Landscape Ecosystem Perspective

1. Background on ecosystem classification

2. Ecological variation among ecosystems

3. Applications for resource mgt

Xeric oak/blueberry ecosystem (35o01'"N, 83o00'25"W)

Xeric chestnut oak/mountain laurel ecosystem (35o01'"N, 82o59'13"W)

Submesic oak/mixed flora ecosystem (34o59'"N, 82o54'18"W)

Mesic hardwoods/bloodroot ecosystem (35o01'"N, 83o00'20"W)

Mesic hemlock/rhododendron ecosystem (35o02'"N, 82o49'09"W)

• Soils, geomorphology, and biota vary from place to place across a landscape

• These 3 factors interact at a given spot on the landscape to produce an ecosystem

• Landscape ecosystem – volumetric unit of the landscape

• Ecosystem classification – grouping similar sites into ecosystem types

Vegetation

Geomorphology Soils

Ecosystem classification identifies interrelationships within and among geomorphology, soils, and vegetation

Ecosystem Type

Ecological Properties

Terrestrial Ecosystem Survey Integrates climate, geology, soils, and vegetation

MA; http://nesoil.com/plymouth/catena.gif

Soil catena

Soil-geomorphic relations in upper Michigan

• Classification is a data reduction or information reduction technique

• This works because combos of similar geomorphology, soils, and veg reoccur across a landscape

• Continuous vs. classification

• An ecosystem type has ecological properties (e.g., soil texture), which differ among ecosystems

• Notes on multifactor and multivariate: simply mean many factors or variables

• Classification has long history in ecology – EC emphasizes interactions and geomorphology/soils

• Geomorphology/soil relatively stable – e.g., topographic features, soil texture

• Vegetation useful, but not essential

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Ecosystem type

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)Identifying key environmental variables

Southern Appalachian Mountains solum = A + B horizon

• EC not a panacea; yet practical tool

• Examples of EC systems – US FS TES, NRCS site types, research-grade EC

• EC provides framework for studying how properties vary among ecosystems

• Here are some examples:

Nutrient Cycling

Landscape ecosystem control over tree mortality

Longleaf pines in SE USA – in very moist, waterlogged ecosystems, rooting depth is restricted.

Trees more susceptible to wind damage (uprooting) due to shallow root system

But lightning mortality important on upland xeric sites!

Plant composition and diversity

From a Michigan project of the federally endangered Kirtland’s warbler in jack pine forests

Findings:  We noted significant differences in climate, physiography, soil, and vegetation between 10 landscape ecosystems at the ecological level of landforms.  Moreover, jack pine height growth differed significantly among the 10 ecosystems, and the landforms exhibited marked differences in the timing of initial colonization and duration of occupancy by the warbler.  Ecosystems favoring jack pine growth - those with a warmer microclimate or higher-quality soil - were typically colonized first but had the shortest duration of occupancy, while colder, drier, and less fertile ecosystems were colonized later but had longer durations of occupancy. 

Summary of warbler relations to landscape ecosystem habitat

Archaeological Resources

• Upper Michigan: Locations of historical logging camps can be predicted using LEC

• Eastern white pine was desirable timber species in late 1800s – logging camps located by pines and by water for transporting logs

• Michigan Archaeologist 43:87-102.

Cooper 1913 Bot Gaz

Examples of Multiple Pathways

1920-2660 m elevations

6300-8700 ft

Ponderosa pine, Gambel oak, aspen

Entisols, Inceptisols, Alfisols, Mollisols

Slope gradients mostly < 10%

60 trees/ha

132 trees/ha

Methods• 102, 0.05-ha plots sampled in 2003 (66 core plots)

• 55, 500, 513, 523, 536, 551, 558, 570, 582, 585, and 611 soil types

• Geomorphology, soils, plant communities

• Cored 2 dominant, open-grown pines of pre-1875 origin

• Seed bank samples

• 0-15 and 15-50 cm soil samples analyzed for texture, gravel content, organic C, total N, pH, CaCO3 equivalent, and water-holding capacity

• Multivariate and univariate analyses

Ecosystem classification

Cluster analysis and ordination

10 ecosystem types on 66 plots

Ecosystem types internally similar in environment and vegetation characteristics

Black cinders/Phacelia (558) Red cinders/Bahia (513) Clay basalt/Gutierrezia (523) Xeric limestone/Bouteloua (500) Mesic limestone/mixed flora (536) Xeric basalt/Muhlenbergia (551, 570) Rocky basalt/Sporobolus (570, 582, 585) Mesic basalt/Festuca (551, 570, 582, 585) Aspen/Lathyrus (611) Park/Symphyotrichum (55)

Black cinders/Phacelia

452800

3905545

UTM 452794E, 3905543N

Elevation 2007 m

Low upper soil fertility

Cinders Clay

1 Haasis, F.W. 1921. Relations between soil type and root form of western yellow pine seedlings. Ecology 2:292-303.

Ponderosa pine seedling growth in 19201

Mesic basalt/Festuca

UTM 432074E, 3903341N

silt: 53% (0-15 cm) organic C: 2.2% total N: 0.14%

C3 Arizona fescue

Xeric basalt/Muhlenbergia

UTM 441833E, 3917442N

silt: 41% (0-15 cm) organic C: 1.2% total N: 0.09%

C4 mountain muhly

Red cinders/Bahia

UTM 446730E, 3915773N

Elevation 2326 m

High gravel content, sandy

loam soils, slow tree growth

UTM 452716E, 3898173N

Elevation 2079 m

Rocky basalt/Sporobolus

UTM 445788E, 3877037N

Elevation 7252 ft

Lupinus argenteus Lathyrus lanszwertii Vicia americana

0-15 cm soil total N: 0.26%

next highest ecosystem: 0.15%

Populus/Lathyrus

UTM 424674E, 3886663N

Elevation 2215 m

Park/Symphyotrichum 31% 0-15 cm clay

Age 50-150 yr mean annual diameter increment of pre-1875 origin ponderosa pine

Means without shared letters differ at P < 0.05 (Fisher’s LSD) Error bars are 1 SD

Plant species richness

Means without shared letters differ at P < 0.05 (Fisher’s LSD)

Error bars are 1 SD

Soil moisture (% of dry soil weight, 0-15 cm depth) for 7 ecosystems measured June 19, 2004. Means without shared letters differ at P < 0.05. Error bars are 1 SD.

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Estimating ponderosa pine diameter growth based on importance of key plant species

51, 10-m2 exclosures

Grazing effects partly related to environmental gradients

Environmental influences:

- vegetation productivity - water availability - animal movement - other factors

Soil Seed Bank Assessment

Seed bank composition(greenhouse emergence method)

103 seed bank species detected, 280 aboveground species

Untreated samples, 0-10 cm mineral soil

Erigeron divergens, fleabane (35% of 102 plots) Verbascum thapsus, mullein (25%) Gnaphalium exilifolium, cudweed (13%) Muhlenbergia minutissima, annual muhly (12%) Chamaesyce serpyllifolia, sandmat (12%) Carex geophila, White Mountain sedge (12%)

Others: Muhlenbergia montana, Nama dichotomum, Poa fendleriana, Chenopodium graveolens

Ecosystem-specific seed bank composition

e.g., black cinders

wishbone fiddleaf annual muhly fetid goosefoot

Nama dichotomum (wishbone fiddleleaf)

21 plots where it occurred in seed bank samples:

0-15 cm sand = 70%

45 plots where it did not occur in seed bank samples:

0-15 cm sand = 37%

Landscape Units Differ in Forest Composition and Change

S-facing ponderosa pine N-facing white fir

Topographic Moisture Gradients

“Pygmy” bonsai site – white fir, ponderosa pine

Red brome