Grassland- shrubland transitions: Part 1 - PowerPoint Presentation

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Grassland-shrubland transitions: Part 1

Previous LTER cycles (I-III) have focused largely of mechanisms and consequences of

shrubland

resilience

Lateral flux of water, sediment, nutrients Percolation

Schlesinger et al. (1990) “islands of fertility” or “

Jornada” desertification model

Not clear how perennial grasses are lost from the ecosystem—

a focus of long-term work since LTER IV

Feedback

Feedback

Disruption of perennial grass cover, shrubs invade

Loss of dominant grasses can be highly abrupt and irreversible

Bestelmeyer et al., 2011, Ecosphere

Drought

Abruptness and hysteresis are hallmarks of a critical transition

Do grasslands cross critical thresholds at low, but positive, levels of grass cover?

Driver-control model:

grass driven extinct directly by grazing/drought

Feedback-control model

: critical threshold of grass cover below which soil erosion/hydrologicalfeedbacks drive remaining grass cover extinct

Driver

Grass cover/production

Bestelmeyer et al, 2013, Ecology Letters

Experimental evaluation of threshold models13-year pulse perturbation experiment, heavy grazing (initiated during LTER III in 1995 as the “Stressor Experiment”)18 paddocks, 0.5 ha

Little support for feedback control model

Winter grazing resulted in biggest decline, but didnot affect rate of recoveryMesquite presence exacerbated pulse effects, but did not constrain recoveryRecovery takes a long timeMight have approached a critical threshold in one plot

Could grass patch size mediate grassland resilience?

LTER VI Proposal, Hypothesis 1(a): As grass patches become smaller and more fragmented, grass resilience decreases such that plants and tillers within small grass patches will have lower fitness and greater water stress than those in large patches.

Scale-dependent feedback theory

(after Rietkerk et al., 2004)

Leads to self organized patchiness, but also to abrupt transitions

Scale dependent feedback study Short-term studies embedded within long-term study(Stressor)144 focal plants classified to 4 patch classes(36 reps/class)

Patch type

Code

Patch Selection Rules

Focal Plant Selection Rule

Large patch interior

L(I)

Contain interior points >30cm from a patch edge

Plants located

>30

cm from the edge of large patches

Large patch edge

L(E)

Plants located

within 30 cm of edge

Medium

patch

M

>20cm wide in at least one dimension but do not contain any interior points >30cm from a patch edge

Plants located on the edge of medium patches

Small

patch

S

≤20cm from boundary to boundary in any direction

Plants located on the edge of small patches

Open

ground

OG

Not in vegetation patch and >30cm from any BOER

base

No focal plant

Least squares means for plant attributes (stolons, ramets and rooted ramets) of each patch class (Small, Medium, Large (exterior), and Large (interior)) over all time periods.  Patch ClassesAttributeSmallMediumLarge (exterior)Large (interior)Stolons47.5 ± 5.6c92.7 ± 5.6a71.8 ± 5.6b74.2 ± 5.6abRamets17.6 ± 4.3c50.4 ± 4.3a38.7 ± 4.3ab34.6 ± 4.3bRooted ramets (RR)0.8 ± 0.5b3.8 ± 0.5a2.5 ± 0.5ab2.1 ± 0.5b

Plants in medium patches had higher rates of reproductive success (RR) and effort (stolons/ramets) than in large patch interiors or small patches. Smallest patches were the worst environments, possible explanation for slow recovery (Svejcar et al, 2015, Ecosystems)

Hypothesis

1(a):

Scale

-

dependent

feedbacks

supported

Hypothesis

1(a): Scale-dependent feedbacks supported

But, reproductive success in small patches increased through a dry summerMight be a stabilizing mechanism responsible for resilience in long-term data

Measurement

DescriptionLocationsFrequencyShallow water contentsSoil water content near surface (5 – 10 cm) using data loggers & 10HSAllEvery 5 min after rain event. Every 8 hrs when dry. March 2011 to July 2014Plant physiologyPredawn water potential, photosynthesis, and 0-12 cm soil water content (Hydrosense)L(I), M, and SPost summer rain event, 15 days in 2010 & 8 days in 2011 (no photosynthesis in 2011)Soil profile water contentSoil water content measured with N-probe (10, 20, 30, 40, & 50 cm)L(I), M, S, and OG1x/month in winter & spring, every 2 wks in summer, & when plant physiology done (7/1/2010 – 5/14/2013)

Hypothesis 1(a): Do plants in smaller patches experience greater water stress?

(Duniway, Bestelmeyer, Svejcar, in prep)

Hypothesis 1(a): Ecohydrology and scale-dependent feedbacks

Greater water stress and lower net carbon assimilation in medium and interior of large than in small patches.

G

reater

infiltration under larger than smaller patches or open ground immediately following rain events.Mean water capture (difference between pre- and post-rain VWC) of 15 events show large patches have greater capture than small patches or open ground.Very few days with significant differences among patch classes, suggesting the effects of short-range facilitation on soil water balance are quickly erased by greater water use in large patches.

Hypothesis 1(a): Ecohydrology and scale-dependent feedbacks

Scale-dependent

feedback-like patterns in plant reproduction seem to be poorly explained by

ecohydrologyMay instead be related to how plants allocate resources in different patch contexts. Results point to the driver-control model of ecological thresholds in the Stressor caseBut, plant-soil erosion feedbacks may be important in other situations, such as when defoliation is sustained year after year (next).

Conclusions

at

this

point

Future

plans

Hypothesis

1(a):

Analysis

of ultra-

high

resolution

(UAV)

imagery

data

from

Stressor

II to

test

new

early

warning

signals

(EWS) (

Vishwesha

Guttal

,

Indian

Institute

of

Science

)

Final record of

grass

recovery

for

current

phase

in

fall

2016 (20

years

)

New pulse

perturbation

to test

for

EWS

along

a

smooth

gradient

using

UAV

imagery

and

soil

nutrient

/

erosion

measurements

(

possibly

spring

2017)

Integrate

interpretations

with

Nate

Pierce’s

work

on

grass

responses to

varying

shrub

density

neighborhoods

(

tomorrow

)