curso lichos - mop and (separately) niche conservatism 201606

MODEL TRANSFERS AND MOP

MESS and MOP• Both have the intention of detecting

extrapolative situations• MESS is implemented within Maxent• MESS compares the area in question to the

centroid of the calibration cloud• MOP compares the area in question to the

nearest part of the calibration cloud• Agree on ‘out of range’ conditions• MOP better characterizes similarities between

calibration and transfer regions, and thus is more optimistic as regards in-range extrapolation

Ecological Niche Conservatism

A. Townsend PetersonUniversity of Kansas

Charles Elton – niche as role in communities

G. Evelyn Hutchinson – multidimensional ecological niches,

bionomic versus scenopoetic variables

First Step: Reconcile Concepts

Abiotic niche

Biotic interactionsAccessibility

Area presenting appropriate combinations of abiotic and biotic conditions (= potential distribution)

Actual geographic distribution(abiotic and biotic conditions fulfilled,accessible to dispersers)

Second Step: Reconcile Scale

Third Step: Explore Patterns

Controversy and Debate I“Overall, these results suggest a considerable role of environmentally mediated divergence in speciation” – Graham et al. 2004, Evolution

“Considerable debate has emerged in the recent literature as to whether or not niches are conserved … We believe that the question of whether niches are conserved or labile is not in itself particularly fruitful.” – Wiens and Graham 2005, Ann. Rev. Ecol. Evol. Syst.

“Several recent papers have mentioned that published studies on environmental niche modelling do not consistently detect phylogenetic signal, but these conclusions have been based on relatively few studies … the evidence at hand does not support the idea that phylogenetic signal should be the expected outcome of evolutionary diversification.” – Losos 2008, Ecology Letters

A Gap in the Literature• All previous reviews of niche conservatism

have reviewed examples without an explicit temporal framework

• At time 0 – no differentiation• At time -- plenty of differentiation (or all

species would be the same ecologically!)• A review is needed, particularly in light of the

burgeoning literature, in which timescale is included as explicitly as is feasible

Review• 72 published studies• 272 species• Coarse-scale environmental features only• Range-wide studies only• Time scales

– Invasion – 100 – 102 years– Longitudinal (short) – 101 – 102 years– Across geographic range – 102 – 105 years– Longitudinal (LGM-present) – 104 – 105 years– Between sister species – 105 – 106 years– Across closely related species – 105 – 106 years– Across deeper phylogenetic lineage – 105 – 107 years

Timescale and Conservatism

Controversy and Debate II“We show … that a shift of the observed climatic niche occurred between native and non-native ranges … The models fail to predict the current invaded distribution … Climate matching … may not predict the full extent of invasions.” – Broennimann et al. 2007, Ecology Letters

“… most studies investigating SDMs typically ignore prediction errors and instead focus on regions where native distributions correctly predict invaded ranges … Native range occurrences under-predicted the invasive potential of fire ants, whereas occurrence data from the US over-predicted the southern boundary of the native range.” – Fitzpatrick et al. 2007, Glob. Ecol. Biogeogr.

Aedes albopictus

• Known as the “Asian Tiger Mosquito”

• Invader; fastest spreading mosquito in the world

• Aggressive daytime biter and pest

• Known to transmit Dengue, La Crosse, St. Louis, Eastern Equine, Ross River, Rift Valley, and West Nile Viruses

Aedes albopictus

Present predicted distribution, native range in Asia

Aedes albopictus:USA invasion

Projected Asian niche into USA present to create invasion risk-map. How well did GARP perform...

Aedes albopictus: USA invasion

Aedes albopictus: world risk-map

Warren et al. 2008, Evolution• Point out that two contrasting null hypotheses

have been used – that niches are more similar than some random

expectation– that niches are identical

• Offer new quantitative metrics of niche similarity and new quantitative approaches to testing niche similarity versus difference

• Resolve one key aspect of the debate … comparing apples and oranges

Timescale and Conservatism

Broennimann et al. - Centaurea

Fitzpatrick et al. - Solenopsis

Niche-equivalent Virtual Species

-4

-3

-2

-1

0

1

2

3

4

-2 -1.5 -1 -0.5 0 0.5 1 1.5 2 2.5 3

North America

Close to Lawrence, Kansas

Niche-equivalent Virtual Species

Warren et al. Tests• Observed Hellinger distance I = 0.4668

• Translation: – The two niches are more similar than random expectations– The two niches are significantly non-identical– The “two” niches in reality were resampled from ONE niche!

• Conclusion: – Tests of niche identity are too powerful statistically, and probably are

detecting differences that are not biologically significant

0

1

2

3

4

5

6

7

8

9

0.4 0.41 0.42 0.43 0.44 0.45 0.46 0.47

Niche Similarity Test

Bobwhite Colinus virginianus

0

5

10

15

20

25

30

0.74

0.76

0.78

0.80

0.82

0.84

0.86

0.88

0.90

Freq

uenc

y

I

0

5

10

15

20

25

0.64

0.66

0.68

0.70

0.72

0.74

0.76

0.78

0.80

0.82

0.84

0.86

0.88

0.90

Freq

uenc

y

Similarity value

D

Niche Equivalency – Warren et al.“Peterson et al.’s (1999) assertion that speciation across the Isthmus of Tehuantepec ‘takes place in geographic, not ecological, dimensions’ is further challenged by rejection of the hypothesis of niche equivalency. This hypothesis is rejected among sister species in nearly every case, indicating that significant environmental niche differentiation occurs in association with most speciation events.”

BUT … Niche equivalency tests are too powerful statistically. Given sampling vagaries, modeling variation, and the highly complex and dimensional nature of the environmental space, essentially all pairs of modeled niches will differ significantly, as in Broennimann’s and Fitzpatrick’s analyses ... Are these differences biologically significant?

Regarding methodological rigor in niche modeling …

?

?

Conclusions I• Niches DO evolve• However:

• They do not evolve frequently or easily• Niches are frequently conserved over time periods of

105 – 106 yr• Evidence for associations between speciation and

niche evolution is not reliable• Researchers have not taken care to characterize

fundamental ecological niches fully, differentiating from existing subsets of niches

• Rigorous examples of niche evolution should be sought, and would be of great interest

Niche Conservatism and Speciation

• Studies to date have not considered temporal dimensions of niche conservatism versus divergence

• Most studies to date do not distinguish the fundamental ecological niche from the existing fundamental niche

• Hence, studies to date over-estimate and over-appreciate the potential for niche evolution and its role in speciation

Can EVOLVE Will change with any

range difference

Icterus graceannae:

Known occurrence points on G

Raw points Distance filter Overlay elevation Hypothesis of M

Occurrences and M Rainfall Temperature Model output

Model within M Cal in M, Trans to G Cal across G

Note that the two maps across all of G are surprisingly different from one another

Environmental variable value

Hutchinson’sDreamWorld

Environmental variable value

Wallace’sDreamWorld

Environmental variable value

Wallace’sDreamWorld

Conclusion: interpret only the portion of the response that is represented within M, or risk making unsupported assertions

Correct conditions, indicated by occurrence data

Too cold, as indicated by no occurrences within M

Too warm? No evidencewithin M

Too cold, good evidence, though beyond η(M)

Too cold, good evidence from within M

Suitable temperatures

Too hot??? No evidence within M

Too cold, good evidence from within M

Well-defined niche limits (upper and lower)

Lower limit well-defined, but upper limit undefinied. Solution 1: treat as missing data in binned analysis

Solution 2: model and anticipate upper range limit in continuous char.

ANCESTRAL STATE RECONSTRUCTION

CONTINUOUS CHARACTERS and problems …

1.0 1.1 1.2 1.3

1.0 1.1 1.2 1.3

Well-defined niche limits (upper and lower)

Lower limit well-defined, but upper limit undefinied. Solution 1: treat as missing data in binned analysis

Solution 2: model and anticipate upper range limit in continuous char.

Geositta ovenbirds

Oriole example …

Model lower and upper limits as continuous traits

Histogram of the rate of Brownian motion evolution (σ2) when uncertainty is considered. Blue = value returned when characters are coded in M only; magenta = value returned when models are calibrated in M but transferred across G. designated by a star. Slower rates indicate less evolution, whereas faster rates indicate more evolution.

Bin and permit missing data

Well-defined niche limits (upper and lower)

Lower limit well-defined, but upper limit undefinied. Solution 1: treat as missing data in binned analysis

Solution 2: model and anticipate upper range limit in continuous char.

Niche Evolution Summary• Fundamental niche is the evolvable quantity of

interest in studies of niche evolution• Realized niche (or existing niche, or worse yet

sampled sites) is a mixture of effects of niche evolution and effects of geography and landscape

• Use of environmental characteristics of occurrences, or uncareful niche models, in such analyses will introduce considerable instability

• Better approach is to account for what is and is not known directly and integrally in analyses

Biodiversity Informatics: making Primary Biodiversity data available

Biodiversity Informatics Training Curriculum Courses

• Data Capture• Biodiversity Inventories• Data Cleaning• Data Publishing• Biodiversity Data Analysis• Species Descriptions• Using R, QGIS, Refine,

EstimateS (under development)

• Biostatistics (under development)

• Public Health Applications

• Ecological Niche Modeling

• National Biodiversity Diagnoses

• Conservation Implementation

• Building Biodiversity Informatics Institutions

Project Webpage

Communications - Facebook

Communications – Google+

Share Video - YouTube

Monthly Seminar

Interchange – Scientific Journal

BITC Version 1.2

• The curriculum is basically complete– 507 videos make up the present curriculum version,

covering topics from data capture to building institutions

– by end 2015, the final modules (R, Refine, EstimateS) will be added

• The curriculum is available– online via the project webpage– in pdf format via Biodiversity Informatics– on USB keys and in DVD formats (by request)

Links

• Town Peterson town@ku.edu

• BITC webpage http://biodiversity-informatics-training.org/

• Facebook https://www.facebook.com/groups/BiodiversityInformatics/