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.     

Alternative spatial resolutions and estimation of carbon flux over a managed forest landscape in Western Oregon

Spatially-distributed estimates of biologically-driven CO₂ flux are of interest in relation to understanding the global carbon cycle. Global coverage by satellite sensors offers an opportunity to assess terrestrial carbon (C) flux using a variety of approaches and corresponding spatial resolutions. An important consideration in evaluating the approaches concerns the scale of the spatial heterogeneity in land cover over the domain being studied. In the Pacific Northwest region of the United States, forests are highly fragmented with respect to stand age class and hence C flux. In this study, the effects of spatial resolution on estimates of total annual net primary production (NPP) and net ecosystem production (NEP) for a 96 km² area in the central Cascades Mountains of western Oregon were examined. The scaling approach was a simple `measure and multiply' algorithm. At the highest spatial resolution (25 m), a stand age map derived from Landsat Thematic Mapper imagery provided the area for each of six forest age classes. The products of area for each age class and its respective NPP or NEP were summed for the area wide estimates. In order to evaluate potential errors at coarser resolutions, the stand age map was resampled to grain sizes of 100, 250, 500 and 1000 m using a majority filter reclassification. Local variance in near-infrared (NIR) band digital number at successively coarser grain sizes was also examined to characterize the scale of the heterogeneity in the scene. For this managed forest landscape, proportional estimation error in land cover classification at the coarsest resolution varied from –1.0 to +0.6 depending on the initial representation and the spatial distribution of the age class. The overall accuracy of the 1000 m resolution map was 42% with respect to the 25 m map. Analysis of local variance in NIR digital number suggested a patch size on the order of 100–500 m on a side. Total estimated NPP was 12% lower and total estimated NEP was 4% lower at 1000 m compared to 25 m. Carbon flux estimates based on quantifying differences in total biomass stored on the landscape at two points in time might be affected more strongly by a coarse resolution analysis because the differences among classes in biomass are more extreme than the differences in C flux and because the additional steps in the flux algorithm would contribute to error propagation. Scaling exercises involving reclassification of fine scale imagery over a range of grain sizes may be a useful screening tool for stratifying regions of the terrestrial surface relative to optimizing the spatial resolution for C flux estimation purposes.     

Linear downscaling from MODIS to landsat: connecting landscape composition with ecosystem functions

Context

The open and free access to Landsat and MODIS products have greatly promoted scientific investigations on spatiotemporal change in land mosaics and ecosystem functions at landscape to regional scales. Unfortunately, there is a major mismatch in spatial resolution between MODIS products at coarser resolution (≥?250 m) and landscape structure based on classified Landsat scenes at finer resolution (30 m).

Objectives

Based on practical needs for downscaling popular MODIS products at 500 m resolution to match classified land cover at Landsat 30 m resolution, we proposed an innovative modelling approach so that landscape structure and ecosystem functions can be directly studied for their interconnections. As a proof-of-concept of our downscaling approach, we selected the watershed of the Kalamazoo River in southwestern Michigan, USA as the testbed.

Methods

MODIS products for three fundamental variables of ecosystem function are downscaled to ensure the approach can be extrapolated to multiple functional measurements. They are blue-sky albedo (0–1), evapotranspiration (ET, mm), and gross primary production (GPP, Mg C ha^?1 year^?1). An object-oriented classification of Landsat images in 2011 was processed to generate a land cover map for landscape structure. The downscaling model was tested for the five Level IV ecoregions within the watershed.

Results

We achieved satisfactory downscaling models for albedo, ET, and GPP for all five ecoregions. The adjusted R² was?>?0.995 for albedo, 0.915–0.997 for ET, and 0.902–0.962 for GPP. The estimated albedo, ET, and GPP values appear different in the region. The estimated albedo was the lowest for water (0.076–0.107) and the highest for cropland (0.166–0.172). Estimated ET was the highest for the built-up cover type (525.6–687.1 mm) and the lowest for forest (209.7–459.7 mm). The estimated GPP was the highest for the build-up cover type (8.65–9.85 Mg C ha^?1 year^?1) and the lowest for forest.

Conclusions

Estimated values for albedo, ET, and GPP appear reasonable for their ranges in the Kalamazoo River region and are consistent with values reported in the literature. Despite these promising results, the downscaling approach relies on strong assumptions and can carry substantial uncertainty. It is only valid at a spatial scale where similar climate, soil, and landforms exist (i.e., values in isolated patches of the same cover type are similar). Plausibly, the uncertainties associated with each estimation, as well as the model residuals, can be explored for other pattern-process relationships within the landscape.

     

Spatial patterns of macroinvertebrate functional feeding groups in streams in relation to physical variables and land-cover in Southwestern France

Artificial neural networks were used to quantify the distribution of macroinvertebrate functional feeding groups (FFGs) in relation to physical variables and to land-cover in the Adour–Garonne stream system (SW France; 116,000 km²). The relative abundances of 5 FFGs were calculated from macroinvertebrate data recorded at 165 sampling sites. Each site was characterized using 5 physical variables (elevation, stream order, stream width, distance from the source, slope) and 3 land-cover variables (% forested, % urban areas, % agricultural areas). The sites were first classified using the Self-Organizing Map algorithm (SOM), according to the physical and land-cover variables. Two major clusters of sites corresponded to anthropogenically modified and natural areas, respectively. Anthropogenically modified areas were clearly divided into agricultural and urban landscapes. Each major cluster was divided into 3–4 subsets of sites according to a topographic gradient of physical variables. To examine the variability of the communities, FFG proportions at the 165 sites were examined on the SOM trained with physical and land-cover variables. When the riverine landscape was natural, FFG patterns responded to the upstream–downstream gradient in physical variables. When the landscape was altered by agriculture or urbanization, the effects of land-cover on FFGs overcame the influence of the physical variables. The categorization of the landscape into forested, agricultural, and urban areas was relevant to detect changes in FFG patterns. In light of increasing development along riparian zones, the use of SOMs to detect responses of FFGs to landscape alterations at regional scales exemplifies an effective technique for assessing river health based on ecological indicator groups.     

Normalized difference vegetation index (NDVI) as a marker of surrounding greenness in epidemiological studies: The case of Barcelona city

The normalized difference vegetation index (NDVI) is often used as a marker of surrounding greenness in epidemiological studies aiming to evaluate the health effects of green space in urban settings. However, it is not clear the relationship between built environment characteristics, including green space, and NDVI. We aimed to evaluate the relationship between built environment characteristics, based on land-use and land-cover maps, and NDVI as a marker of surrounding greenness in the city of Barcelona. We used data from an already existing cohort of pregnant women in Barcelona (N = 8402). NDVI was derived and averaged within buffers of 100 m and 300 m for each participant, and categories of the built environment (m²) were derived from land-use and land-cover maps of Barcelona. We conducted ANOVA models to calculate the contribution (R²) of each land-use (or land-cover) category. The variability in NDVI in Barcelona was mainly explained by urban green (R² between 0.32 and 0.53) and natural green areas (R² between 0.19 and 0.52), although for the latter less than 4% of the participants were exposed to this. Both land-use and land-cover maps explained NDVI at 300 m better (full models explaining 76% and 78%, respectively) than at 100 m buffers (full models explaining 55% and 54%, respectively). Results of the present study indicate that NDVI can be a useful greenness metric depending on the hypothesis and area of study. However, for certain sizes of study areas (buffers smaller than 100 m), NDVI might have a lower predictive value. Results of the present study should be replicated in studies from other cities with different urban characteristics and climate conditions.     

Influence of fire regimes on lodgepole pine stand age and density across the Yellowstone National Park (USA) landscape

A probabilistic spatial model was created based on empirical data to examine the influence of different fire regimes on stand structure of lodgepole pine (Pinus contorta var. latifolia) forests across a >500,000-ha landscape in Yellowstone National Park, Wyoming, USA. We asked how variation in the frequency of large fire events affects (1) the mean and annual variability of age and tree density (defined by postfire sapling density and subsequent stand density) of lodgepole pine stands and (2) the spatial pattern of stand age and density across the landscape. The model incorporates spatial and temporal variation in fire and serotiny in predicting postfire sapling densities of lodgepole pine. Empirical self-thinning and in-filling curves alter initital postfire sapling densities over decades to centuries. In response to a six-fold increase in the probability of large fires (0.003 to 0.018 year⁻¹), mean stand age declined from 291 to 121 years. Mean stand density did not increase appreciably at high elevations (1,029 to 1,249 stems ha⁻¹) where serotiny was low and postfire sapling density was relatively low (1,252 to 2,203 stems ha⁻¹). At low elevations, where prefire serotiny and postfire lodgepole pine density are high, mean stand densities increased from 2,807 to 7,664 stems ha⁻¹. Spatially, the patterns of stand age became more simplified across the landscape, yet patterns of stand density became more complex. In response to more frequent stand replacing fires, very high annual variability in postfire sapling density is expected, with higher means and greater variation in stand density across lodgepole pine landscapes, especially in the few decades following large fires.     

Landscape effects on scales of movement by white-tailed deer in an agricultural–forest matrix

Understanding how organisms respond to landscape heterogeneity is foundational to landscape ecology. We characterized seasonal scales of movement of white-tailed deer (Odocoileus viginianus) in an agricultural–forest matrix using first-passage time analysis (FPT) for 62 GPS-collared individuals. We investigated whether those scales were driven by demographic or landscape features. We found FPT for each individual across all seasons was typically dominated by a peak in variance of FPT/area at scales (radii) from 425 to 1,675 m. These peaks occurred at scales consistent with seasonal space use. We observed additional lower magnitude peaks at larger scales (3,000–6,000 m) and small scales (25–150 m). Peaks at larger scales were associated with seasonal migrations and dispersal events. Small scale peaks may represent resting or foraging behavior. Female movements were organized at smaller scales than males in the spring/summer season. Models relating landscape features to movement scales suggest that deer perceive and move within the landscape differently as the roles of dominant land-cover types shift seasonally. During winter, configuration (interspersion/juxtaposition) of land-cover types is more important to deer than during spring/summer and fall. During spring/summer and fall, movement behavior may be dictated by reproductive and harvest activities.     

Effects of aspect and altitude on carbon cycling processes in a temperate mountain forest catchment

Context

Varying altitudes and aspects within small distances are typically found in mountainous areas. Such a complex topography complicates the accurate quantification of forest C dynamics at larger scales.

Objectives

We determined the effects of altitude and aspect on forest C cycling in a typical, mountainous catchment in the Northern Limestone Alps.

Methods

Forest C pools and fluxes were measured along two altitudinal gradients (650–900 m a.s.l.) at south-west (SW) and north-east (NE) facing slopes. Net ecosystem production (NEP) was estimated using a biometric approach combining field measurements of aboveground biomass and soil CO₂ efflux (SR) with allometric functions, root:shoot ratios and empirical SR modeling.

Results

NEP was higher at the SW facing slope (6.60?±?3.01 t C ha^?1  year^?1), when compared to the NE facing slope (4.36?±?2.61 t C ha^?1 year^?1). SR was higher at the SW facing slope too, balancing out any difference in NEP between aspects (NE: 1.30?±?3.23 t C ha^?1 year^?1, SW: 1.65?±?3.34 t C ha^?1 year^?1). Soil organic C stocks significantly decreased with altitude. Forest NPP and NEP did not show clear altitudinal trends within the catchment.

Conclusions

Under current climate conditions, altitude and aspect adversely affect C sequestering and releasing processes, resulting in a relatively uniform forest NEP in the catchment. Hence, including detailed climatic and soil conditions, which are driven by altitude and aspect, will unlikely improve forest NEP estimates at the scale of the studied catchment. In a future climate, however, shifts in temperature and precipitation may disproportionally affect forest C cycling at the southward slopes through increased water limitation.

     

Carbon storage in a peri-urban neotropical forest: Assessing its potential and patterns of change over half a century

Forest ecosystems are associated with environmental regulation services, such as carbon storage, which is an outstanding service. Carbon fluxes in cities are difficult to estimate due to the scale at which they are addressed, particularly at the local level. In this work, we were interested in determining the carbon stored in the aboveground biomass of the tropical montane cloud forest tree species located on the western periphery of the city of Xalapa, Veracruz, Mexico. With these data, we interpolated the storage and sequestration over five decades through image satellites and aerial photography of this unique forest. Additionally, to assess this potential as a basis for a biodiversity contribution to city resilience, we conducted phytosociological sampling. Native species such as Quercus xalapensis, Liquidambar styraciflua var. mexicana and Q. lancifolia showed the most significant values of 72.92, 58.79, and 49.14 Mg ha⁻¹, respectively, of carbon. We used phytosociological sampling to better understand structural and functional features of urban forest biodiversity that can contribute to management practices for adaptation to climate change. In addition, the native species currently studied offer an opportunity for the city to implement better-targeted reforestation and ecological restoration programs for integrated landscaping in urban planning. Our results suggest that between 1966 and 2022, there was a forest recovery of 52.4 ha and an increase in urban areas of 63.4 ha, which is equivalent to an increase from 7,700.86 Mg ha⁻¹ in 1966 to 12,620.00 Mg ha⁻¹ in 2022. In this context, it is possible to both recover the vegetation cover and expand the city, thus avoiding part of the loss of ecosystem services that urbanization usually implies. This should be promoted among decision-makers and citizens in urban planning. Recovery processes can take place successfully in some cases even as urban areas expand. This possibility is relevant due to the many contributions that vegetation provides to citizens, including carbon storage. The opportunity to study five decades allows us to know the history, monitor the processes and make a projection to conserve the vegetation and improve management.     

Simulated productivity of heterogeneous patches in Southern African savanna landscapes using a canopy productivity model

A daily model of terrestrial productivity is used to simulate the annual productivity of heterogeneous vegetation structure at three savanna/woodland sites along a large moisture gradient in southern Africa. The horizontal distributions of vegetation structural parameters are derived from the three-dimensional canopy structure generated from detailed field observations of the vegetation at each site. Rainfall and daily climatic data are used to drive the model, resulting in a spatially explicit estimate of vegetation productivity in 100 m² patches over an area 810,000 m² (8,100 patches per site). Production is resolved into tree and grass components for each subplot. The model simulates the relative contribution of trees and grasses to net primary productivity (NPP) along the rainfall gradient. These simulated production estimates agree with previously published estimates of productivity in southern African savannas. Water-use efficiency of each site is directly related to the structural composition of the site and the differing water-use efficiencies for tree and grass functional types. To assess the role of spatial scale in governing estimates of vegetation productivity in heterogeneous landscapes, spatial aggregation is performed on the canopy mosaic at the northern-most (wettest) site for 625 m², 2500 m² and 5625 m² resolutions. These simulations result in similar overall patterns of average NPP for both trees and grasses, but drastically reduced distributions of productivity due to reduced structural heterogeneity. In particular, the aggregation of the detailed spatial mosaic to coarser resolutions is seen to eliminate information regarding demographic processes such as regeneration and mortality, and the dependence of grass productivity on over-story density. These results indicate that models of system productivity in savanna/woodland ecosystems must retain high spatial resolution to adequately characterize multi-year structural responses and to accurately represent the contribution of grass biomass to overall ecosystem production.This revised version was published online in May 2005 with corrections to the Cover Date.     

Large termitaria act as refugia for tall trees,deadwood and cavity-using birds in a miombo woodland

Landscape heterogeneity can play an important role in providing refugia and sustaining biodiversity in disturbed landscapes. Large Macrotermes (Isoptera) termite mounds in miombo woodlands form nutrient rich islands that sustain a different suite of woody plant species relative to the woodland matrix. We investigated the role of termitaria in providing habitat for cavity-using birds in miombo woodlands that had been greatly impacted by elephants and fire, by comparing the availability of habitat favored by cavity-using birds (tall trees, trees with deadwood, and cavities) on and off mounds, and then testing its effect on species richness and abundance of cavity-using birds. We surveyed 48 termitaria paired with 48 woodland matrix sites in the breeding season; and 54 matrix-termitarium pairs in the non-breeding season in Chizarira National Park, Zimbabwe. Generalized linear mixed-effects models showed that termitaria harboured significantly higher densities (ha⁻¹) of habitat components considered important for cavity nesting birds. Density of trees >6 m in height and incidence of trees with deadwood was nearly 10 times greater on mounds than in the matrix, and the density of cavities was nine times higher on mounds compared to the matrix. A model selection procedure showed that termitaria provided refugia for cavity-using birds and contributed to the resilience of bird communities through high on-mound densities of trees with deadwood. Large termitaria thus appear to play an important role in maintaining functionally important components of the avifauna in heavily impacted Miombo woodlands.     

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.     

Effects of ammonium sulphate and urea on NO3− and NO2− accumulation,nutrient contents and yield criteria in spinach

In this study, effects of ammonium sulphate (AS) and urea fertilizers on NO₃⁻ and NO₂⁻ accumulation, N, P, K, Ca, Mg, Fe, Cu, Zn, Mn contents and some yield criteria in spinach were investigated. Increments in nitrogen doses of AS and urea from 0 (control) to 150 kg N level ha⁻¹ increased NO₃⁻, NO₂⁻, total N contents and yield of spinach significantly, but usually decreased P, Zn and Mn contents. NO₃⁻ contents of spinach in 120 and 150 kg N ha⁻¹ of urea applications were higher than that of AS applications, while the NO₃⁻ contents of spinach in the lower application doses of AS were higher than that of urea applications. Increasing phosphorus availability in the higher doses of AS applications due to possibility of decreasing soil pH might be decrease NO₃⁻ accumulation in spinach by assimilating NO₃⁻ in protein form. NO₃⁻ and NO₂⁻ contents also gave the significant negative relationships with yield and P content in spinach. Decreasing micronutrient contents in spinach at the higher nitrogen doses might be due to dilution effect by increasing the plant biomass.     

Laser scanning of fine scale pattern along a hydrological gradient in a peatland ecosystem

Lowland ombrotrophic (rain-fed) peatlands are a declining ecological resource in Europe. Peatlands display characteristic patterns in vegetation and surface topography, linked to ecological function, hydrology, biodiversity and carbon sequestration. Laser scanning provides a means of precisely measuring vegetation pattern in peatlands, and thus holds promise as a tool for monitoring peatland condition. Terrestrial laser scanning (TLS) was used for measurement of vegetation pattern along an eco-hydrological gradient at a UK peatland (Wedholme Flow, Cumbria) at fine grain sizes (<1 cm spatial resolution over 10 m spatial extent). Seven sites were investigated—each showed varying water table and ecological characteristics. TLS data were analysed using semi-variogram analysis which enabled the scale of spatial dependence in vegetation structures to be measured. In addition ecological, hydrological and positional surveys were conducted to elucidate interpretation of spatial patterns. Results show that TLS was able to rapidly measure vegetation patterns associated with eco-hydrological condition classes. Intact sites with hummock-hollow topography showed an isotropic pattern with a grain size or length-scale of 1 m or less (indicated by semi-variogram range). Degraded sites with high shrub cover showed increased sill variance values at larger range distances—typically around 3–4 m. The work presented shows the advantages of TLS methodologies for rapid measurement of 3-D vegetation canopy structure and surface microtopography, at fine spatial scales, in short vegetation. The paper considers how these approaches may be extended to monitoring peatland structure over larger spatial extents from airborne LiDAR systems.     

Influence of landscape structure and stand age on species density and biomass of a tropical dry forest across spatial scales

Three central related issues in ecology are to identify spatial variation of ecological processes, to understand the relative influence of environmental and spatial variables, and to investigate the response of environmental variables at different spatial scales. These issues are particularly important for tropical dry forests, which have been comparatively less studied and are more threatened than other terrestrial ecosystems. This study aims to characterize relationships between community structure and landscape configuration and habitat type (stand age) considering different spatial scales for a tropical dry forest in Yucatan. Species density and above ground biomass were calculated from 276 sampling sites, while land cover classes were obtained from multi-spectral classification of a Spot 5 satellite imagery. Species density and biomass were related to stand age, landscape metrics of patch types (area, edge, shape, similarity and contrast) and principal coordinate of neighbor matrices (PCNM) variables using regression analysis. PCNM analysis was performed to interpret results in terms of spatial scales as well as to decompose variation into spatial, stand age and landscape structure components. Stand age was the most important variable for biomass, whereas landscape structure and spatial dependence had a comparable or even stronger influence on species density than stand age. At the very broad scale (8,000–10,500 m), stand age contributed most to biomass and landscape structure to species density. At the broad scale (2,000–8,000 m), stand age was the most important variable predicting both species density and biomass. Our results shed light on which landscape configurations could enhance plant diversity and above ground biomass.     

Textural Ordination Based on Fourier Spectral Decomposition: A Method to Analyze and Compare Landscape Patterns

We propose an approach to texture characterization and comparison that directly uses the information of digital images of the earth surface without requesting a prior distinction of structural ‘patches’. Digital images are partitioned into square ‘windows’ that define the scale of the analysis and which are submitted to the two-dimensional Fourier transform for extraction of a simplified textural characterization (in terms of coarseness) via the computation of a ‘radial’ power spectrum. Spectra computed from many images of the same size are systematically compared by means of a principal component analysis (PCA), which provides an ordination along a limited number of coarseness vs. fineness gradients. As an illustration, we applied this approach to digitized panchromatic air photos depicting various types of land cover in a semiarid landscape of northern Cameroon. We performed ‘textural ordinations’ at several scales by using square windows with sides ranging from 120 m to 1 km. At all scales, we found two coarseness gradients (PCA axes) based on the relative importance in the spectrum of large (> 50 km⁻¹), intermediate (30–50 km⁻¹), small (10–25 km⁻¹) and very small (<10 km⁻¹) spatial frequencies. Textural ordination based on Fourier spectra provides a powerful and consistent framework to identifying prominent scales of landscape patterns and to compare scaling properties across landscapes.     

Historic range of variability in landscape structure in subalpine forests of the Greater Yellowstone Area,USA

A measure of the historic range of variability (HRV) in landscape structure is essential for evaluating current landscape patterns of Rocky Mountain coniferous forests that have been subjected to intensive timber harvest. We used a geographic information system (GIS) and FRAGSTATS to calculate key landscape metrics on two ∼130,000-ha landscapes in the Greater Yellowstone Area, USA: one in Yellowstone National Park (YNP), which has been primarily shaped by natural fires, and a second in the adjacent Targhee National Forest (TNF), which has undergone intensive clearcutting for nearly 30 years. Digital maps of the current and historical landscape in YNP were developed from earlier stand age maps developed by Romme and Despain. Maps of the TNF landscape were adapted from United States Forest Service Resource Information System (RIS) data. Key landscape metrics were calculated at 20-yr intervals for YNP for the period from 1705-1995. These metrics were used to first evaluate the relative effects of small vs. large fire events on landscape structure and were then compared to similar metrics calculated for both pre- and post-harvest landscapes of the TNF. Large fires, such as those that burned in 1988, produced a structurally different landscape than did previous, smaller fires (1705-1985). The total number of patches of all types was higher after 1988 (694 vs. 340-404 before 1988), and mean patch size was reduced by almost half (186 ha vs. 319-379 ha). The amount of unburned forest was less following the 1988 fires (63% vs. 72-90% prior to 1988), yet the number of unburned patches increased by nearly an order of magnitude (230 vs. a maximum of 41 prior to 1988). Total core area and mean core area per patch decreased after 1988 relative to smaller fires (∼73,700 ha vs. 87,000-110,000 ha, and 320 ha vs. 2,123 ha, respectively). Notably, only edge density was similar (17 m ha⁻¹ after 1988) to earlier landscapes (9.8-14.2 m ha⁻¹).Three decades of timber harvesting dramatically altered landscape structure in the TNF. Total number of patches increased threefold (1,481 after harvest vs. 437 before harvest), and mean patch size decreased by ∼70% (91.3 ha vs. 309 ha). None of the post-harvest landscape metrics calculated for the TNF fell within the HRV as defined in YNP, even when the post-1988 landscape was considered. In contrast, pre-harvest TNF landscape metrics were all within, or very nearly within, the HRV for YNP. While reference conditions such as those identified by this study are useful for local and regional landscape evaluation and planning, additional research is necessary to understand the consequences of changes in landscape structure for population, community, ecosystem, and landscape function. This revised version was published online in July 2006 with corrections to the Cover Date.     

Estimating Settlement carbon stock and density using an inventory approach and quantifying their variation by land use and parcel size

A lack of very-high resolution land-cover data and in-situ carbon sampling in Settlement areas has limited the quantification of terrestrial carbon in Canadian Settlements and elsewhere. Without those data, it is difficult to quantify Settlement area terrestrial carbon for United Nations Framework Convention on Climate Change reporting within the Land Use, Land Use Change, and Forestry sector. The presented research takes a step toward filling this gap by first classifying Settlement land cover at a very-high resolution (<=80 cm, 93% overall accuracy). Then, with those data, an inventory approach is used to estimate carbon stocks based on local data, standard rulesets from the IPCC, and practice-based assumptions. Guided by FAIR principles, our approach is operationalized and available in a Jupyter Notebook for distribution, use, and extension by others. Results found that the study Settlement comprised 30% tree cover and 18% turfgrass. When analyzed by parcel size, carbon densities varied little for parcels less than 1.6 ha (3.9–4.2 kg C m^-2), but then increased with larger parcels up to 6.6 Gg C m^-2 for parcels > 8.1 ha. Among different land uses, industrial, commercial, and transportation had the lowest carbon densities (2.4–2.8 kg C m^-2), followed by high, medium, and low-density residential (3.6, 4.0, 8.9 kg C m^-2, respectively) with low-density residential almost achieving carbon densities in protected and recreation areas (10.2 kg C m^-2). Our results suggest that land use is a stronger driver of carbon-storage relative to parcel size, but their combination best represents the variation in carbon-storage in low-density residential land use. Currently, only carbon change in urban trees and deforestation around urban centres is reported in Canada’s National GHG Inventory Report. The present research quantifying carbon densities provides an analysis that could inform carbon change resulting from other land-use conversions and improve deforestation estimates by better defining the final state of a land-use change.     

Soil nitrogen and carbon dynamics in a fragmented landscape experiencing forest succession

Forest fragmentation is an increasingly common feature across the globe, but few studies examine its influence on biogeochemical fluxes. We assessed the influence of differences in successional trajectory and stem density with forest patch size on biomass quantity and quality and N transformations in the soil at an experimentally fragmented landscape in Kansas, USA. We measured N-related fluxes in the laboratory, not the field, to separate effects of microclimate and fragment edges from the effects of inherent biomass differences with patch size. We measured net N mineralization and N₂O fluxes in soil incubations, gross rates of ammonification and nitrification, and microbial biomass in soils. We also measured root and litterfall biomass, C:N ratios, and δ¹³C and δ¹⁵N signatures; litterfall [cellulose] and [lignin]; and [C], [N], and δ¹³C and δ¹⁵N of soil organic matter. Rates of net N mineralization and N₂O fluxes were greater (by 113% and 156%, respectively) in small patches than in large, as were gross rates of nitrification. These differences were associated with greater quantities of root biomass in small patch soil profiles (664.2 ± 233.3 vs 192.4 ± 66.2 g m⁻² for the top 15 cm). These roots had greater N concentration than in large patches, likely generating greater root derived organic N pools in small patches. These data suggest greater rates of N cycling in small forested patches compared to large patches, and that gaseous N loss from the ecosystem may be related to forest patch size. The study indicates that the differences in successional trajectory with forest patch size can impart significant influence on soil N transformations in fragmented, aggrading woodlands.