Northern Spruce Bog - APn80

Northern Spruce Bog

Forest description

Black spruce-dominated peatlands on deep peat. Canopy is often sparse, with stunted trees. Understory is dominated by ericaceous shrubs and fine-leaved graminoids on high Sphagnum hummocks.

Community Description

APn80 forests are a common bog community throughout the Laurentian Mixed Forest province, ranging from Lake of the Woods down to Mille Lacs and through the entire Arrowhead region (see map; 191 relevés, 367 ECS worksheets). Occurrences of APn80 can be found in the Northern Minnesota & Ontario Peatlands (MOP), Northern Superior Uplands (NSU), Northern Minnesota Drift & Lake Plains, (MDL) and Western Superior Uplands (WSU) sections of the state. Few occurrences are outside the Laurentian Mixed Forest province.

Distribution in Minnesota

Distribution map for APn80

Vegetation Structure & Composition

Description is based on summary of vascular plant data from 84 plots (relevés) and bryophyte data from 17 plots.

  • Moss layer consists of a carpet of Sphagnum with moderately high hummocks, usually surrounding tree bases, and weakly developed hollows. S. magellanicum dominates hummocks, with S. angustifolium present in hollows. High hummocks of S. fuscum may be present, although they are less frequent than in open bogs and poor fens. Pleurozium schreberi is often very abundant and forms large mats covering drier mounds in shaded sites. Dicranum species are commonly interspersed within the Pleurozium mats.
  • Forb cover is minimal, and may include three-leaved false Solomon’s seal (Maiathemum trifolium) and round-leaved sundew (Drosera rotundifolia).
  • Graminoid cover is 5-25%. Fine-leaved graminoids are most important and include three-fruited bog sedge (Carex trisperma) and tussock cottongrass (Eriophorum vaginatum).
  • Low-shrub layer is prominent and dominated by ericaceous shrubs, particularly Labrador tea (Rhododendron groenlandicum), which often has >25% cover. Other ericads include bog laurel (Kalmia polifolia), small cranberry (Vaccinium oxycoccos), and leatherleaf (Chamaedaphne calyculata). Understory trees are limited to scattered black spruce.
  • Canopy is dominated by black spruce. Trees are usually stunted (<30ft [10m] tall) with 25-75% cover. Some sites have scattered tamaracks in addition to black spruce. Canopy can be dense and taller than 30ft on well-developed crests of raised bogs, where surface peat is elevated above the water table and tree roots are better aerated.

Notes: Vegetation is composed only of bog species (see Appendix D in Field Guides); minerotrophic species are absent or present only as single individuals or single clones. Overall species diversity is low. In recently developed bogs, isolated minerotrophic species whose roots still have access to underlying minerotrophic groundwater may be present for a short period until overwhelmed by Sphagnum development. When upland seed sources are present nearby, seedlings of deciduous tree species (especially red maple, northern red oak, or paper birch) may be present on Sphagnum hummocks but do not survive to become saplings or trees.

Landscape Setting & Soils

APn80 is most extensive and best developed in peatlands on the eastern Agassiz, Aitkin, and Upham glacial lake plains, where underlying impermeable clay layers minimize groundwater movement through the peat. APn80 also occurs in peat-filled basins on nutrient-poor outwash plains, in scoured bedrock terrain, and on non-calcareous till. On these landforms, the basins are in small watersheds and receive minimal surface water input. APn80 can also occur on floating mats bordering low-alkalinity lakes and ponds. Soils are typically deep peat (>40in [1m]), although peat depth can be less in scoured bedrock landscapes or on nutrient-poor sand plains. The upper peat layer is poorly decomposed (fibric) peat formed from Sphagnum. It may be underlain by more decomposed peat of variable origin. Surface water is very acidic (pH <4.2), and mineral concentrations, particularly Ca++, are extremely low. Water table is usually at or near the surface but can drop during periods of drought.

Tree Suitability

The suitability index is our estimate of a tree's ability to compete with all plants in a particular NPC Class without silvicultural assistance.  The data come from forests approaching rotation age or older. The raw index is based upon the product of percent presence and mean cover-when-present (below) within the set of relevés classified as that NPC. Plants are ranked by their raw index and the full rank order is partitioned into 5 equal groups of plants and re-scaled to yield the suitability index ranging from 1 to 5. This is done so that the indices can be compared within the NPC (below) or with other NPC classes (statewide suitability table[AJ(1]). 

It is important to note that the table presented below is a landscape summary of how trees perform on average in a NPC Class. At the stand-scale current stocking and any knowledge of the stand's disturbance/management history should inform how the suitability table can be used. Discussion of stand-scale application of the table follows below the table. 

The table is also useful at the landscape-scale when there are restoration or conservation needs for the NPC Class itself, or when forest plan directives call for a management emphasis of a particular species. Species with a high suitability index that are not currently present on the site can be introduced to the site with less risk than species with a lower index. 

Learn more about suitability

A tree species is 'suited' to a site when its physical and genetic makeup allow for it to survive and reproduce given the constraints of a site's physical environment AND co-occurring vegetation. Ecologists call this the 'realized niche' of a tree. Our suitability index is based upon the assumption that a tree is highly suited to a site when we see it often and in great abundance in its Native Plant Community Class.

These tables are intended to help foresters decide which tree species to silviculturally favor or introduce on sites that have been classified using the Field Guides to the Native Plant Communities of Minnesota1. Trees with excellent suitability should grow well with very little silvicultural treatment other than providing the correct light and seedbed environments for establishment and recruitment. Trees with poorer suitability for a site can be grown to meet specific objectives, but the forester should expect progressive increases in cost and risk for trees with good to fair to poor suitability rankings. The underlying assumption for using these tables is that when trees are naturally suited to their site, they are vigorous. Vigor should translate to superior quality, resistance to disease, capacity for natural regeneration, and the ability to withstand fluctuations in climate. 

Suitability Index
Suitability is a mathematical calculation. The data for this calculation come from 6,303 vegetation plots that have been classified as belonging to one of 54 forested NPCs. Two metrics -- commonness and local abundance -- are the elements of suitability.

A plant is 'suited' to a NPC when we often find it there. Percent presence was our metric of commonness. Similarly, a plant is 'suited' to a NPC when it tends to occur in abundance when present. Mean percent cover-when-present was our metric of local abundance. The suitability index is the product of percent presence and mean percent cover-when-present. 

Example: Of the 6,306 sample plots, 757 were classified as Northern Mesic Hardwood Forest (MHn35). Basswood trees occur in 483 of the 757 plots. Thus, its percent presence as a tree is (483/757)*100= 63.8%. The mean cover of basswood trees on those 757 plots is 16.5%. Thus, its raw suitability index is 63.8*16.5=1,053. There are 158 species with >3% presence in MHn35 forests and basswood's rank order on a scale of 1-5 is 4.8, its standardized suitability index. The index is standardized so that basswood's suitability can be compared among different NPC classes.


Tree suitability table for APn80 trees

Legend for Tree suitability values
Suitability index valuesCrop Tree PotentialColor
4.0 - 5.0ExcellentGreen
3.0 – 3.99GoodBlue
2.0 – 2.99FairYellow

In general, trees with higher suitability indices are better choices as crop trees than trees with lower indices. APn80 sites offer little choice of crop trees, with just two species having a good or excellent suitability. Black spruce is ranked as the only excellent crop tree by virtue of its frequent occurrence and high cover-when-present on APn80 sites. It is always the management target because it alone can form the cover type. Tamarack is ranked as a good crop tree, and stands can be managed to perpetuate tamarack as a co-dominant whether for its inherent value or as a future seed source. No amount of silvicultural manipulation will alter by much the relative abundance of these trees because the site’s water chemistry strongly selects for black spruce.

Tree Response to Climate Change

Due to global warming, land managers are bracing for local vegetation shifts to plants whose North American ranges are warmer and drier than their current habitat. Minnesota's climate has warmed approximately 2oF since temperature records have been collected and archived (ca. 1900). The rate of warming has noticeably accelerated since 1980, affecting winter-low temperatures more so than what is observed in other seasons. However, all seasons now have warmer temperatures than the long-term average. Unlike some parts of the continent, Minnesota has seen an increase of about 3" of rain annually. However the year-to-year fluctuation and rainfall in a particular storm have become incredibly variable and unpredictable. Minnesota is experiencing both drought and flooding extremes over several time scales. 

Differences among the 52 forested NPCs are related very much to water availability for trees and understory plants. Forested communities have different capacities for interception, infiltration, storage, and runoff. Thus we expect them to react differently to changes in the hydrologic regime -- whatever that may be. The table below presents our best guess as how trees currently suited to this NPC will react to a warmer and wetter climate. Keeping the full complement of trees on-site is a good hedge against future climate uncertainty.

Learn more about climate change

Climate Shift Calculations
Due to global warming, land managers are bracing for local vegetation shifts to plants whose North American ranges are warmer and drier than their habitat in Minnesota. An analysis of range climate was used to assign and adjust 'synecological' scores for our plants with regard to moisture (M) and temperature (H). The scores range from 1 (dry/cool) to 5 (wet/warm). The difference between a plant's individual synecological score and the mean synecological score of its community provides some insight as to whether that plant would benefit or suffer should its local environment become warmer or wetter. 

Example: For each of the 256 MHn35 vegetation plots, the M score of all component plants was summed and averaged to yield a score for each plot. Then the plot scores were summed and averaged to yield an M score for the community, which in this case was 2.3. The adjusted M score for basswood is 2.01, which is drier than 2.3. Thus, we assume that basswood would benefit from a slightly drier conditions. Similarly, the H score for basswood is 4.03, which is substantially warmer than the 2.9 mean for the MHn35 community ... suggesting that basswood would greatly benefit if MHn35 sites get warmer. 

 


Climate in Minnesota has been getting warmer and wetter. If this trend continues the descriptions in the table forecast the direction and magnitude how we expect APn80 trees to respond. The responses of “slight” or “significant” increases/decreases represents a full unit departure from the mean synecological score for the APn80 community. 

Tree habitat response to climate change in APn80

Tree Establishment and Recruitment

The vertical structure of releves was used to interpret the ability of trees to establish themselves and recruit to taller strata under the canopy of a mature forest and on seedbeds associated with older forests. The goal was to develop an appreciation of which trees are capable of developing enough advance regeneration to fully stock a future stand by natural regeneration. For trees with modest advance regeneration, we wanted to figure out if the problem seems to be related to poor establishment or poor recruitment -- issues that can be silviculturally resolved. For trees with little or no advance regeneration but good or excellent suitability as a tree, we assume that even-aged systems would be required to perpetuate them in that community.

Establishment and recruitment indices are calculations designed to estimate how a tree performs in different size classes with no silvicultural assistance:

1. small regenerant <10cm tall, R-index

2. seedling 10cm -- 2m, SE-index

3. sapling 2m -- 10m, SA-index

4. tree >10m, T-index

The index is the product of percent presence, mean percent cover-when-present, and mean number of reported strata. The index is re-scaled to run from 0 to 5 so that suitability can be compared among different NPCs.

Learn more about establishment and recruitment indices

The tree height data from releves was transformed into 4 standard height strata:  regenerants <10cm tall, seedlings 10cm -- 2 m tall, saplings 2 -- 10m tall, and trees >10m. These height breaks were used because they are the most frequently used on releves to describe the natural structural breaks in forests. Still, some releves report strata that span our standard height seams and we had to apportion the presence of the tree and its percent cover into our standard classes. This was done by splitting the reported strata into the 8 individual height classes and evenly splitting the cover among the classes. For example, sugar maple reported in a D3-6 layer (0.5-20m) comprises four individual height classes that need to contribute cover to our standard seedling, sapling, and tree strata. The cover of sugar maple in that stratum was class 3 (25-50% cover). Using the mid-point rule as for suitability (see above), cover class 3 is converted to 37.5%, and the apportionment is 37.5% / 4 = 9.37% cover awarded for sugar maple in each height class. After cover was awarded to all individual height classes in a releve, they were then lumped into the standard strata and the individual covers summed.

For each standard stratum we calculated an index of 'regeneration success' for the tree species. We settled on three measures of success:

First, trees were considered successful if they were common in a particular stratum. Presence is our measure of stratum commonness, and below is how seedling presence was calculated. The parallel calculation was done also for regenerants, saplings, and trees.

SE Presence = (# of releves with the tree present as a seedling / total # of releves for the community) * 100

Second, trees were considered successful if we found them to be abundant in a particular stratum. Mean cover-when-present (MCWP) was our measure of stratum abundance, and below is how seedling MCWP was calculated. The parallel calculation was done also for regenerants, saplings, and trees.

SE MCWP = sum of all seedling cover of tree / number of releves wit

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h the tree present as a seedling

Third, trees were considered successful recruiters if we often found it in multiple strata. As a measure of recruitment complexity we calculated the mean number of strata when present (MSWP) reported in the original releves (not our standard strata) for a species. We used this number as a weighting factor to help segregate species that develop a presence in many layers from those that don't develop a lot of strata because they probably need some kind of disturbance to develop an understory cohort. 

MSWP = sum of all reported strata for a species / number of releves in which the species occurs

From these three measures of stratum success we calculated the raw recruitment index by multiplying the numbers together. Below is how the raw seedling index was calculated.

Raw SE Index = SE presence * SE MCWP * SE MSWP

For each stratum -- regenerants, seedlings, saplings, and trees -- the ranges of raw index scores are different and not comparable between strata and between communities. To allow comparison, the raw scores were ranked and then re-scaled so that the lowest raw score was zero and the maximum was five.

The indices of regeneration were placed into classes as for suitability so that in tables, foresters can quickly identify the species that tend to have poor, fair, good, or excellent regeneration in mature forests that have not been silviculturally manipulated in the recent past.
 

Regeneration IndexEquivalent PercentileDescriptor
0-10-20%none
1-220-40%Poor Suitability
2-340-60%Fair Suitability
3-460-80%Good Suitability
4-580-100%Excellent Suitability

Establishment and recruitment for APn80 trees

Legend for Tree establishment values
Index valuesRatingColor
4.0 - 5.0ExcellentGreen
3.0 – 3.99GoodBlue
2.0 – 2.99FairYellow
1.0 – 1.99FairOrange
0.0 – 0.99FairWhite

In general, trees with high understory presence and excellent R-, SE-, and SA-indices can be depended upon to produce enough advance regeneration to stock a stand after removal of canopy trees. In APn80 forests black spruce is almost always present in usable abundance. At maturity black spruce dominates both the understory and overstory, and the forest is self-sustaining.

Trees with excellent R-index values have no problem establishing on an undisturbed forest floor in mature APn80 forests. Black spruce primarily establishes by seed without any site preparation. Tamarack most often needs to establish by seed. Its lower R-index value indicates a germination need that is not fully met in a mature APn80 forest. Silvicultural improvement requires knowledge of tamarack’s silvics and its competitive context following silvicultural treatment. Common germination and early survival hurdles in APn80 forests are: adequate drainage provided by hummock-and-hollow micro-topography, the right species of mosses forming the seedbed, tolerable levels of Ericaceous phenolic compounds, and favorable water chemistry. Other than conserving a site’s micro-topography, little can be done to improve tamarack’s regenerative chances relative to black spruce.
 
Trees with excellent SE- and SA-index need no silvicultural assistance recruiting to tree size in an unmanaged forest. Black spruce does this in APn80 forests. Trees with either a good or fair SE- or SA-index would likely benefit from intermediate silvicultural treatment as long as establishment isn’t a problem. If the SE-index is the lower of the two then early survival and growth is the issue, and treatments like cleaning and spacing may help to diminish proximal competition. Tamarack may fit this pattern, but its R-index is also lower, suggesting that establishment and early growth are both a problem. If the SA-index is the lower of the two then the issue is most likely sufficient light as the trees try to emerge from the shrub layer, and overhead release may help to promote the advance regeneration. No tree fits this pattern as both black spruce and tamarack recruit to heights over 10m without assistance. There are no trees in APn80 forests with a poor or very poor R-, SE-, and SA-index, thus even-aged silvicultural strategies are not necessary, but still might help to slightly favor a tree as intolerant as tamarack.

Natural Disturbance

Understanding natural disturbance regimes is prerequisite for designing silvicultural systems and treatments that emulate natural processes. Theoretically, 'natural' treatments favor trees adapted to the site, conserve local gene pools by relying on natural regeneration, maintain native plants in the understory, are less risky than agricultural approaches, and cheaper to implement. Because clear-cutting and other stand-regenerating systems are so often employed, it is important to determine which NPCs were maintained by stand-replacing disturbances and, further, to estimate the natural rotation.  For many NPCs the natural rotation far exceeds commercial rotation, and this requires us to look to other silvicultural strategies for harvest and regeneration.  Thus, we must also estimate the frequency and intensity of disturbances that maintain these kinds of forest communities.

Natural rotation of catastrophic and maintenance disturbances were calculated from Public Land Survey (PLS) records. The records provide a point-in-time estimate (ca. 1846-1908 AD) of just how much of the historic landscape was recently disturbed by fire, windthrow, or gap-forming events such as surface fires, disease pockets, etc. To some extent these regional trends can be applied to management at the stand-scale. The kind of natural disturbance can inform site preparation; the comparative frequency of stand-replacement and maintenance events informs canopy retention and entry schedules/rotation. 

Learn more about calculating natural disturbance rotations

Natural Disturbance Regimes

The goal of the PLS analysis was to estimate the rotation of stand-replacement and maintenance disturbances unique to each NPC class. The surveyors explicitly described burned and windthrown land when working within the forested regions of Minnesota. When in the prairie region and especially along the prairie/forest border, the surveyors used a variety of terms to describe wooded vegetation understood to be maintained by frequent disturbance. Most often this was fire, but in some regions wind was important as well. Thus, geographic context is an important consideration when trying to determine if a surveyor's comments are indicating that the corner was 1) undisturbed, 2) catastrophically disturbed, or 3) recently affected by a less intense, maintenance disturbance. Placing corners in these three categories is the critical step that allows the calculation of disturbance regimes. To get at this, we must understand the surveyor's physiognomic descriptions of the vegetation at the corners: prairie, grove, bottoms, barrens, burned lands, windthrown timber, etc. Our rules for assessing disturbance at survey corners were individually set for each physiognomic vegetation type across the state

Stocking (i.e., tree density) is the most important element of their physiognomic descriptions. Our initial step in the analysis was to understand how the distances to bearing trees affected the surveyor's vocabulary. For all of the types, we calculated the mean distance to bearing trees which allowed us to rank and group the types in some sensible fashion.

Wooded typesDisturbance typesRiverine typesFire maintained typesOpen types
Swamp 40Windthrow 72Bottomland 135Thicket 92Meadow 183
Forest 50Burned land 76Dry land 157Pine openings 113NOTA 192
Dry ridge 60  Oak openings 145Prairie 236
Grove 69  Scattering oak 166Marsh 278
Island 70  Barrens 177Wet prairie 411

Table 1. Vegetation types mentioned by surveyors and their mean distances in links to their bearing trees. Columns roughly ranked by range of distances. (NOTA means 'no other tree around.')

Wooded and riverine types (Table 1) were assumed to be undisturbed forest. The short distances to trees in the wooded types are indicative of naturally stocked forest where tree density is largely set by competition for space among trees. The riverine types have longer distances than the wooded types because bottomland and dry land corners are intermingled with river channels and marsh at a fine scale. It is common for these linear, treeless features to occupy a full quadrant at a corner in bottomland forest requiring a bearing tree be found across the channel or meadow if possible. For each wooded type, we examined the frequency distribution of corners in 10-link distance classes to get a general sense of distances that would indicate natural stocking. Figure 1 is an example for the forest-type distribution associated with 77,506 corners. 

Figure 1

Figure 1. Frequency of 'forest' survey corners in 10-link distance classes by rounding mean distance (e.g., the 10-link class includes corners with mean distance of 5-15 links).

In Figure 1 about 80% of all corners fall in the first 6 classes (up to 55 links). The mean distance for all forest corners is 50 links. Our interpretation is that somewhere around the mean there is a change in the nature of the distribution. Classes under 50 links are common and likely represent the natural range of variation in stocking (perhaps due to age). Classes over 50 links are infrequent and most likely represent a corner where at least one quadrant lacked nearby trees or had damaged trees due to disturbance.  Thus, for our 'undisturbed' wooded and riverine classes, it just turns out that the mean distance usually falls in the last or one of the last abundant distance classes, and classes with longer distances were assumed to be disturbed to some extent. To make a simple rule, we arbitrarily set the minimum distance indication disturbance to the mean for vegetation that the surveyors described as swamp, forest, dry ridge, grove, island, bottomland, or dry land

Setting the upper limit, above which we assume stand-replacement, was also a guess. It is clear that mean distances over about 180 links are typical of open, treeless environments (Table 1.). Even at distances of about 110-180 links it is clear that trees were scarce enough that the surveyors noted that the vegetation wasn't forest. The distribution in Figure 1 is incredibly smooth over the longer mean-distance classes and there is no gap in classes to suggest a natural break for our higher distance threshold. To make a simple rule, we arbitrarily set the maximum distance indicating stand-replacing disturbance as the mean plus one standard deviation for swamp, forest, dry ridge, grove, island, bottomland, or dry land.  For most classes, this number is close to the mean distances for open types that we know had very few trees.

The frequency distributions of fire-maintained types are different from the wooded and riverine types. At distances greater than the peak class, the fall in frequency is nearly linear, an example of which is for oak openings (Figure 2.). There is no obvious point of inflection to set the lower, naturally-stocked, undisturbed limit, nor are there breaks in the distribution that can help us set the upper limit for catastrophic disturbance. It is important to remember that we are interpreting the use of terms like 'openings' and 'scatterings' to corners that we believe from modern vegetation to be capable of forest stocking. Almost certainly, these terms were used to describe recent disturbance that caused trees to be sparser than normal “forest.” To help us interpret the use of these terms to describe forest, we returned to the coarser analysis. Corners with distances under 50 links were almost certainly in places one would describe as undisturbed forest. Corners with distances over 200 links were in places where tree density was low and comparable to open habitats like prairie and meadow. To make a simple rule for corners described as thicket, pine openings, oak openings, scattering timber, and barrens, we arbitrarily set the minimum distance indicating disturbance to 50 links, and we set the maximum distance indicating stand-replacing disturbance at 200 links.

Figure 2

Figure 2. Frequency of 'oak opening' survey corners in 10-link distance classes by rounding mean distance (e.g., the 10-link class includes corners with mean distance of 5-15 links).

In addition to distance, we found it important to consider also missing bearing trees as evidence of disturbance. A common survey note is 'NOTA' meaning 'no other tree around,' which was the surveyor's explanation for not marking all of the required bearing trees (i.e., 4 at section corners and 2 at quarter-section corners). Most often this note appeared at corners described as one of the fire-maintained or open community groups (Table 1.). NOTA was also used at corners described as burned or windthrown. Within the context of interpreting corners modeled as forest or woodland, NOTA almost certainly was relating to some kind of disturbance that left dead trees or trees too small to scribe. Table 2 describes our model for assigning a disturbance class based on both distance and complement of bearing trees. Within their type, survey corners were assigned their final disturbance class -- undisturbed, partially disturbed, catastrophically disturbed -- by a combination of the corner's mean distance to its bearing trees and whether it had its full complement of 2 or 4 bearing trees.

Assumed undisturbed - Wooded and Riverine groups< meanbetween mean and mean + SD>Mean + SD
Full complementUndisturbedUndisturbedMaintenance
Partial complementUndisturbedMaintenanceBurned
Assumed disturbed - Fire-maintained group< 50 linkslinks> 206 links
Full complementUndisturbedMaintenanceBurned
Partial complementMaintenanceMaintenanceBurned

Table 2. Rules for assigning a disturbance class to survey corners not explicitly described as burned or windthrown.

Adjusting the Model -- Window of Recognition
It is obvious that several pragmatic decisions and rules were made in order to assign corners to disturbance categories. Even if these rules are reasonable, one must still set a 'window of recognition' in order to make quantitative estimates of stand-replacing and maintenance rotations. The window of recognition is the span of years for which a surveyor would have bothered to describe a disturbance. Would a surveyor recognize and care to report that a stand had been burned 5, 10, 15, or 20 years after the fact? We believe that mention of fire and windthrow was more an excuse for not marking bearing trees than any conscientious effort to alert potential buyers to fire- or wind-damaged timber. Consider the fact that quaking aspen is the early successional species for nearly all terrestrial forests in Minnesota. The surveyors actually marked and scribed some 390, 2-inch aspen bearing trees and some 3,039 three-inch trees. Clearly, surveyors would bother to scribe 2-3' trees if that was their only choice. Our age/diameter models for 2-3' aspen trees suggest that these trees were between 11 and 18 years old respectively. If commenting about fire and wind was an excuse, then the window of recognition should be somewhere in the 11-18 year range because that is when trees reach a minimum diameter for marking. 

Alternatively, a window of recognition is empirically set to 'force' the rotation model to match the estimates from studies using more reliable methods. In the Great Lakes States, there are reconstructions of disturbance regimes from fire-scar studies (Frissell 1973), stand-origin mapping (Heinselman 1996), and charcoal analysis of varved sediments (Clark 1988). When we model disturbance regimes from bearing trees in these same regions, a window of 15 years tends to yield results similar to the other methods for stand-replacing disturbance. We used a 15-year window of recognition because it yields rotations comparable to rotations calculated from fire-scars, stand-origin maps, and varved lake sediments.

Many detailed investigations of forest disturbance do not calculate rotations of maintenance disturbance, but recognize its confounding effect on estimating stand-replacing events. Trees with multiple fire-scars attest that some forest types are affected more by maintenance surface fire than catastrophic crown fires. Dendrochronological reconstructions of stand history also attest that maintenance events (fire and non-fire) are common and important, releasing cohorts of advance regeneration and providing some growing space in the canopy (e.g. Bergeron et al. 2002).  Minor peaks in varve charcoal are also more common than major ones, possibly recording maintenance fires. Calculating maintenance disturbance is more complicated than stand-replacement because the signal is weaker, reliable studies are fewer, and the cause less obvious. However, some estimate is absolutely required to provide guidance in applying intermediate silvicultural treatments to the right NPCs.

As was the case for estimating stand-replacing rotations, adjusting the window of recognition is the easiest way to adjust the model. Logic would suggest that the window should be shorter for maintenance events because the disturbance is less intense and evidence of it might be gone in 15 years. If the surveyors really used terms like burned or windthrown to explain the lack of bearing trees, it is likely that they did so less often on lands lightly disturbed because there were trees around -- they just had to go a little farther to find bearing trees and might not always find a suitable tree in all quadrants. We found that a 5-year window produced rotations that matched what one might guess from multiple-scarred trees. Also, the ratio of maintenance events to catastrophic ones seemed within the range of what one might expect from the ratio of strong charcoal peaks to minor ones in varve studies. A 5-year recognition window was used to calculate maintenance rotations because it seems to fit fire-scar and varve studies.

Calculating Rotation by Example -- Northern Mesic Mixed Forest (FDn43)
Having settled on windows of recognition and having assigned disturbance classes to the corners associated with an NPC, it is possible to calculate rotation. This is easiest to understand by example.

Northern Mesic Mixed Forest (FDn43) is a fire-dependant NPC that is the matrix vegetation for much of northeastern Minnesota. Our model assigned 11,712 PLS survey corners to this community because 1) they fall on landforms (LTAs) where we have modern samples of FDn43 forests, 2) the attending bearing trees were typical of the community (>70% frequency), and 3) they lacked trees atypical of the community (<30% frequency). 

Each corner was assigned one of 4 disturbance classes based upon the distance and complement rules set up for each physiognomic vegetation class (Table 2.). The tallies for each class are shown in Table 3. 

Vegetation ClassFire 15-year windowWind 15-year windowMaintenance 5-year windowUndisturbed
Barrens  1111
Dry ridge  129
Forest42 11110168
Grove   1
Bottoms   45
Scattering pine  716
Scattering timber2 2460
Swamp (misassigned)  5153
Thicket21 61143
Burned710   
Ravine   6
Windthrown 63  
No other tree around16   
Island  15
Totals7916322110637

Table 3. Counts of survey corner assignment to disturbance classes by physiognomic vegetation class for the FDn43 community.

The FDn43 landscape of 11,712 survey corners provides the base area for calculating rotation of a NPC. In Table 3, 791 of those corners were interpreted as having been catastrophically burned, representing 6.75% of the area.
(791 burned corners/11,712 total corners)*100=6.75% of the landscape

Presumably, surveyors recognized burned lands for 15 years after the event, meaning that the annual percent of the landscape that catastrophically burned is 1/15th of 6.75%.
6.75% of landscape burned/15-year recognition window=0.45% burned annually

The rotation is the time required to catastrophically burn the entire area represented by 11,712 corners. Because we have calculated this as a percent, the time it takes to achieve that is: 
100%/0.45% burning annually=222 year rotation of catastrophic fire

There is no need to calculate acres or percent of landscape, but it makes the calculation easier to understand given the area concept of rotation in forestry. The easier formulas to use are:
(Total # corners / # corners in disturbance category)*recognition window=rotation
(11,712/791burned)*15 years=222 year rotation of catastrophic fire
(11,712/63 windthrown)*15 years=2,788 year rotation of catastrophic windthrow
(11,712/221 maintenance)*5 years=265 year rotation of maintenance disturbance

It is also useful to calculate the rotation of all fire (or wind), regardless if it was catastrophic or maintenance. To make this calculation it is easiest to sum the annual percents. 
0.45% burned catastrophically each year
0.37% burned in maintenance event
0.45%+0.37%=0.82% annual=122 year rotation for all types of fires

It is the rotation of all fires that tends to reasonably match the published estimates of return intervals. For example, in the BWCAW Heinselman (1996) reports return intervals for the common forest types: Aspen-Birch-Conifer (70-110 years), Red Pine (<100), and White Pine (>100). These cover types, especially the white pine, are predominantly the FDn43 community for which we calculate a 122 year rotation for all fires.


The table below shows the frequency of PLS survey corners assigned to four different disturbance categories. Shown also is the percent of the APn80 landscape in those conditions and the resulting calculated rotation. Maintenance disturbances were the most frequent disturbance type in this landscape; fire was very rare in this landscape. 

Natural disturbance rotations for APn80 landscapes

Stand Dynamics & Growth Stages

Understanding natural stand dynamics is the essence of prescription writing. Without some understanding of how dynamics affect tree establishment, thinning, recruitment, competitive ability, form, longevity, and succession during 'unsupervised' stand maturation -- foresters cannot write worthwhile prescriptions. For the most part, prescriptions are written to alter, accelerate, or allow the natural course of events in a forest in order to meet a management objective. 

Public land survey records were used to develop a natural model of compositional succession and structural change. The figure below orders PLS section and quarter-sections by diameter class, assigned as the diameter of the largest attending bearing tree at the corner. Presumably this is chronological ranking along the y-axis. The rough age of each diameter class was estimated by FIA diameter/age models for a tree common in all diameter classes. 

For every tree, its relative abundance in a diameter class is graphed along the x-axis. This shows the compositional change as forests mature from small diameter classes to larger ones. The inter-tree distances provide some insight concerning initial tree density and how that changes as forests age. Low standard deviation of the inter-tree distances indicate uniform tree spacing; high standard deviations indicate a patchy distribution of trees. A cluster analysis (CONISS) groups contiguous diameter classes into periods of stability (growth-stages) and change (transitions).

Learn more about natural dynamics and growth stages

Stand Dynamics

PLS data are not inherently temporal. To create a model of stand dynamics we must somehow rank survey corners assigned to a particular NPC Class in a way that is reflective of time.  The best that can be done is to assign each corner to a diameter-class equal to the diameter of the largest bearing tree at that corner. This allows us to reasonably rank corners from smaller-diameter/presumably younger forests to larger/presumably older forests the first 100 years or so. We refer to the diameter of the largest tree at a corner as 'stand-diameter.' We believe that this ranking is good enough to make some broad interpretations about dynamics throughout the early years of stand maturation. The modeled age of the largest tree at a corner is a minimum estimate of how long the stand has avoided a catastrophic disturbance. This is NOT true stand age because no corner can be assigned a diameter/age beyond the biological size or longevity of its old-growth species. For forest classes with long rotations of stand-replacing disturbance, the largest tree at any point can easily belong to the 2nd, 3rd, or subsequent cohort. Survey corners were assigned to 'stand-diameter' classes equal to the diameter of the largest witness tree at that corner.

For the set of corners in a diameter class we calculated the relative abundance of each bearing tree taxon. This allows us to see how composition changes as stand-diameter increases over time. For each tree taxon, we plotted its relative abundance by stand diameter to see if its relative abundance tends to decrease, increase, or peak over the range of stand-diameters (below). Also, for the set of corners in a diameter class we calculated the mean distance of trees to the corner and the standard deviation of that mean. This allows us to understand how tree density and variance in density changes as stand diameter increases over time. Because these dynamic models are useful for forest planning the estimated age of a tree that diameter is provided. This is done for a tree species that is abundant and present in all stand-diameter classes. The model is based upon diameter and age measurements of FIA site trees. Stand diameter age was estimated by using a quadratic equation that was fit to FIA site-index trees.

Age=C+A*dbh+B*dbh2 (where C is a constant, A&B are coefficients from the FIA model)

A constrained clustering routine (CONISS, constrained incremental sum of squares) was applied to the stand-diameter classes as characterized by the relative abundance of trees in that class. This method is constrained in that stand-diameter classes must be grouped to its adjoining classes or clusters that include the adjoining classes. The result is a hierarchical grouping of contiguous diameter classes based upon the similarity of their tree composition (below). Tight groups represent a span of stand-diameters where we infer little compositional change. We call these 'growth-stages.' Separating growth-stages are clusters of contiguous diameter classes that are not necessarily very similar, but are the last to be clustered. Such spans of diameter classes represent periods of species turnover called 'transitions.' This analysis provides some insight into the timing and rate of dynamic change.


Graphed for each of the common APn80 trees is their relative abundance (percent composition; x-axis) as PLS bearing trees by diameter class. Also shown is the mean distance of trees to the survey corner (inter-tree distance, white inset bars) and the standard deviation about that mean (black bars) for each diameter class. All data were smoothed using a 5-sample running average. A constrained cluster analysis (CONISS) groups diameter classes with similar species composition; the groups are interpreted as either stable growth-stages (e.g. young, mature) or periods of change (transition). Data for APn80 comprise 4,587 PLS corners and 13,951 witness trees.

Natural dynamics model for APn80

Natural dynamics model for APn80

Compositional Succession
APn80 forests were among several non-successional peatland communities where a particular hydrologic regime and water chemistry resulted in dominance by a single species. In this case, the actively growing substrate of Sphagnum peat had risen above the influence of minerotrophic groundwater, and the permanently saturated soils were maintained by precipitation. Also, the Sphagna capable of growth above minerotrophic groundwater are tolerant of very low nutrient input and they actively exchange H+ ions to sequester nutrient cations, leaving the water extremely acid. These hydrologically stable and acidic conditions greatly favored black spruce, some tamarack, and a very limited set of vascular plants. There was little in the way of compositional succession, and black spruce dominated all of the growth stages. Young forests were dominated by black spruce and considerably less tamarack, and together they made up the initial cohort. Over the period when stand diameter increased from 5-14 inches, tamarack increased slightly relative to black spruce. By the time stand diameter reached 15 inches and the forest was about 175 years old, most canopy trees belonged to the second cohort and composition stabilized. Stands were still dominated by black spruce but were enriched with more tamarack than when young. It is likely that this apparent compositional change is an artifact of our method of assigning PLS corners to a diameter class based upon the largest tree at the corner. For an unknown reason, tamarack radial growth in bogs is faster than that of black spruce, and tamarack’s range of diameters is broader, extending further into the large diameter classes. When stand diameter was 6 inches and the stand roughly 70 years old, the frequency of tamarack as the largest tree at a corner began to increase relative to black spruce. For stand diameters greater than 11 inches, tamarack was more often the largest tree in spite of the fact that there were more black spruce trees in the stand. 

Structural Succession
APn80 forests were typical of peatland communities that were very rarely affected by catastrophic disturbances and not commonly influenced by maintenance disturbance. They were maintained by fine-scale disturbances that had little effect on tree density and a limited effect as to how regularly trees were spaced—regardless of stand diameter or age. By the time stand diameter reached 4-5 inches any self-thinning was essentially complete and young forests had trees just 22 feet apart, which was typical of all peatland forests. This spacing essentially remained constant throughout the process of stand maturation. If anything, tree density increased slightly, likely due to layering of initial-cohort trees.

APn80 forests also showed very little variance in tree spacing as stands aged. Young forests had evenly spaced trees, ratios of standard deviation to mean inter-tree distances was about 1.1 at that time. Over the period when stand diameter increased from 6-14 inches this ratio held constant ranging between 0.9 and 1.2. Only when very old did this change, and trees in very old APn80 stands were very uniformly spaced. Beginning when stand diameter reached 15 inches, the ratios of standard deviations to mean inter-tree distances dropped to about 0.6. Northern acidic peatland bogs were the densest and most evenly spaced forests in Minnesota at maturity.

Sivicultural Strategies

Silvicultural strategies are sequences of treatment outcomes designed to emulate natural stand dynamics and promote natural regeneration. They are not silvicultural systems in the traditional sense because they do not cover a full rotation or have attached the implied goal of maintaining a particular species or cover-type indefinitely. Most involve 1-2 stand entries over a short period of time that will move a stand towards a forest plan objective -- with enough inertia that little silvicultural intervention will be needed to meet long-term goals.  We describe management outcomes rather than silvicultural treatments because there are usually several treatments that might achieve the desired outcome. All strategies are based upon our understanding of NPC-specific natural stand dynamics and disturbance regimes. The sequence of outcomes follows the natural pattern; the timing is foreshortened because we intend to harvest sound trees rather than allowing natural senescence.


The most common, natural pattern of tree mortality and replacement was the partial loss of trees on a rotation of about 120 years. Stand-replacing fire was not important with an estimated rotation of 2,400 years. Stand-replacing windthrow was more common with an estimated rotation of 690 years. 

Although fire is offered as a management strategy for regenerating black spruce, there is little evidence in either the PLS survey notes or in examinations of peat cores that these forests burned with any regularity. Anthropogenic fires occurred during the period of settlement that included the ditching of bogs, and some of these surface fires resulted in black spruce regeneration. Other fires burned deeply into the peat, usually flattening the raised bog-features and leaving the new growing surface within rooting range of minerotrophic groundwater. The consequence of such catastrophic burning was often the formation of treeless peatland communities that required centuries of recovery before peat growth could provide the drainage necessary for trees. Thus emulating fire as a regeneration method and applying prescribed burning comes with considerable risk. Also, prescribed fires cannot sustainably remove more peat than what will grow back within a rotation or entry period. However, prescribed burning can have a sanitizing effect regarding dwarf mistletoe and phenolic allelopathy of Ericaceous shrubs. For that reason, one strategy is envisioned:

  • Re-initiate a stand as would light surface fire to create open to very large gap habitat primarily for sanitation reasons. 

Although APn80 forests show virtually no compositional or structural succession, they displayed a broad range of stand diameters. Stands of trees died and were replaced—apparently by their own progeny and at similar density. The most likely cause of mortality in our peatland forests was widespread climate-induced stress, followed secondarily by defoliating insects or disease. Drought, periods of overwhelming rainfall, compromised drainage, and snow-load all stressed peatland trees over broad areas.  Because most peatland forests are monotypic, infestations of species-specific pests can spread across peatlands as moving wave fronts or expanding gaps of pocket diseases—at least until the stressed trees regained vigor. Two strategies are envisioned: 

  • Re-initiate a stand as would stand-replacing disease/pest wave events to create open to very large gap habitat.
  • Maintain a stand as would natural senescence, selective windthrow, or disease/pest expanding gap events to create small-gap habitat.

Modern APn80 forests are still greatly affected by widespread climate-induced stress followed by secondary attack from insects and disease. The warmer and shorter winters associated with climate change are likely to increase both the frequency and magnitude of climatic stress in these forests. The historic response of this community to disturbance is now complicated by altered drainage due to widespread ditching of peatlands between 1910 and 1930, highway roadbeds that alter lateral groundwater flow, and invasive forest pests that affect tamarack more so than black spruce.  Commercial logging coupled with these complications has resulted in APn80 forests with far less tamarack and more black spruce than was documented by PLS surveyors in the late 1800s. The greatest risk associated with commercial logging is swamping, which has occasionally resulted in conversion to treeless wetland communities. Unfortunately, this hydrologic risk is not usually evident at the stand scale. 

 

Silvicultural Strategy for re-initiating APn80 forests as would light surface fire
Emulating light surface fire to favor black spruce

Re-initiation Concept
Rarely prolonged drought dried the peat surface of APn80 forests to the point where creeping surface fires could slowly consume the surface layer of peat down to the water table and kill enough black spruce and tamarack to create open habitat. Such fires 1) favored seeding-in by black spruce because of its semi-serotinous cones, 2) initiated a post-fire succession of mosses and liverworts that provided a favorable seedbed for either black spruce or tamarack, and 3) reduced or eliminated any accumulation of phenolic compounds produced by Labrador tea, which deters germination of black spruce seeds more so than tamarack seeds. 

 

Silvicultural Strategy for re-initiating APn80 forests as would stand-replacing disease/pest wave events
Emulating stand-replacing outbreaks of defoliating insects or disease to favor black spruce 

Re-initiation Concept
The broad expanses and monotypic nature of APn80 forests left them vulnerable to widespread mortality caused primarily by defoliating insects. Such outbreaks could go on for years creating a wave-front of dying trees that would go unchecked until the insect populations were diminished by a lack of food, equally impressive outbreaks of their predators, or fortuitous climatic circumstances. Throughout recorded history, these outbreaks have affected tamarack far more so than black spruce. Such events 1) released advance regeneration of black spruce and any surviving tamarack, and 2) encouraged the expansion of Labrador tea and leatherleaf populations, which considerably delayed and diminished black spruce recovery by seed. 

 

Silvicultural Strategy for maintaining APn80 forests as would natural senescence, selective windthrow, or disease/pest expanding gap events
Emulating expanding gap events to favor tamarack

Expanding-gap Concept
Windthrow, pocket diseases, and dwarf mistletoe created gaps in the APn80 canopy that due to greater wind purchase and the nature of the pocket diseases/mistletoe tended to expand over time. Such events generally 1) released advance regeneration of tamarack and black spruce, 2) provided enough light for some tamarack regeneration, and 3) encouraged the expansion of Labrador tea and leatherleaf populations, which considerably delayed and diminished black spruce recovery by seed.