Impact of scale on morphological spatial pattern of forest

Assessing and monitoring landscape pattern structure from multi-scale land-cover maps can utilize morphological spatial pattern analysis (MSPA), only if various influences of scale are known and taken into account. This paper lays part of the foundation for applying MSPA analysis in landscape monitoring by quantifying scale effects on six classes of spatial patterns called: core, edge, perforation, branch, connector and islet. Four forest maps were selected with different forest composition and configuration. The sensitivity of MSPA to scale was studied by comparing frequencies of pattern classes in total forest area for various combinations of pixel size (P) and size parameter (S). It was found that the quantification of forest pattern with MSPA is sensitive to scale. Differences in initial composition and configuration influence the amount but not the general tendencies of the variations of morphological spatial pattern (MSP) class proportions with scale. Increase of P led to data generalization resulting in either a removal of the small size features or their potential transformation into other non-core MSP classes, while an increase of S decreases the MSP core area and this process may transform small core areas into the MSP class islet. We established that the behavior of the MSPA classes with changing scale can be categorized as consistent and robust scaling relations in the forms of linear, power, or logarithmic functions over a range of scales.     

Landscape patterns from mathematical morphology on maps with contagion

The perceived realism of simulated maps with contagion (spatial autocorrelation) has led to their use for comparing landscape pattern metrics and as habitat maps for modeling organism movement across landscapes. The objective of this study was to conduct a neutral model analysis of pattern metrics defined by morphological spatial pattern analysis (MSPA) on maps with contagion, with comparisons to phase transitions (abrupt changes) of patterns on simple random maps. Using MSPA, each focal class pixel on a neutral map was assigned to one of six pattern classes—core, edge, perforated, connector, branch, or islet—depending on MSPA rules for connectivity and edge width. As the density of the focal class (P) was increased on simple random maps, the proportions of pixels in different pattern classes exhibited two types of phase transitions at threshold densities (0.41 ≤ P ≤ 0.99) that were predicted by percolation theory after taking into account the MSPA rules for connectivity and edge width. While there was no evidence of phase transitions on maps with contagion, the general trends of pattern metrics in relation to P were similar to simple random maps. Using an index P for comparisons, the effect of increasing contagion was opposite that of increasing edge width.     

Mapping Spatial Patterns with Morphological Image Processing

We use morphological image processing for classifying spatial patterns at the pixel level on binary land-cover maps. Land-cover pattern is classified as ‘perforated,’ ‘edge,’ ‘patch,’ and ‘core’ with higher spatial precision and thematic accuracy compared to a previous approach based on image convolution, while retaining the capability to label these features at the pixel level for any scale of observation. The implementation of morphological image processing is explained and then demonstrated, with comparisons to results from image convolution, for a forest map of the Val Grande National Park in North Italy.     

Divergent rates of change between tree cover types in a tropical pastoral region

Context

Forest cover change analyses have revealed net forest gain in many tropical regions. While most analyses have focused solely on forest cover, trees outside forests are vital components of landscape integrity. Quantifying regional-scale patterns of tree cover change, including non-forest trees, could benefit forest and landscape restoration (FLR) efforts.

Objectives

We analyzed tree cover change in Southwestern Panama to quantify: (1) patterns of change from 1998 to 2014, (2) differences in rates of change between forest and non-forest classes, and (3) the relative importance of social-ecological predictors of tree cover change between classes.

Methods

We digitized tree cover classes, including dispersed trees, live fences, riparian forest, and forest, in very high resolution images from 1998 to 2014. We then applied hurdle models to relate social-ecological predictors to the probability and amount of tree cover gain.

Results

All tree cover classes increased in extent, but gains were highly variable between classes. Non-forest tree cover accounted for 21% of tree cover gains, while riparian trees constituted 31% of forest cover gains. Drivers of tree cover change varied widely between classes, with opposite impacts of some social-ecological predictors on non-forest and forest cover.

Conclusions

We demonstrate that key drivers of forest cover change, including topography, road distance and historical forest cover, do not explain rates of non-forest tree cover change. Consequently, predictions from medium-resolution forest cover change analyses may not apply to finer-scale patterns of tree cover. We highlight the opportunity for FLR projects to target tree cover classes adapted to local social and ecological conditions.

     

Socioeconomics drive woody invasive plant richness in New England, USA through forest fragmentation

Woody invasive plants are an increasing component of the New England flora. Their success and geographic spread are mediated in part by landscape characteristics. We tested whether woody invasive plant richness was higher in landscapes with many forest edges relative to other forest types and explained land use/land cover and forest fragmentation patterns using socioeconomic and physical variables. Our models demonstrated that woody invasive plant richness was higher in landscapes with more edge forest relative to patch, perforated, and especially core forest types. Using spatially-explicit, hierarchical Bayesian, compositional data models we showed that infrastructure and physical factors, including road length and elevation range, and time-lagged socioeconomic factors, primarily population, help to explain development and forest fragmentation patterns. Our social–ecological approach identified landscape patterns driven by human development and linked them to increased woody plant invasions. Identifying these landscape patterns will aid ongoing efforts to use current distribution patterns to better predict where invasive species may occur in unsampled regions under current and future conditions.     

Impact of error on landscape pattern analyses performed on land-cover change maps

Researchers have emphasized the value of linking observed patterns of land-cover change to the processes driving changes in land-use to explain the dynamics of a land change system. The association of pattern and process requires an accurate quantification of the spatial characteristics of land-cover change. The objective of this research is to assess the impact of error on the accuracy of landscape pattern analyses performed on maps of change. Simulation was used to develop of a series of error-free and error-perturbed change maps, which varied with respect to the pattern of change occurring between the time-1 and time-2 land-cover maps and the patterns of error associated with the time-1 and time-2 land-cover maps. A variety of change and error patterns were examined. The error-free and error-perturbed change maps were compared by calculating landscape pattern metrics, which revealed the degree to which error altered the pattern of change. The introduction of error notably changed the structure of the persistent and transitioning classes, with metrics indicating a more fragmented and variable landscape under error. Agreement between the error-free and error-perturbed maps improved when a greater amount of change occurred within the time-series, change was concentrated at the boundaries of land-cover classes and when time-2 errors were increasingly correlated to their time-1 counterparts. These results have several implications for change pattern analyses given the fundamental nature of land-cover change.     

Temporal change in fragmentation of continental US forests

Changes in forest ecosystem function and condition arise from changes in forest fragmentation. Previous studies estimated forest fragmentation for the continental United States (US). In this study, new temporal land-cover data from the National Land Cover Database (NLCD) were used to estimate changes in forest fragmentation at multiple scales for the continental US. Early and late dates for the land-cover change data were ca. 1992 and ca. 2001. Forest density was used as a multi-scale index of fragmentation by measuring the proportion of forest in neighborhoods ranging in size from 2.25 to 5314.41 ha. The multi-scale forest density maps were classified using thresholds of 40% (patch), 60% (dominant), and 90% (interior) to analyze temporal change of fragmentation. The loss of dominant and interior forest showed distinct scale effects, whereas loss of patch forest was much less scale-dependent. Dominant forest loss doubled from the smallest to the largest spatial scale, while interior forest loss increased by approximately 80% from the smallest to the second largest spatial scale, then decreased somewhat. At the largest spatial scale, losses of dominant and interior forest were 5 and 10%, respectively, of their ca. 1992 amounts. In contrast, patch forest loss increased by only 25% from the smallest to largest spatial scale. These results indicate that continental US forests were sensitive to forest loss because of their already fragmented state. Forest loss would have had to occur in an unlikely spatial pattern in order to avoid the proportionately greater impact on dominant and interior forest at larger spatial scales.     

Modeling grain-size dependent bias in estimating forest area: a regional application

A better understanding of scaling-up effects on estimating important landscape characteristics (e.g. forest percentage) is critical for improving ecological applications over large areas. This study illustrated effects of changing grain sizes on regional forest estimates in Minnesota, Wisconsin, and Michigan of the USA using 30-m land-cover maps (1992 and 2001) produced by the National Land Cover Datasets. The maps were aggregated to two broad cover types (forest vs. non-forest) and scaled up to 1-km and 10-km resolutions. Empirical models were established from county-level observations using regression analysis to estimate scaling effects on area estimation. Forest percentages observed at 30-m and 1-km land-cover maps were highly correlated. This intrinsic relationship was tested spatially, temporally, and was shown to be invariant. Our models provide a practical way to calibrate forest percentages observed from coarse-resolution land-cover data. The models predicted mean scaling effects of 7.0 and 12.0% (in absolute value with standard deviations of 2.2 and 5.3%) on regional forest cover estimation (ranging from 2.3 and 2.5% to 11.1 and 23.7% at the county level) with standard errors of model estimation 3.1 and 7.1% between 30 m and 1 km, and 30 m and 10 km, respectively, within a 95% confidence interval. Our models improved accuracy of forest cover estimates (in terms of percent) by 63% (at 1-km resolution) and 57% (at 10-km resolution) at the county level relative to those without model adjustment and by 87 and 84% at the regional level in 2001. The model improved 1992 and 2001 regional forest estimation in terms of area for 1-km maps by 15,141 and 7,412 km² (after area weighting of all counties) respectively, compared to the corresponding estimates without calibration using 30 m-based regional forest areas as reference.     

The influence of patch-delineation mismatches on multi-temporal landscape pattern analysis

Investigations of land-cover change often employ metrics designed to quantify changes in landscape structure through time, using analyses of land cover maps derived from the classification of remote sensing images from two or more time periods. Unfortunately, the validity of these landscape pattern analyses (LPA) can be compromised by the presence of spurious change, i.e., differences between map products caused by classification error rather than real changes on the ground. To reduce this problem, multi-temporal time series of land-cover maps can be constructed by updating (projecting forward in time) and backdating (projecting backward in time) an existing reference map, wherein regions of change are delineated through bi-temporal change analysis and overlaid onto the reference map. However, this procedure itself creates challenges, because sliver patches can occur in cases where the boundaries of the change regions do not exactly match the land-cover patches in the reference map. In this paper, we describe how sliver patches can inadvertently be created through the backdating and updating of land-cover maps, and document their impact on the magnitude and trajectory of four popular landscape metrics: number of patches (NP), edge density (ED), mean patch size (MPS), and mean shape index (MSI). In our findings, sliver patches led to significant distortions in both the value and temporal behaviour of metrics. In backdated maps, these distortions caused metric trajectories to appear more conservative, suggesting lower rates of change for ED and inverse trajectories for NP, MPS and MSI. In updated maps, slivers caused metric trajectories to appear more extreme and exaggerated, suggesting higher rates of change for all four metrics. Our research underscores the need to eliminate sliver patches from any study dealing with multi-temporal LPA.     

Regional land-cover conversion in the U.S. upper Midwest: magnitude of change and limited recovery (1850–1935–1993)

Land-use legacies can persist for hundreds to thousands of years, influencing plant species composition, nutrient cycling, water flows, and climate. To understand how land use has affected regional land-cover composition in Wisconsin (USA), we assessed the magnitude and direction of change in land cover between: (1) c.1850, at the onset of Euro-American settlement; (2) c.1935, the period of maximum clearing for agriculture following widespread forest logging; and (3) 1993, which, especially in northern Wisconsin, follows farm abandonment and forest recovery. We derived land-cover maps using U.S. Public Land Survey records (c.1850), the Wisconsin Land Economic Inventory (c.1935), and Landsat TM satellite data (1993). We stratified Wisconsin (145,000 km²) into two ecological provinces and used spatial error models, multinomial logistic regression, and non-metric multi-dimensional scaling ordination to examine change. Between 1850 and 1935, forest cover in the North declined from 84% to 56%, cropland increased to 24%, and mixed/coniferous forests and savannas were replaced by deciduous forests. In the South, formerly dominant savannas (69%) and prairies (6%) were mostly converted to cropland (51%) and pasture (11%). Remnant deciduous savannas and coniferous forests and savannas were replaced by deciduous forests. Remarkably little recovery to pre-settlement land-cover classes occurred from 1935 to 1993. Less cropland was abandoned than expected, and there was little net gain in coniferous/mixed forest. Based on these general land-cover classes, current cover is significantly different from that in 1850, but not from that in 1935, and thus continues to reflect historical logging and agricultural patterns. These results provide a historical framework for measuring associated changes in ecosystem function and can be used to guide restoration where desirable and feasible.     

Forest conservation and land development in Puerto Rico

In the Caribbean island of Puerto Rico, rapid land-use changes over the past century have included recent land-cover conversion to urban/built-up lands. Observations of this land development adjacent to reserves or replacing dense forest call into question how the changes relate to forests or reserved lands. Using existing maps, this study first summarizes island-wide land-cover change between 1977-78 and 1991-92. Then, using binomial logit modeling, it seeks evidence that simple forest cover attributes, reserve locations, or existing land cover influence land development locations. Finally, this study quantifies land development, reserve protection and forest cover by ecological zone. Results indicate that 1) pasture is more likely to undergo land development than shrubland plus forest with low canopy density, 2) forest condition and conservation status appear unimportant in that development locations neither distinguish between classes of forest canopy development nor relate to forest patch size or reserve proximity, and 3) most land development occurs in the least-protected ecological zones. Outside the boundaries of strictly protected forest and other reserves, accessibility, proximity to existing urban areas, and perhaps desirable natural settings, serve to increase land development. Over the coming century, opportunities to address ecological zone gaps in the islands forest reserve system could be lost more rapidly in lowland ecological zones, which are relatively unprotected.This revised version was published online in May 2005 with corrections to the Cover Date.     

Alternative stable states and the role of fire–vegetation–soil feedbacks in the temperate wilderness of southwest Tasmania

Two ecological models have been put forward to explain the dynamics of fire-promoting and fire-sensitive vegetation in southwest Tasmania: the alternative stable states model of Jackson (in Proc Ecol Soc Aust 3:9–16, 1968) and the sharpening switch model of Mount (in Search 10:180–186, 1979). Assessing the efficacy of these models requires high resolution spatio-temporal data on whether vegetation patterns are stable or dynamic across landscapes. We analysed ortho-rectified sequences of aerial photography and satellite imagery from 1948, 1988 and 2010 to detect decadal scale changes in forest and non-forest vegetation cover in southwest Tasmania. There was negligible change from forest to non-forest (<0.05%) and only a modest change from non-forest to forest over the study period. Forest cover increased by 4.1% between 1948 and 1988, apparently due to the recovery of forest vegetation following stand-replacing fire prior to 1948. Forest cover increased by 0.8% between 1988 and 2010, reflecting the limited ability of forest to invade treeless areas. The two models include interactions between vegetation, fire and soil, which we investigated by analysing the chemical (phosphorus, nitrogen) and physical properties (clay, silt) of 128 soil samples collected across 34 forest–non-forest boundaries. Phosphorus in the upper horizon was typically lower in non-forest vegetation compared to forest vegetation, which is consistent with proposed fire–vegetation–soil feedbacks. Mineral horizons were dominated by sand, with low levels of clay under all vegetation types. Available field evidence lends support to the Jackson (1968) alternative stable states model as the most suitable model of vegetation dynamics on nutrient poor substrates in southwest Tasmania although modifications of the timeframes for transitions toward rainforest are required.     

Living on the edge: quantifying the structure of a fragmented forest landscape in England

Forest ecosystems have been widely fragmented by human land use, inducing significant microclimatic and biological changes at the forest edge. If we are to rigorously assess the ecological impacts of habitat fragmentation, there is a need to effectively quantify the amount of edge habitat within a landscape, and to allow this to be modelled for individual species and processes. Edge effect may extend only a few metres or as far as several kilometres, depending on the species or process in question. Therefore, rather than attempting to quantify the amount of edge habitat by using a fixed, case-specific distance to distinguish between edge and core, the area of habitat within continuously-varying distances from the forest edge is of greater utility. We quantified the degree of fragmentation of forests in England, where forests cover 10 % of the land area. We calculated the distance from within the forest patches to the nearest edge (forest vs. non-forest) and other landscape indices, such as mean patch size, edge density and distance to the nearest neighbour. Of the total forest area, 37 % was within 30 m and 74 % within 100 m of the nearest edge. This highlights that, in fragmented landscapes, the habitats close to the edge form a considerable proportion of the total habitat area. We then show how these edge estimates can be combined with ecological response functions, to allow us to generate biologically meaningful estimates of the impacts of fragmentation at a landscape scale.     

Temporal and spatial changes in an area of the New Jersey Pine Barrens landscape

In order to document the extent of landscape fragmentation for a section of the New Jersey Pine Barrens region, we have used satellite image and spatial analysis to monitor landscape change between 1972 and 1988. Land-cover patterns were quantified by mean, number, and size of patches; and amount of edges between land cover types. During the intervening sixteen year period, fractal dimension, diversity, and contagion generally decreased while dominance, disturbance and edges increased, indicating a trend to a more dissected and disturbed landscape. There was an increase in the number of forest patches and a significant decrease in the average size of forest patches. In contrast, the mean patch size for the non-forest category has increased as a result of a coalescence of patches. The landscape fragmentation is shown by a downward shift in the distribution of forest patches by size class. These changes in landscape pattern have implications for many ecological processes and resources. Management practices need to consider landscape fragmentation in the Pinelands National Reserve in order to preserve the essential character of the Pine Barrens landscape.     

Watershed analysis of forest fragmentation by clearcuts and roads in a Wyoming forest

Remotely sensed data and a Geographic Information System were used to compare the effects of clearcutting and road-building on the landscape pattern of the Bighorn National Forest, in north-central Wyoming. Landscape patterns were quantified for each of 12 watersheds on a series of four maps that differed only in the degree of clearcutting and road density. We analyzed several landscape pattern metrics for the landscape as a whole and for the lodgepole pine and spruce/fir cover classes across these maps, and determined the relative effects of clearcutting and road building on the pattern of each watershed. At both the landscape- and cover class-scales, clearcutting and road building resulted in increased fragmentation as represented by a distinct suite of landscape structural changes. Patch core area and mean patch size decreased, and edge density and patch density increased as a result of clearcuts and roads. Clearcuts and roads simplified patch shapes at the landscape scale, but increased the complexity of lodgepole pine patches. Roads appeared to be a more significant agent of change than clearcuts, and roads which were more evenly distributed across a watershed had a greater effect on landscape pattern than did those which were densely clustered. Examining individual watersheds allows for the comparison of fragmentation among watersheds, as well as across the landscape as a whole. Similar studies of landscape structure in other National Forests and on other public lands may help to identify and prevent further fragmentation of these areas.     

Seasonal dynamics of soil nitrogen availability and phosphorus fractions under urban forest remnants of different vegetation communities in Southern China

Urban forest remnants are a useful tool to study forest response to global change with urbanization. Soil nutrient status in urban forests has not been well understood, especially under the pressure of rapid urbanization in developing countries. In this study, ion-exchange resin bags and a modified Hedley P fractionation procedure were used to measure seasonal dynamics of soil N forms (ammonium and nitrate) and P fractions (available, labile, slow, occlude and weathered mineral P) under urban forest remnants across a successional sequence and non-forest land in the city of Nanchang, Southern China. Results showed that soil N availability varied with season and vegetation community (P < 0.05). Soil P fractions showed minimal seasonal variation except available P, while their averages generally increased with forest development from non-forest land to coniferous forest to conifer-broadleaf mixed forest to evergreen broad-leaved forest. The ratios of fresh soil N forms to P fractions generally decreased with forest development, while N forms absorbed by resins to P fractions generally increased from non-forest land to coniferous forest, then decreased from conifer-broadleaf mixed forest to evergreen broad-leaved forest. It is suggested that urban older forest remnants could easily move to N saturation status and soil P enrichment, causing urban water pollution due to the accumulative effect of elevated atmospheric N deposition and exogenous P input with urbanization.     

Improving land change detection based on uncertain survey maps using fuzzy sets

In this paper we present a method for correcting inherent classification bias in historical survey maps with which subsequent land cover change analysis can be improved. We linked generalized linear modelling techniques for spatial uncertainty prediction to fuzzy set based operations. The predicted uncertainty information was used to compute fuzzy memberships of forest and non-forest classes at each location. These memberships were used to reclassify the original map based on decision rules, which take into consideration the differences in identification likelihood during the historical mapping. Since the forest area was underestimated in the original mapping, the process allows to correct this bias by favouring forest, especially where uncertainty was high. The analyses were performed in a cross-wise manner between two study areas in order to examine whether the bias correction algorithm would still hold in an independent test area. Our approach resulted in a significant improvement of the original map as indicated by an increase of the Normalized Mutual Information from 0.26 and 0.36 to 0.38 and 0.45 for the cross-wise test against reference maps in Pontresina and St. Moritz, respectively. Consequently subsequent land cover change assessments could be considerably improved by reducing the deviations from a reference change by almost 50 percent. We concluded that the use of logistic regression techniques for uncertainty modelling based on topographic gradients and fuzzy set operations are useful tools for predictively reducing uncertainty in maps and land cover change models. The procedure allows to get more reliable area estimates of crisp classes and it improves the computation of the fuzzy areas of classes. The approach has limitations when the original map shows high initial accuracy.     

Influence of biophysical factors and differences in Ojibwe reservation versus Euro-American social histories on forest landscape change in northern Wisconsin,USA

Landscape ecology studies have demonstrated that past modifications of the landscape frequently influence its structure, highlighting the utility of integrating historical perspectives from the fields of historical ecology and environmental history. Yet questions remain for historically-informed landscape ecology, especially the relative influence of social factors, compared to biophysical factors, on long-term land-cover change. Moreover, methods are needed to more effectively link history to ecology, specifically to illuminate the underlying political, economic, and cultural forces that influence heterogeneous human drivers of land-cover change. In northern Wisconsin, USA, we assess the magnitude of human historical forces, relative to biophysical factors, on land-cover change of a landscape dominated by eastern white pine (Pinus strobus L.) forest before Euro-American settlement. First, we characterize land-cover transitions of pine-dominant sites over three intervals (1860–1931; 1931–1951; 1951–1987). Transition analysis shows that white pine was replaced by secondary successional forest communities and agricultural land-covers. Second, we assess the relative influence of a socio-historical variable (“on-/off-Indian reservation”), soil texture (clay and sand), and elevation on land-cover transition. On the Lake Superior clay plain, models that combine socio-historical and biophysical variables best explain long-term land-cover change. The socio-historical variable dominates: the magnitude and rate of land-cover change differs among regions exposed to contrasting human histories. Third, we developed an integrative environmental history-landscape ecology approach, thereby facilitating linkage of observed land-cover transitions to broader political, economic, and cultural forces. These results are relevant to other landscape investigations that integrate history and ecology.     

Changes in land-use/land-cover patterns in Italy and their implications for biodiversity conservation

Land-use/land-cover change is the most important factor in causing biodiversity loss. The Mediterranean region has been affected by antropic disturbance for thousands of years, and is, nowadays, one of the most significantly altered hotspots in the world. However, in the last years a significant increase in forest cover has been measured. These new patterns are independent from planned conservation strategies and appear to have a substantial impact on landscapes and biodiversity. We used three land-use/land-cover maps (from 1960 to 2000) covering the Italian peninsula to analyze the pattern of land-use/land-cover change. We measured an increase in forests, especially in mountains, an increase in artificial areas, especially in coastal zones, and a decrease in pastures. Intensively cultivated areas showed a limited decrease while extensively cultivated ones showed a marked decrease. In the same period mammal and bird species followed a similar pattern, with forest birds, ungulates and carnivores increasing, and typically Mediterranean species decreasing. We suggest that our results may provide important information, which could be useful for conservation planning in the entire Mediterranean hotspot. We suggest that an increasing conservation effort should be made to protect the Mediterranean-type forests and scrublands, as well as traditional agricultural practices. Moreover, future conservation efforts should consider the broad socio-political and ecological processes that are most likely to occur across the whole hotspot, especially along coastal areas, and the network of protected areas should be functionally integrated in a conservation strategy that includes the human-dominated landscape.     

Effects of Intensive Forest Management on Stand and Landscape Characteristics in Northern New Brunswick, Canada (1945–2027)

Historical and future projected landscape patterns and changes caused by harvesting and silviculture were evaluated for a 189,000 ha, intensively managed forest in New Brunswick, Canada. We compared changes in species composition, age classes, and patch characteristics (area, size, density, edge, shape, and core area) between 1945, 2002, and projections to 2027 (based on the landowner's spatial forest management plan). In 1945, the landbase was 40% softwood, 37% mixed hardwood–softwood, 10% hardwood, and 9% softwood–cedar. From 1945 to 2002 and 2027, respectively, softwood forest area increased by 2 and 11%, mixedwood decreased by 19 and 20%, and hardwood area increased by 15 and 14%, and softwood–cedar increased by 6% and then decreased by 7%. In 1945, forest >70 years old comprised 85% of the landscape, but declined to 44% in 2002 and was projected to encompass 41% in 2027. Increased area harvested, decreasing harvest patch size, and protection against natural disturbances resulted in progressively smaller mean and less variable patch sizes from 1945 to 2002. Based upon the 25-year forest management plan, this trend was projected to continue, with the exception of nine patches >1000 ha created by 2027, eight of which were softwood plantations. Stand type successional dynamics were highly variable in both harvested and non-harvested areas, and in some cases were unexpected. Few of the 1945 stand types remained static by 2002, with 42 and 35% of mixedwood shifting to softwood as a result of harvesting, and to hardwood as a result of both harvesting and spruce budworm (Choristoneura fumiferana Clem.) outbreaks in the 1950s and 1970s. This study demonstrates the strong cumulative effect of forest management on landscape patterns, especially the socially mandated drive for smaller clearcuts resulting in the loss of large patches.