor communities Species-rich communities

10 Prediction 1: Continuum hypothesis  Species-rich communities are driven more strongly by neutral processes  Species-poor communities are driven more strongly by the niche Modeling studies suggested that species richness is a main determinant species richness gradient Species-poor communities Species-rich communities High effect Low effect Environment effect (Neutral) (Niche) A clear negative correlation= continuum (-)

11 Prediction 2: Niche species richness gradient Species-poor communities Species-rich communities High effect Low effect Environment effect (Neutral) (Niche) A clear positive correlation= niche (+) Environmental gradient Occurrence prob. Environmental gradient Occurrence prob. Species-rich communities Species-poor communities

12 Prediction 3: Neutral

13 Where? Australia

14 What? (IUCN, 2008)

15 Quantifying environmental effect The effect of environmental factors on species distribution High effect Low effect Neutral theory Niche theory

16 Species Distribution Model (SDM) Species “X” Occurrence data Difference environmental factors + Niche characterization Extracting data for validation Model validation SDM performance Predicted species distribution map

17 MaxEnt (Phillips et al. 2006) Species “X” Occurrence data Difference environmental factors + Niche characterization Extracting data for validation Model validation MaxEnt ‘gain’ Predicted species distribution map

18 Methods Species-richness gradient for each species

19 Prediction 1: Continuum hypothesis  Species-rich communities are driven more strongly by neutral processes  Species-poor communities are driven more strongly by the niche Modeling studies suggested that species richness is a main determinant species richness gradient Species-poor communities Species-rich communities High effect Low effect MaxEnt ‘gain’ (Neutral) (Niche) A clear negative correlation= continuum (-)

20 Prediction 2: Niche species richness gradient Species-poor communities Species-rich communities High effect Low effect MaxEnt ‘gain’ (Neutral) (Niche) A clear positive correlation= niche (+) Environmental gradient Occurrence prob. Environmental gradient Occurrence prob.

21 Species richness  Organism perspective  Guilds  Biological characteristics: taxon, trophic level and body weight All Mammals Bats CarnivoreHerbivores 1g-100g100g-5000g

22 The data Global Biodiversity Information Facility

Study design Raw data Data cleaning Conclusions

24 Data cleaning Non-numeric Latitude Missing Latitude Non-numeric Longitude Missing Longitude Precision: Longitude & Latitude precision with at least 3 decimal digits Out of Australia coordinates Switched Longitude & Latitude Records in center of country Geospatial Conventional data check and filtering

25 Data cleaning Unrecognized species Domesticated species Extinct species Taxonomic Unknown year Records above the year 1990 Temporal From 1,041,867 records to 515,479

Results- 100km grid trend Spearman rank values (rho) p.value<0.1 Before cleaningAfter cleaning Continuum (-) 1837 Niche (+) 78 Spearman rank correlation test (rho) a non-parametric correlation test Total

Results- 200km grid trend Spearman rank values (rho) p.value<0.1 Before cleaningAfter cleaning Continuum (-) 2433 Niche (+) 134 Total

Results- 300km grid trend Spearman rank values (rho) p.value<0.1 Before cleaningAfter cleaning Continuum (-) 3343 Niche (+) 63 Total

29 Conclusions  The effect of the Environment decreases with species richness  We exapmlefy the crucial role of data cleaning!

Thank you for listening 30 See Metadata record Contact Harry Burton for details. National Parks Association of NSW, Great Koala Count Data supplied by Dept. Natural Resources, Environment, The Arts and Sport. Northern Territory of Australia See Metadata record and Contact Harry Burton for details. See Metadata record Contact Dave Watts for details on citation details. Biodiversity occurrence data provided by the Atlas of New South Wales Wildlife, a resource owned by the State of New South Wales which holds data from a number of custodians including the Office of Environment and Heritage, Department of Premier and Cabinet (OEH), the National Herbarium of NSW, Forests NSW, the Australian Museum and the Australian Bird and Bat Banding Scheme. (Accessed through ALA Data Portal, ). Department of Environment and Natural Resources, Biological Databases of SA (BDSA), Date of Extraction: October 2012 See Metadata record Contact Harry Burton for details. See metadata record Contact Harry Burton for details. Australian National Insect Collection Citation is at record level EMBL Australian Mirror, European Bioinformatics Institute, Records provided by Global Biodiversity Information Facility, accessed through ALA website. See Metadata record Contact Dave Watts for details on citation details. See Metadata record for details Paul Daves Littlewood" Museum of New Zealand Te Papa Tongawera Records provided by Australian Antarctic Data Centre, accessed through ALA website. Records provided by Australian National Insect Collection, CSIRO Entomology, accessed through ALA website. Citations (Data resource)

31 Citations (Data resource) See the following Metadata records Contact Data Centre for help on citation details. Records provided by Queen Victoria Museum and Art Gallery - Mammals, accessed through ALA website. Great Koala Count, South Australia Natural Values Atlas ( Date Stamp, (c) State of Tasmania Records provided by Queensland Museum Mammals, accessed through ALA website. Records provided by Australian Museum Marine Invertebrate Collection, accessed through ALA website. Records provided by Tasmanian Museum and Art Gallery Vertebrate Collection, accessed through ALA website. Records provided by Western Australian Museum, accessed through ALA website. Queen Victoria Museum and Art Gallery, Northern Territory Museum and Art Gallery, Queensland Museum, Far North Quoll Seekers Network, Wildlife Preservation Society of Queensland Australian National Wildlife Collection, CSIRO, Australian Museum, Records provided by Littlewood, accessed through ALA website. Tasmanian Museum and Art Gallery, Museum of New Zealand Te Papa Tongawera Western Australian Museum,

32 Citations (Data resource) See Metadata record Contact Data Centre for details. Records provided by OZCAM (Online Zoological Collections of Australian Museums) Provider, accessed through ALA website. New Zealand Department of Conservation Records provided by Morphbank, accessed through ALA website. See Metadata record Contact Data Centre for details. Records provided by Tasmanian Museum and Art Gallery, accessed through ALA website. When using OBIS data, please cite the relevant data sources. Arthur D. Chapman, March 2012 Records provided by Western Australian Museum Mammal Collection, accessed through ALA website. Records provided by Australian Museum, accessed through ALA website. Records provided by Australian National Wildlife Collection, accessed through ALA website. Records provided by ECOCEAN Whale Shark Expeditions, accessed through ALA website. Records provided by European Molecular Biology Laboratory Australia, accessed through ALA website. citation is at record level See Metadata record and Contact Eric Woehler for details on citation details. Records provided by Australian Museum Mammalogy Collection, accessed through ALA website. Records provided by Department of Natural Resources, Environment, The Arts and Sport, Northern Territory of Australia, accessed through ALA website. Records provided by Museum and Art Gallery of the Northern Territory Mammal Collection, accessed through ALA website. Records provided by South Australia, Department of Environment, Water and Natural Resources, accessed through ALA website. Records provided by Queensland Museum, accessed through ALA website. Records provided by Office of Environment and Heritage, Department of Premier and Cabinet representing the State of New South Wales, accessed through ALA website. Records provided by Barcode of Life, accessed through ALA website. Records provided by Museum and Art Gallery of the Northern Territory, accessed through ALA website. Records provided by Australian Museum Ornithology Collection, accessed through ALA website. Records provided by Queen Victoria Museum and Art Gallery, accessed through ALA website. Records provided by Australian National Insect Collection, accessed through ALA website. Data collected due to the support provided by the Australian Government's Natural Heritage Trust and Q2 Coasts and Country programme and supplied by Northern Gulf Resource Management Group Ltd Records provided by BOLD - Australia, accessed through ALA website. Records provided by Commonwealth Scientific and Industrial Research Organisation, accessed through ALA website.

33 Results Case study 1 Grid trend Spearman rank values (rho) p.value<0.1 Before cleaningAfter cleaning 100km km km km Ecoregions

34 Results Case study 1 Grid trend Spearman rank values rho 0.4 Before cleaningAfter cleaning 100km km km km Ecoregions

35 Five different grids

Our approach 36 Research question Data analysis Data validation and cleaning Biases investigation The data

37 Research design Case study 1 (theoretical Q) Case study 2 (applicable Q) Data cleaning Biases analysis Data cleaning & Conclusions Overall protocol

38 Species richness  Organism perspective  Guilds  Biological characteristics: taxon, trophic level and body weight All Mammals Bats Herbivore Bats Carnivore BatsHerbivores Omnivores Carnivores Herbivores CarnivoreHerbivores Carnivore Herbivores 1g-100g 100g-5000g5000g +