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 [email protected]
• BITC webpage http://biodiversity-informatics-training.org/
• Facebook https://www.facebook.com/groups/BiodiversityInformatics/