Jack Lee Lincoln University, Canterbury, New Zealand .

Slides:



Advertisements
Similar presentations
Topic 12 – Further Topics in ANOVA
Advertisements

Factorial ANOVA More than one categorical explanatory variable.
Inference for Regression
N-way ANOVA. 3-way ANOVA 2 H 0 : The mean respiratory rate is the same for all species H 0 : The mean respiratory rate is the same for all temperatures.
Meet the Kiwis…. Population of kiwis… Codes… Species Region GS-Great Spotted, NIBr-NorthIsland Brown, Tok-Southern Tokoeka NWN-North West Nelson, CW-Central.
OUR Ecological Footprint …. Ch 20 Community Ecology: Species Abundance + Diversity.
Statistical Techniques I EXST7005 Factorial Treatments & Interactions.
Stochastic effects for interacting microbial populations Rosalind Allen School of Physics and Astronomy, Edinburgh University eSI “Stochastic effects in.
BPS - 3rd Ed. Chapter 211 Inference for Regression.
So far... We have been estimating differences caused by application of various treatments, and determining the probability that an observed difference.
Factorial ANOVA More than one categorical explanatory variable STA305 Spring 2014.
Chapter 13 Analysis of Variance (ANOVA) PSY Spring 2003.
Jeopardy Opening Robert Lee | UOIT Game Board $ 200 $ 200 $ 200 $ 200 $ 200 $ 400 $ 400 $ 400 $ 400 $ 400 $ 10 0 $ 10 0 $ 10 0 $ 10 0 $ 10 0 $ 300 $
The Completely Randomized Design (§8.3)
© 2008 Pearson Addison-Wesley. All rights reserved Chapter 5 Statistical Reasoning.
Understanding Your Data Set Statistics are used to describe data sets Gives us a metric in place of a graph What are some types of statistics used to describe.
Individual-based storage promotes coexistence in neutral communities.
IE241: Introduction to Design of Experiments. Last term we talked about testing the difference between two independent means. For means from a normal.
Relative-Abundance Patterns
Designs for Experiments with More Than One Factor When the experimenter is interested in the effect of multiple factors on a response a factorial design.
BPS - 5th Ed. Chapter 231 Inference for Regression.
Stats Methods at IC Lecture 3: Regression.
Biodiversity How did biological diversity come about?
Inferential Statistics
Ecology (B & C) NY coaches meeting J.D. Lewis NY test writer
Lesson Overview 5.1 How Populations Grow.
Advanced Higher Statistics
Introduction to Statistics for the Social Sciences SBS200 - Lecture Section 001, Fall 2016 Room 150 Harvill Building 10: :50 Mondays, Wednesdays.
Introduction The two-sample z procedures of Chapter 10 allow us to compare the proportions of successes in two populations or for two treatments. What.
Relative-Abundance Patterns
Interactions and Factorial ANOVA
Hypothesis testing using contrasts
Rui Liua*, Helen Sutera, Helen Haydenb, Deli Chena, Jim Hea
Figure 1. The relationships of bacterial operational taxonomic unit richness (A) and phylogenetic diversity (B) with aridity index based on 97% sequence.
Two-Factor Full Factorial Designs
Chapter 36 Population Ecology Lecture by Brian R. Shmaefsky 1.
Population Dynamics The study of population characteristics and how they change over time Although several species may share a habitat they each have.
Multivariate community analysis
Physics- atmospheric Sciences (PAS) - Room 201
Studying Ecosystems.
Two-Factor Studies with Equal Replication
What is Rarity?.
Inferences and Conclusions from Data
Scientific Method.
Environmental Systems
Taxonomic composition of subway microbial communities.
Classification (Dis)similarity measures, Resemblance functions
Two-Factor Studies with Equal Replication
Microbial community dissimilarity.
Multi Linear Regression Lab
Heatmap summarizing the significant (P < 0
Student name Student ID Degree program Area of specialization
Randomized Complete Block and Repeated Measures (Each Subject Receives Each Treatment) Designs KNNL – Chapters 21,
Population Ecology 5.01 Investigate and analyze the interrelationships among organisms, populations, communities, and ecosystems.
Basic Practice of Statistics - 3rd Edition Inference for Regression
The Index of Biotic Integrity (the BI or IBI)
Principal Component Analysis
PCA of Waimea Wave Climate
Introduction to Biodiversity
Fixed, Random and Mixed effects
Biodiversity.
Microbial diversity of the 10 body locations sampled.
Inferential Statistics
Structure of benthic microbial communities of residential and industrial land use types before and after two rain events in urban waterways are shown.
Psych 231: Research Methods in Psychology
InferentIal StatIstIcs
Student name Student ID Degree program Area of specialization
14 Design of Experiments with Several Factors CHAPTER OUTLINE
Figure 1. Map of Alaska indicating the location of (A) the Caribou Poker Creek Research Watershed (CPCRW) and (B) the ... Figure 1. Map of Alaska indicating.
Variations in beta and alpha diversity of gut microbiome bacterial communities in relation to presence of Blastocystis. Variations in beta and alpha diversity.
Presentation transcript:

Jack Lee Lincoln University, Canterbury, New Zealand . An investigation of species sorting and neutral processes during early colonisation of aquatic microcosms. Jack Lee Lincoln University, Canterbury, New Zealand . I’d remove Canterbury, New Zealand, this is pretty obvious to your audience anyway

Bacterial Immigration.... About 54,000 Kiwi’s migrated to Australia last year. However, c. 1.34 x 1015 (1.34 quadrillion) bacterial cells enter NZ on Australian dust particles each year! Limited knowledge of the impact! Perfect!! 134000 metric tonnes of dust from Oz to NZ each year (Marx et al .,2009). Very conservative estimate of 104 bacterial cells per gram = 1338550000000000 bacterial cells a year!

Neutral Processes Vs Species Sorting… TRY TO MENTION STERILE ENVIRONMENTS AS YOU TALK ABOUT THIS – GET THE AUDIENCE READY FOR THE NEXT SLIDE Stress impot Neutral Processes- Random migration, deaths, births, ‘speciation’. Species Sorting- Niche based sorting. Deterministic environmental selection

Investigate the effects of different immigration times in both pre-sterilised and non-sterilised microcosms. A 23L pH 7.8 B 150L pH 7.4 C 550L pH 7.1 Water = PS NS Inoculate = STILL THINK PS AND NS SHOULD BE ADDED TO THE TITLE (IN BRACKETS) Time = Water x 3 (A,B,C), Inoculate x 2 (PS, NS), Time x 7, Rep x 3 = 108 microcosms

Methods All samples collected after 7 days. All water filtered. ARISA PCR DNA Extraction Ordination diagrams generated and experimental treatments compared (MDS plots). ARISA performed

Neutral theory predicts... Pre-Sterilised microcosms will show no significant differences in community structure relating to pond water source (A,B or C). Pre-Sterilised Non-Sterilised Key: = A = B = C = Rain Process Pre-Sterilised Non- Sterilised Neutral Theory  MAKE THE WORDS COMMUNITY STRUCTURE STAND OUT MORE. IT LOOKS LIKE THERE IS NO DIFFERENCE (A VERSUS B AND C) WHEN YOU LOOK AT PS, SO YOU’LL HAVE TO EMPHASISE THAT THERE ARE SIGNIFICNAT TRENDS, BUT THAT THEY ARE WEAKER THAN FOR NS Significant differences between the two inoculates (PS and NS). Significant differences between the water samples (A, B and C) for both NS inoculates and PS inoculates. Significant differences in variability between PS samples, with A showing higher dissimilarity, and C showing the highest similarity. 2D stress 0.2 Based on a Bray-Curtis similarity matrix

Neutral theory predicts... There will be no significant differences in community evenness relating to pond water source. Source of variation d.f SS F P (i) PS Sample Data A v B 1 4.3 0.18 0.69 A v C 22.2 0.83 0.40 B v C 0.70 (ii) NS Sample Data 146 4.19 0.06 767 49.91 <0.01 0.05 Process Pre-Sterilised Non-Sterilised Neutral Theory   NICE, BUT YOU NEED A LEGEND FOR YOUR TABLE Lorenz Curve Contrast results (comparing the effects of water (A,B, C) based on permutational ANOVA of Gini Coefficient data Glossary: Community Evenness is a measure of the equality or distribution of individuals among species

Neutral theory predicts... There will be fewer differences in community composition between the Pre-Sterilised microcosms and the rain water samples than between the Non-Sterilised microcosms and rain water. 12h 167 h Pre-Sterilised Non-Sterilised A B C 45 Relative abundance of taxon (percent of total community) Taxon (ARISA peak) PS +NS Process Pre Sterilised Non Sterilised Neutral Theory  

Neutral Model... Makes predictions using only three parameters: J (total community size), m (which describes the fraction of recruits coming into the local community from the source pool), Ɵ (the fundamental biodiversity number).

Neutral theory predicts... That m will increase with increased immigration times. Process Pre-Sterilised Non-Sterilised Neutral Theory   Generated using Etienne, 2005.

Conclusions….. Both neutral processes and species sorting appear to be important during the colonisation of aquatic environments. However, species sorting seems more important in previously colonised environments! Variable Process Non-Sterilised Pre-Sterilised Structure (Bray-Curtis) Neutral Theory  Evenness  Composition neutral parameter m IF YOU CAN THINK OF AN END STATEMNENT THAT WOULD BE GOOD. SOMETHING ALONG THE LINES OF, THESE RESULTS ARE IMPORTANT BECAUSE….. OR MAYBE YOU COULD PRESENT THIS IN THE CONTEXT OF AUSTRALIAN BACTERIAL IMMIGRATION – DON’T WORRY ABOUT THESE AUSSIE IMMIGRANTS TOO MUCH… THEY HAVE ONLY A SMALL EFFECT BECAUSE WE HAVE A RESIDENT POPULATION OF KIWI BACTERIA WHICH ARE KEEN TO HOLD THEIR GROUND!!

Bacterial airborne immigration. ....

Thank you. Any Questions?