Acmispon Glaber Var

Home , Acmispon, Acmispon glaber, Artemisia californica, Ceanothus crassifolius, Ceanothus tomentosus, Eriodictyon crassifolium

Finding Balance: Considering Species' Traits, Species Distribution Models, and Climate Forecasting in Seed Sourcing Decisions

Arlee M. Montalvo Nov. 15, 2016 Do No Harm Workshop, Davis, CA Acknowledgements:

My collaborators! Erin C. Riordan- the modeling and maps Jan L. Beyers- editing, profile assistance

Thanks to USFS Pacific Southwest Research Station and RCRCD for funding and UCR and UCLA for logistical support! California shrublands occupy a diverse landscape: Ecological Sections and Subsections Goudey and Smith (1994) updated with ECOMAP (2007) Parent geology

continental influence

topography ocean influence

Precipitation and temperature Ecological Sections can be diverse and contain many contrasting Subsections

Elevation: 300 to 11,500 ft Precipitation: 6 to 40 inches Temperature: 40° to 70°F Goudey & Smith 1994 Growing Season: 150 to 300 days Environmental diversity supports amazing biological diversity

California shrublands and their foundation plant taxa are diverse protecting, supporting, managing native biodiversity chaparral alluvial scrub coastal sage scrub Many foundation species of shrubs are distributed across multiple Ecological Sections and plant communities

Plant Community Plant Community Scientific Name Life Form‡ ALSC CHAP CSS MIX Scientific Name Life Form‡ ALSC CHAP CSS MIX Acmispon glaber var. brevialatus† suffr subshr X X Eriodictyon trichocalyx var. lanatum suffr subshr X X Acmispon glaber var. glaber † Forsuffr subshreachX ofX 36X shrubsX E. t. var &. trichocalyx subshrubs: suffr subshr X X X Adenostoma fasciculatum shrub X X X Eriogonum fasciculatum var. Arctostaphylos glandulosa (3 subsp) shrub X fasciculatum subshrub X X Artemisia californica subshrub X X X E. f. var. foliolosum subshrub X X X X E. f. var. polifolium subshrub X X Ceanothus crassifolius var. c. shrub X X • Running models that estimate currentEriophyllum confertiflorumand future var. c.† suitablesuffru per. X X X Ceanothus cuneatus var. cuneatus shrub X Hesperoyucca whipplei suffr rosette X X X X Ceanothushabitat leucodermis shrub X Heteromeles arbutifolia shrub X X Ceanothus megacarpus var. m. shrub X Lepidospartum squamatum shrub X Ceanothus oliganthus shrub X Malacothamnus fasciculatus var. f.† subshrub X X X Ceanothus• Assembling perplexans profilesshrub withX information about physiology, ecology, Malosma laurina shrub X X X X Ceanothus tomentosus shrub X demographics, life-history traits, Prunusand ilicifolia population subsp. ilicifolia geneticsshrub to X X Ceanothus vestitus shrub X Quercus berberidifolia shrub X X Cercocarpusinform betuloides interpretation var. b. shrub andX practicalX Rhamnus applications crocea of modelshrub resultsX X Corethrogyneand filaginifolia† seed sourcingsuffru per. decisions X X X X Rhamnus ilicifolia shrub X Encelia californica subshrub X Rhus ovata shrub X X Encelia farinosa subshrub X Salvia apiana suffr subshr X X X Eriodictyon crassifolium var. c. suffr subshr X X Salvia mellifera subsh/shrub X X X X E. c. var. nigrescens suffr subshr X X X Most taxa have been studied for fire response, many for drought tolerance, but few for genetic patterns

Distribution of California sagebrush Genetically based latitudinal variation in (Artemisia californica) Artemisia californica secondary chemistry

Common garden studies have shown correlated patterns in use of plants by arthropods and in traits related to water economy

Pratt et al. 2014. Oikos. 123(8) pp 953-963. Figure 3. DOI: 10.1111/oik.01156 Acmispon glaber (aka Lotus scoparius), California broom, deerweed •self-compatible subshrub with infra-specific variation •two named varieties - distributions differ but overlap •differ in morphology and habitat affinities •common garden work local adaptation, outbreeding issues A. g. var. glaber A. g. var. brevialatus

(Montalvo & Ellstrand. 2000 Conservation Biology, 2001 AJB) Careful choice of species, subspecific taxa and seed sources for projects can:

• Minimize risk of maladaptation • Maintain variation and adaptive potential • Reduce risk of inbreeding and outbreeding depression • Preserve important interactions • Increase long-term success of projects How do we factor in climate change?

Observed shifts in climate variables for 1981-2010 relative to 1951-1980

Δ MIN DJF Temp (C) ΔMAX JJA Temp (C)

using CA-BCM downscaled Δ PPT % Δ CWD (mm) climate data (270 m resolution) Dealing with a complex world: Outline

• Starting point for seed sourcing • Consider climate change and Species Distribution Modeling • Plant traits important in decision frameworks • Decision frameworks and provenancing models to help keep us on right track For the many species with no seed transfer research, Provisional seed zones for native plants reflect the complex landscape and associated climate

a starting tool to be combined with expert knowledge of plants A. D. Bower, J. B. St. Clair, V. Erikson. 2014. Ecological Applications 24:913-919. Ecological Archives A024-053-A1. Based on high resolution climate data & aridity index. Seed Zones Mobile http://www.fs.fed.us/wwetac/threat_map/seed_zones/Seed_Zone_Google_Map_Links.pdf

How effective are these tools for southern CA? What about climate change? Will rate of climate change exceed species’ capacity to respond?

Prov. Seed Zones

Tmin/AHM 35 - 40 Deg. F. / 6 - 12

Baseline 1951-1980

MIROC RCP8.5 CNRM RCP 8.5 2040-2069 2040-2069 Detailed studies of long-lived tree species Genetic maladaptation of coastal Douglas‐fir seedlings to future climates

Assisted migration: ”the purposeful movement of individuals or propagules of a species to facilitate or mimic natural range expansion or long distance gene flow within the current range, as a direct management response to climate change” (Havens et al. 2015. NAJ)

St. Clair, B. J., and G. T. Howe. 2007. Global Change Biology 13(7): 1441-1454 Seeding sourcing for the future?

• First, what is projected loss of suitable habitat? • Consider risks from moving too much or too soon: • poor adaptation to current conditions • growth phase mismatches with seed/pollen dispersers • outbreeding depression • unanticipated changes in community interactions • unanticipated aggressiveness/weakness in novel environment

• Are there other, interacting risk factors? • Action should not cause more harm than no action Dealing with a complex world

California Basin Characterization Model (CA-BCM): applies a monthly regional water-balance model to simulate hydrologic responses to climate at the spatial resolution of a 270 m grid • High resolution (270 m) baseline (1951-1980), current (1981-2010) and projected (2049-2060) climate and hydrologic surfaces • Variables used in modeling: strong drivers of plant distribution

– Winter Tmin, Summer Tmax, – T seasonality – Winter PPT, Summer PPT – Climatic Water Deficit (CWD), Actual Evapotranspiration (AET) Flint et al. 2013 Ecological Processes Projected change in southwestern CA climate 2040-2069 relative to 1951-1980

RCP Percent change in annual PPT (%) PPT annual in change Percent

Increase in minimum winter Temp (°C) Projected change in southwestern CA climate 2040-2069 relative to 1951-1980

“Hot/Wetter”

“Hot/Drier”

“Warmer/Drier” RCP “Hot/Drier”

Percent change in annual PPT (%) PPT annual in change Percent “Hottest/Very Dry”

Increase in minimum winter Temp (°C) Species distribution models for southern California region

Habitat suitability + baseline

Species occurrences Baseline conditions future (Herbarium records (1951‒1980) and plot data) MAXENT Species Distribution Model (SDM) algorithm Planning Tools

Tseas Future conditions (2040‒2069) Species Distribution Modeling (SDM)

• Estimates spatial pattern of suitable habitat and shifts in suitable habitat by pooling data over species’ range • Results vary with global change model employed • Some caveats (concerns) – Doesn’t show population level patterns of variation, biotic interactions, or demographics – Not all populations likely to do well in all suitable habitat – Assumes no adaptive capacity to respond to change – Other, very important risks factors not in model – Climate may interact with other drivers of change

Extending SDM to incorporate population level data is enormously complex SDM’s run on the southern California extent of species’ ranges and on infra-taxa

Genetically based latitudinal variation in • Most species likely to have Artemisia californica secondary chemistry populations that differ genetically from north to south

• SDM results on smaller extent differ from SDMs run on full species range

• Resulting projections of habitat suitability are likely more realistic for the extent under consideration

Pratt et al. 2014. Oikos. 123(8) pp 953-963. Figure 3. DOI: 10.1111/oik.01156 Species Distribution Models (SDM) estimate future stability, loss, and gain of suitable habitat

SDM of projected change in habitat suitability for Artemisia californica Occurrence data Baseline (1951-1980) suitability Projected (2040-2060) stable suitability

Projected future suitability gain Projected future suitability loss MAXENT algorithm

modeling extent =urban/agriculture Example of plant with infra-specific taxa

•distributions of Acmipson glaber varieties differ, but they overlap •common garden work showed local adaptation and outbreeding issues

A. g.var. brevialatus

A. g. var. glaber Acmispon glaber var. brevialatus Acmispon g. var. glaber

Baseline (1951-1980) habitat suitability Acmispon glaber var. brevialatus Acmispon glaber var. glaber loss loss SDM projected habitat suitability to mid century (2040-2069):

gain gain var. brevialatus, 55–98 % stable loss > gain (3)

var. glaber, stable stable 1–65 % stable; loss > gain (5) = high climate exposure Species vary in their exposure, resilience, and vulnerability to climate change and translocation

• What traits capture differences in species’ ability to persist in place, adapt, and migrate? • What traits are associated with different levels of risk of maladaptation or outbreeding depression? Dealing with a complex world

We need to know about the plants! Plant traits influence migration (gene flow) Fruit type x primary / secondary dispersers

near far (meters) (km)

Birds, Birds, mammals / squirrels / Gravity / ants, rodents rodents, water Wind / ants rodents Stature and structure influence gene flow Wind dispersed seeds or pollen

near (within 10 m) far (100’s of meters)

height Plants x animals x habitats influence migration Type of pollinator: foraging distance, constancy near far (meters) (km)

gnats, beetles, bumblebees, social tiny solitary bees butterflies, moths bees, hummingbirds, bees (honeybee) Barriers to migration across a landscape Heterogeneity and fragmentation can influence dispersal

Parts of California are highly Decreasing porosity fragmented, especially along coast of barriers Correlates between life-history traits and spatial genetic structure (differences among populations) in plant species

Correlation with spatial genetic structure Trait Highest Lowest Breeding system Selfing species Outcrossing, wind-pollinated Life form Annual Long-lived, woody perennial Seed dispersal Gravity Gravity then animal-attached mechanism

Successional status Early Late Taxonomic status Dicots Gymnosperms Regional distribution Temperate Boreal-temperate from Rogers & Montalvo 2004, derived from Hamrick & Godt 1990 Higher levels of genetic differentiation and structure are associated with:

• Habitat heterogeneity and geographic isolation • Low gene-flow potential (e.g., short, self-compatible herbs, gravity dispersed seeds) • Local adaptive differences and unique gene interactions • Local adaptation (home site advantage) at smaller scale • Higher likelihood of problems following mating with other populations

On this end of continuum, one would decrease distance limits to collection Dealing with a complex world

• Starting point for seed sourcing • Consider climate change and Species Distribution Modeling • Plant traits important in decision frameworks • Decision frameworks and provenancing models to help keep us on right track A framework to aid “distance” decisions More conservative/near In between? More relaxed/longer distance sourcing distance sourcing

Species traits Narrow and/or habitat specialist Widely distributed/or generalist Little long-distance gene flow Extensive long-distance gene flow Low phenotypic plasticity High phenotypic plasticity Narrow environmental tolerance Wide environmental tolerance

Habitat traits Historically fragmented Recently fragmented High quality Low quality/degraded Ancient/stable landscape Younger/dynamic landscape

Taxonomic understanding Taxonomic uncertainty, cryptic species Taxonomic stability, well known High hybridization potential Low hybridization potential Low rates of evolution (conserved) High rates of evolution

Distance ecological/genetic/geographic Modified from Havens, Vitt et al. 2015. Natural Areas Journal How does Acmispon glaber var. brevialatus score? More conservative/near In between? More relaxed/longer distance sourcing distance sourcing

Habitat traits Historically fragmented Recently fragmented High quality Low quality/degraded Ancient/stable landscape Younger/dynamic landscape

Modified from Havens, Vitt et al. 2015. Natural Areas Journal Modified from Shoo, Hoffmann, Garnett, et al. 2013. Climate Change 119:239–46

Evaluate direction of shifts in future climate of ecoregions and seed No seed zones and compare with shifts in habitat suitability revealed by SDMs zone shifts warranted If taxon SDM is available, is there substantial risk

that habitat climatic suitability will decline? NO YES

Taxon with high levels of plasticity, Can taxon likely tolerate expected YES genetic diversity, gene flow, or shifts in place? (secure refugia) historical climate tolerance NO

Is taxon able to migrate &/or is it YES sufficiently genetically diverse for adaptive evolutionary response? Limit zone combinations for seed YES sourcing to adjacent zones and logical NO Restore migration corridors? direction of expected shifts. NO Candidate for “assisted migration”. Consider scale of expected shifts in Taxa with low levels of genetic diversity, low YES gene flow, or adapted to highly localized habitat suitability relative to scale of climate or edaphic factors? local adaptation, migration & risk Provenancing models deal with common questions about seed sourcing

• How can we move seeds, while minimizing risk of maladaptation and genetic mismatches? • What type of seed sourcing (provenancing) model should we use within seed zones or among seed zones?

Projected increase in aridity

Source planting populations site

(modified from Prober et al. “Climate-adjusted provenancing” 2105. Frontiers Ecol. Evol.) Summary

• SDM can be used with detailed ecological, physiological, and population genetic information to inform seed sourcing decisions. • Not all baseline or future “suitable habitat” is appropriate or available. • Distance models for sourcing seeds within current climates can also apply to assisted migration. • Candidates for assisted migration: high climate exposure, low gene flow/adaptive capacity, or highly compromised dispersal capacity • Other risk factors may be more important or interact with climate change Managing biological diversity in southern California shrublands

Questions?

chaparral alluvial scrub coastal sage scrub Building profiles for ~44 taxa, fully referenced

• Species: Photos, taxonomy, relationships • General: Mapped occurrences, life-history traits • Habitat: Associated vegetation and environmental attributes • Climate change and projected future suitable habitat: Species distribution models and forecasts, fragmentation • Growth, reproduction, and dispersal: Including fire effects • Biological interactions: Competition, microorganisms, herbivory, seed predation, animal dispersers • Ecological genetics: Ploidy, plasticity, pattern and scale of genetic variation, translocation risks • Seeds: Dormancy, germination, planting, seed increase • Ecological and evolutionary considerations for restoration: summary and implications FIRST SET TO BE POSTED IN 2017 at www.RCRCD.ORG National Native Seed Strategy for Rehabilitation and Restoration/ 2015-2020

• The vision: the right seed in the right place at the right time • The Mission: To ensure the availability of genetically appropriate seed to restore viable and productive plant communities and sustainable ecosystems.

A public-private partnership of organizations that share the goal: to protect native plants by ensuring that native plant populations and their communities are maintained, enhanced, and restored. Protecting/supporting/managing biodiversity