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.     

Transitions in forest fragmentation: implications for restoration opportunities at regional scales

Where the potential natural vegetation is continuous forest (e.g., eastern US), a region can be divided into smaller units (e.g., counties, watersheds), and a graph of the proportion of forest in the largest patch versus the proportion in anthropogenic cover can be used as an index of forest fragmentation. If forests are not fragmented beyond that converted to anthropogenic cover, there would be only one patch in the unit and its proportional size would equal 1 minus the percentage of anthropogenic cover. For a set of 130 watersheds in the mid-Atlantic region, there was a transition in forest fragmentation between 15 and 20% anthropogenic cover. The potential for mitigating fragmentation by connecting two or more disjunct forest patches was low when percent anthropogenic cover was low, highest at moderate proportions of anthropogenic cover, and again low as the proportion of anthropogenic cover increased toward 100%. This fragmentation index could be used to prioritize locations for restoration by targeting watersheds where there would be the greatest increase in the size of the largest forest patch.     

Land use and forest cover on private parcels in the Upper Midwest USA, 1970 to 1990

This paper analyzes the interactions between land use and forest cover in the Upper Midwest, USA from 1970 to 1990. New data are presented and interpreted to evaluate the effects of land-use changes, especially abandonment of agriculture and dispersed development, on forest cover throughout the region. Forest-cover data were collected from Landsat satellite imagery and land use was interpreted from aerial photographs for land parcels, based on archival maps of land ownership. In general, forest cover increased throughout the region and throughout the period. Simultaneously, the area used for agriculture declined, much of it being converted to natural uses, and the area of land in low density residential development increased. Forest cover increased most rapidly on low density residential lands and in counties in which a large percentage of homes were for seasonal use (i.e., vacation homes). The data suggest that the transformation of the region from an extractive (i.e., forestry and agriculture) to a recreation-based service economy has played a significant role in the increasing forest cover observed throughout the region. This revised version was published online in July 2006 with corrections to the Cover Date.     

Recent forest cover type transitions and landscape structural changes in northeast Minnesota,USA

Landsat TM satellite data covering an approximate 5-year interval (1990–1995) were used to quantify spatial pattern and transition rates between forest ecological states for a 2.76 million ha region in northeast Minnesota. Changes in forest cover were stratified by Ecological Subsection, management status, and by ownership categories using a 1995 digital ownership layer. Approximately 4.2% of the 1990 mature forested area was converted to early successional types by 1995. Of this 4.2%, private lands accounted for 33%, federal lands 31%, county lands 20% and state lands 16%. Notable conversion percentages by cover type category were spruce-fir (−5.3%), aspen-birch(−4.7%), jack pine (−4.6%) and black spruce(−3.0%). Transition rates were also adjusted to fit ten-year time intervals. Shannon-Weaver Eveness and edge density of cover types increased over the study period as relative contagion and interior forest area decreased. These trends suggest both smaller patches and a more even distribution of cover types. Area of upland conifers, lowland conifers and lowland hardwoods decreased while the area of mature upland hardwoods increased in most patch size classes except the > 500 ha class which showed a substantial decrease in area. The area of early successional types increased in most patch size classes. Non-industrial private forestland had the lowest proportion of interior forest of all ownership categories -decreasing by 13.5% in five years. Smaller average cut-unit size sand uncoordinated forest management is the likely cause since cutting rates between private and public forestland were similar. This revised version was published online in July 2006 with corrections to the Cover Date.     

Influence of high-resolution data on the assessment of forest fragmentation

Context

Remote sensing has been a foundation of landscape ecology. The spatial resolution (pixel size) of remotely sensed land cover products has improved since the introduction of landscape ecology in the United States. Because patterns depend on spatial resolution, emerging improvements in the spatial resolution of land cover may lead to new insights about the scaling of landscape patterns.

Objective

We compared forest fragmentation measures derived from very high resolution (1 m²) data with the same measures derived from the commonly used (30 m?×??30 m; 900 m²) Landsat-based data.

Methods

We applied area-density scaling to binary (forest; non-forest) maps for both sources to derive source-specific estimates of dominant (density ≥?60%), interior (≥?90%), and intact (100%) forest.

Results

Switching from low- to high-resolution data produced statistical and geographic shifts in forest spatial patterns. Forest and non-forest features that were “invisible” at low resolution but identifiable at high resolution resulted in higher estimates of dominant and interior forest but lower estimates of intact forest from the high-resolution source. Overall, the high-resolution data detected more forest that was more contagiously distributed even at larger spatial scales.

Conclusion

We anticipate that improvements in the spatial resolution of remotely sensed land cover products will advance landscape ecology through re-interpretations of patterns and scaling, by fostering new landscape pattern measurements, and by testing new spatial pattern-ecological process hypotheses.

     

Assessing net carbon sequestration on urban and community forests of northern New England,USA

Urban and community forests play an important role in the overall carbon budget of the USA. Accurately quantifying carbon sequestration by these forests can provide insight for strategic planning to mitigate greenhouse gas effects on climate change. This study provides a new methodology to estimate net forest carbon sequestration (FCS) in urban and community lands of northern New England using ground based forest growth rates, housing density data, satellite derived land cover and tree canopy cover maps at the county level. We estimated that the region's urban and community forests sequestered 603,200 tC/yr ($38.7 million/yr value), contributing 8.2% of regional net forest ecosystem carbon sequestration. The contributions at the state level varied from 2.3% in Vermont to 16.6% in New Hampshire with substantial variation at the county level up to 73.3%. Spatially, contribution rates from urban and community forests at the county level were much higher and concentrated in southeast portion of NH and southwest portion of ME along the coast, and decreased toward inland areas. Our estimated net FCS compared reasonably with gross FCS in the region reported by a previous study. On average, the net FCS was 34.2% lower (varying from 41.9% lower in Vermont to 28.1% lower in Maine) than the corresponding gross FCS mainly because of a lower regional average net growth rate used in this study, compared to the national average gross carbon sequestration rate used in the previous study.     

Trade-offs between tree cover, carbon storage and floristic biodiversity in reforesting landscapes

This study explores the relationships between an increase in tree cover area (i.e., natural and planted-tree land covers) and changes in forest carbon storage and the potential of a landscape to provide habitat for native floristic biodiversity. Four areas experiencing an increase in tree cover were analyzed. We developed a metric estimating the potential to support native biodiversity based on tree cover type (plantation or natural forests) and the landscape pattern of natural and anthropogenic land covers. We used published estimates for forest and plantation carbon stocks for each region. Focus regions in northwestern Costa Rica, northern Vietnam, southern Chile and highland Ecuador all showed an increase in tree cover area of 390?%, 260?%, 123?% and 418?%, respectively. Landscapes experiencing increases in natural secondary forest also experienced an increase in carbon stored above and below ground, and in the potential to support native floristic biodiversity. Study landscapes in Chile and Ecuador experiencing an expansion of exotic plantations saw their carbon stock decrease along with their potential to support native floristic biodiversity. This study shows that an increase in forest area does not necessarily imply an increased provision of ecosystem services when landscapes are reforesting with monoculture plantations of exotic tree species. Changes in the support of native biodiversity and the carbon stored in pulp rotation plantations, along with other ecosystem services, should be fully considered before implementing reforestation projects.     

Effects of changing landscape pattern and U. S. G. S. land cover data variability on ecoregion discrimination across a forest-agriculture gradient

We examined the use of coarse resolution land cover data (USGS LUDA) to accurately discriminate ecoregions and landscape-scale features important to biodiversity monitoring and management. We used land cover composition and landscape indices, correlation and principal components analysis, and comparison with finer-grained Landsat TM data, to assess how well LUDA data discriminate changing patterns across an agriculture-forest gradient in Minnesota, U.S.A. We found LUDA data to be most accurate at general class levels of agriculture and forest dominance (Anderson Level I), but in consistent and limited in ecotonal areas of the gradient and within forested portions of the study region at finer classes (Anderson Level II). We expected LUDA to over-represent major (matrix) cover types and under-represent minor types, but this was not consistent with all classes. 1) Land cover types respond individualistically across the gradient, changing landscape grain as well as their spatial distribution and abundance. 2) Agriculture is not over-represented where it is the dominant land cover type, but forest is over-represented where it is dominant. 3) Individual forest types are under-represented in an open land matrix. 4) Within forested areas, mixed deciduous-coniferous forest is over-represented by several orders of magnitude and the separate conifer and hardwood types under-represented. Across gradual, transitional agriculture-forest areas, LUDA cover class dominance changes abruptly in a stair-step fashion. In general, rare cover types that are discrete, such as forest in agriculture or wetlands or water in forest, are more accurately represented than cover classes having lower contrast with the matrix. Northward across the gradient, important changes in the proportions of conifer and deciduous forest mixtures occur at scales not discriminated by LUDA data. Results suggest that finer-grained data are needed to map within-state ecoregions and discriminate important landscape characteristics. LUDA data, or similar coarse resolution data sources, should be used with caution and the biases fully understood before being applied in regional landscape management. This revised version was published online in July 2006 with corrections to the Cover Date.     

A large-scale fire suppression edge-effect on forest composition in the New Jersey Pinelands

Broad scale ecological edge-effects are most likely common in urbanized landscapes prone to wildfire, but most edge-effect studies have focused on fine scale processes such as shade tolerance and seed dispersal. Evidence has suggested a shift from pine dominated to oak dominated forests at the interface of developed land and natural areas in the Pinelands of New Jersey with the presence of a large edge-effect due to fire suppression. The goal of this study was to assess the location, magnitude and mechanism of the shift from pine to oak cover focusing on distance to human-altered land as the driver of fire suppression and forest composition changes. Overall, fire frequency and upland pine cover decreased sharply closer to human-altered land and affected up to 420 m of adjacent upland forest. Other factors, such as prescribed fire and wetlands configurations may play a role in the interior forest dynamics, but trends toward lower upland pine forest cover and higher upland oak cover near human altered were dominant. The areal summations of distance from altered land and the use of percent change thresholds for determining the scale and magnitude of large scale ecological edge-effects could be useful to managers attempting to maintain or restore forest types in areas of high wildland–urban interface.     

Modeling habitat dynamics accounting for possible misclassification

Land cover data are widely used in ecology as land cover change is a major component of changes affecting ecological systems. Landscape change estimates are characterized by classification errors. Researchers have used error matrices to adjust estimates of areal extent, but estimation of land cover change is more difficult and more challenging, with error in classification being confused with change. We modeled land cover dynamics for a discrete set of habitat states. The approach accounts for state uncertainty to produce unbiased estimates of habitat transition probabilities using ground information to inform error rates. We consider the case when true and observed habitat states are available for the same geographic unit (pixel) and when true and observed states are obtained at one level of resolution, but transition probabilities estimated at a different level of resolution (aggregations of pixels). Simulation results showed a strong bias when estimating transition probabilities if misclassification was not accounted for. Scaling-up does not necessarily decrease the bias and can even increase it. Analyses of land cover data in the Southeast region of the USA showed that land change patterns appeared distorted if misclassification was not accounted for: rate of habitat turnover was artificially increased and habitat composition appeared more homogeneous. Not properly accounting for land cover misclassification can produce misleading inferences about habitat state and dynamics and also misleading predictions about species distributions based on habitat. Our models that explicitly account for state uncertainty should be useful in obtaining more accurate inferences about change from data that include errors.     

Spatial patterning of fuels and fire hazard across a central U.S. deciduous forest region

Information describing spatial and temporal variability of forest fuel conditions is essential to assessing overall fire hazard and risk. Limited information exists describing spatial characteristics of fuels in the eastern deciduous forest region, particularly in dry oak-dominated regions that historically burned relatively frequently. From an extensive fuels survey of unmanaged forest lands (1,446 plots) we described fuel loadings and spatial patterns of fine and coarse fuels. We attempted to explain the variability in fuel loading of each time-lag fuel class using landscape and seasonal variables through a multiple regression modeling approach. Size class distributions of woody fuels were generally homogeneous across the region except in the glaciated portions of Illinois where loadings appeared lower. Temporally, litter depths progressively decreased from leaffall (November). A fire hazard model that combined seasonal changes in litter depth and fuel moisture content depicted the degree of regional spatial variability during the transition between extreme dry and wet conditions. In the future, fire hazard indices could be paired with ignition probabilities in order to assess spatio-temporal variability of fire risk within the region.     

Sampling to characterize landscape pattern

Current reseach suggests that metrics of landscape pattern may reflect ecological processes operating at different scales and may provide an appropriate indicator for monitoring regional ecological changes. This paper examines the extent to which a 1/16 areal subset of the landscape using equally spaced 40-km² hexagons can characterize the spatial extent of land cover types and landscape pattern (number of types of edges, patch shape complexity, dominance, and contagion). For 200-m resolution data the hexagon subset gives a reasonable estimate of overall landscape cover but may not be adequate for monitoring uncommon land cover types such as wetlands. For agriculture and forest, their proportion of the full landscape units is only outside the 95% confidence interval of the hexagon estimate 4–8% of the time, whereas the proportions for wetland and barren areas are outside the confidence interval 11–34% of the time. The hexagon subset also does not appear to be adequate as the sole basis for monitoring landscape pattern. The values for contagion, dominance, and shape complexity calculated on the full landscape units are outside the 95% confidence interval of the hexagon estimate 27–76% of the time. Other statistical analyses include regressions between full landscape and hexagon subsets, mean differences and standard errors along with tests on number of positive and negative values, and percent relative error of hexagon estimates.Although the research described in this article has been funded in part by the U.S. Environmental Protection Agency, under Interagency Agreement DW89934921-01-0 with the U.S. Department of Energy under Contract DE-AC05-84OR21400 with Martin Marietta Energy Systems, Inc., it has not been subjected to Agency review. Therefore, it does not necessarily reflect the views of the Agency. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.Research supported by the Landscape Characterization Project, Environmental Monitoring and Assessment Program, U.S. Environmental Protection Agency, under Interagency Agreement DW89934921-01-0 with the U.S. Department of Energy under Contract DE-AC05-84OR21400 with Martin Marietta Energy Systems, Inc., Environmental Sciences Division Publication No. 4090.     

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.     

90 years of forest cover change in an urbanizing watershed: spatial and temporal dynamics

Landscape structure in the Eastern US experienced great changes in the last century with the expansion of forest cover into abandoned agricultural land and the clearing of secondary forest cover for urban development. In this paper, the spatial and temporal patterns of forest cover from 1914 to 2004 in the Gwynns Falls watershed in Baltimore, Maryland were quantified from historic maps and aerial photographs. Using a database of forest patches from six times—1914, 1938, 1957, 1971, 1999, and 2004—we found that forest cover changed, both temporally and spatially. While total forest area remained essentially constant, turnover in forest cover was very substantial. Less than 20% of initial forest cover remained unchanged. Forest cover became increasingly fragmented as the number, size, shape, and spatial distribution of forest patches within the watershed changed greatly. Forest patch change was also analyzed within 3-km distance bands extending from the urban core to the more suburban end of the watershed. This analysis showed that, over time, the location of high rates of forest cover change shifted from urban to suburban bands which coincides with the spatial shift of urbanization. Forest cover tended to be more stable in and near the urban center, whereas forest cover changed more in areas where urbanization was still in process. These results may have critical implications for the ecological functioning of forest patches and underscore the need to integrate multi-temporal data layers to investigate the spatial pattern of forest cover and the temporal variations of that spatial pattern.     

Landscapes as continuous entities: forest disturbance and recovery in the Albertine Rift landscape

Kibale National Park, within the Albertine Rift, is known for its rich biodiversity. High human population density and agricultural conversion in the surrounding landscape have created enormous resource pressure on forest fragments outside the park. Kibale presents a complex protected forest landscape comprising intact forest inside the park, logged areas inside the park, a game corridor with degraded forest, and forest fragments in the landscape surrounding the park. To explore the effect of these different levels of forest management and protection over time, we assessed forest change over the previous three decades, using both discrete and continuous data analyses of satellite imagery. Park boundaries have remained fairly intact and forest cover has been maintained or increased inside the park, while there has been a high level of deforestation in the landscape surrounding the park. While absolute changes in land cover are important changes in vegetation productivity, within land cover classes are often more telling of longer term changes and future directions of change. The park has lower Normalized Difference Vegetation Index (NDVI) values than the forest fragments outside the park and the formerly logged area—probably due to forest regeneration and early succession stage. The corridor region has lower productivity, which is surprising given this is also a newer regrowth region and so should be similar to the logged and forest fragments. Overall, concern can be raised for the future trajectory of this park. Although forest cover has been maintained, forest health may be an issue, which for future management, climate change, biodiversity, and increased human pressure may signify troubling signs.     

Spatial scaling of core and dominant forest cover in the Upper Mississippi and Illinois River floodplains, USA

Different organisms respond to spatial structure in different terms and across different spatial scales. As a consequence, efforts to reverse habitat loss and fragmentation through strategic habitat restoration ought to account for the different habitat density and scale requirements of various taxonomic groups. Here, we estimated the local density of floodplain forest surrounding each of ~20 million 10-m forested pixels of the Upper Mississippi and Illinois River floodplains by using moving windows of multiple sizes (1?C100 ha). We further identified forest pixels that met two local density thresholds: ??core?? forest pixels were nested in a 100% (unfragmented) forested window and ??dominant?? forest pixels were those nested in a >60% forested window. Finally, we fit two scaling functions to declines in the proportion of forest cover meeting these criteria with increasing window length for 107 management-relevant focal areas: a power function (i.e. self-similar, fractal-like scaling) and an exponential decay function (fractal dimension depends on scale). The exponential decay function consistently explained more variation in changes to the proportion of forest meeting both the ??core?? and ??dominant?? criteria with increasing window length than did the power function, suggesting that elevation, soil type, hydrology, and human land use constrain these forest types to a limited range of scales. To examine these scales, we transformed the decay constants to measures of the distance at which the probability of forest meeting the ??core?? and ??dominant?? criteria was cut in half (S _1/2, m). S _1/2 for core forest was typically between ~55 and ~95 m depending on location along the river, indicating that core forest cover is restricted to extremely fine scales. In contrast, half of all dominant forest cover was lost at scales that were typically between ~525 and 750 m, but S _1/2 was as long as 1,800 m. S _1/2 is a simple measure that (1) condenses information derived from multi-scale analyses, (2) allows for comparisons of the amount of forest habitat available to species with different habitat density and scale requirements, and (3) can be used as an index of the spatial continuity of habitat types that do not scale fractally.     

新疆野苹果居群年龄结构及郁闭度研究

对新疆巩留与新源2地的新疆野苹果居群年龄结构及郁闭度进行测定和分析,旨在为新疆野苹果资源的保护保存提供依据。结果表明,在随机选取的200个单株中,巩留居群Ⅰ级幼树为0,而且Ⅱ级小树数量也极少,仅2株,只占1%,年龄级构成有下降性特征,存活曲线呈断点凸型,故年龄结构应属老衰类型,郁闭度为0.47;新源居群有Ⅰ级幼树,10株占5%,Ⅱ级小树达26株占13%,年龄级构成有稳定中略有上升的特征,存活曲线呈弧形凸型,故年龄结构应属稳定类型,郁闭度为0.80。上述结果显示,巩留新疆野苹果居群破坏严重,亟待加强保护,而新源新疆野苹果居群保存较完好。     

Multi-temporal trajectories of landscape change explain forest biodiversity in urbanizing ecosystems

Context

Forest loss and fragmentation negatively affect biodiversity. However, disturbances in forest canopy resulting from repeated deforestation and reforestation are also likely important drivers of biodiversity, but are overlooked when forest cover change is assessed using a single time interval.

Objectives

We investigated two questions at the nexus of plant diversity and forest cover change dynamics: (1) Do multitemporal forest cover change trajectories explain patterns of plant diversity better than a simple measure of overall forest change? (2) Are specific types of forest cover change trajectories associated with significantly higher or lower levels of diversity?

Methods

We sampled plant biodiversity in forests spanning the Charlotte, NC, region. We derived forest cover change trajectories occurring within nested spatial extents per sample site using a time series of aerial photos from 1938 to 2009, then classified trajectories by spatio-temporal patterns of change. While accounting for landscape and environmental covariates, we assessed the effects of the trajectory classes as compared to net forest cover change on native plant diversity.

Results

Our results indicated that forest stand diversity is best explained by forest change trajectories, while the herb layer is better explained by net forest cover change. Three distinct forest change trajectory classes were found to influence the forest stand and herb layer.

Conclusions

The influence of forest dynamics on biodiversity can be overlooked in analyses that use only net forest cover change. Our results illustrate the utility of assessing how specific trajectories of past land cover change influence biodiversity patterns in the present.