Peter T. Wolter

Mapping submergent aquatic vegetation in the US Great Lakes using Quickbird satellite data

Submergent aquatic vegetation (SAV) is a powerful indicator of environmental conditions in both marine and fresh water ecosystems. Quickbird imagery was used to map SAV at three sites across the Great Lakes. Unsupervised classifications were performed at each site using summer Quickbird sensor data. At one site, a multi‐temporal classification approach was added, combining visible red difference (May–August) with August red and green visible band data. Multi‐temporal SAV classification was superior to single‐date results at this site. Muck bottom was not seriously confused with SAV, which was unexpected. Multi‐temporal classification results showed less confusion between deep water and SAV, although spectral variability due to sub‐surface sandbar structure was a source of error in both single‐ and multi‐date classifications. Nevertheless, some of the confounding effects of water column on SAV classification appear to have been mitigated using this multi‐temporal approach. Future efforts would be well served by incorporating detailed, continuous, bathymetry data in the classification process. Quickbird sensor data are very useful for classifying SAV under US Great Lakes conditions. However, regional classification efforts using these data may be impractical at this time, as high cost, rigid tasking parameters and unpredictable water conditions limit availability of suitable imagery.

Land Use Land Cover Change in the U.S. Great Lakes Basin 1992 to 2001

ABSTRACT The pace of Land Use/Land Cover (LULC) change in the Great Lakes, particularly in urban and suburban areas, far exceeds that predicted by population growth alone. Thus, quantification of LULC and change through time may be a key factor in understanding the near-shore ecology of this system. The work described in this paper is part of a larger effort called the Great Lakes Environmental Indicators Project (GLEI), whose goal was to develop and refine environmental state indicators for the U.S. near-shore zone of the Great Lakes. Here we describe methodologies for using existing Landsat-based LULC maps to assemble consistent LULC data for the U.S. portion of the Great Lakes basin for 1992 and 2001, as well as summarizing salient LULC results. Between 1992 and 2001, 2.5% (798,755 ha) of the U.S. portion of the Great Lakes watershed experienced change. Transitions due to new construction included a 33.5% (158,858 ha) increase in low-intensity development and a 7.5% (140,240 ha) increase in road area. Agricultural and forest land each experienced ∼2.3% (259,244 ha and 322,463 ha, respectively) decrease in area. Despite the large and enduring agricultural losses observed (2.23% of 1992 agricultural area), the rate of agricultural land decrease between 1992 and 2001 was less than that reported by the EPA (−9.8%) for the previous ∼10-year period. Areas of new development were largely concentrated near coastal areas of the Great Lakes. Over 38% (6,014 ha) of wetland losses to development between 1992 and 2001 occurred within 10 km of a coastal area, and most of that area was within the nearest 1 kilometer. Clearly, these land use change data will be especially useful as quantifiable indicators of landscape change over time and aid in future land use planning decisions for protection of the integrity of the Great Lakes ecosystem.

Two-dimensional wavelet analysis of spruce budworm host basal area in the Border Lakes landscape

Increases in the extent and severity of spruce budworm (Choristoneura fumiferana Clem.) outbreaks over the last century are thought to be the result of changes in forest structure due to forest management. A corollary of this hypothesis is that manipulations of forest structure and composition can be used to reduce future forest vulnerability. However, to what extent historical forest management has influenced current spatial patterns of spruce budworm host species is unknown. To identify landscape-scale spatial legacies of forest management in patterns of spruce budworm host species (i.e., Abies balsamea and Picea spp.), we analyzed remotely sensed forest data from the Border Lakes landscape of northern Minnesota and northwestern Ontario. Our study area contains three regions with different management histories: (1) fine-scale logging patterns in Minnesota, (2) coarse-scale logging patterns in Ontario, and (3) very limited logging history in the Boundary Waters Canoe Area and adjacent Quetico Provincial Park. We analyzed forest basal-area data using wavelets and null models to identify: (1) at which scales forest basal area is structured, (2) where those scales of pattern are significantly present, and (3) whether regions of local significance correspond to regional boundaries that separate the study area. Results indicate that spatial patterns in host basal area are created by nonstationary processes and that these processes are further constrained by lakes and wetlands. Wavelet analysis combined with significance testing revealed a bimodal distribution of scale-specific wavelet variance and separate zones of host species basal area that partially correspond with regional boundaries, particularly between Minnesota and the Wilderness region. This research represents one of the first comparisons of forest spatial structure in this region across an international border and presents a novel method of two-dimensional wavelet analysis that can be used to identify significant scale-specific structure in spatial data.

Sixty-three Years of Land Alteration in Erie Township

ABSTRACT Land use and land cover (LULC) was mapped using historical aerial photos (1940) and contemporary QuickBird satellite imagery (2003) for a 100 km2 area covering portions of Erie Township, Michigan, and Toledo, Ohio on the western end of Lake Erie. This area serves as a microcosm of conditions elsewhere on the Great Lakes coast, containing a range of human-altered to natural landscapes. Geographic information system analysis was used to measure LULC change within the study area based on the 1940 and 2003 maps, and to illustrate the use of historical aerial photos and data to quantify changes in anthropogenic pressures to coastal ecosystems. Agriculture was and is the main land use in the study site, constituting 78% and 55% of upland area in 1940 and 2003, respectively. Most conversions to other land uses originated as agricultural lands. Transportation changes over the time period included the loss of two major railroad yards and the gain of an interstate highway. The area of commercial and industrial development increased 12-fold, from 20 ha in 1940 to 246 ha by 2003. Major industries built after 1940 included an electrical power plant and a sanitary landfill. Residential development approximately doubled from 353 ha in 1940 to 717 ha in 2003, consistent with an 80% increase in population. Coastal ecosystems within the study area included a coastal spit (Woodtick Peninsula) and a large, partially-diked wetland behind it (Erie Marsh), both of which changed extensively over the time period studied. This approach offers a means of incorporating long-term observations into the evaluation of environmental condition in coastal wetlands.

Emissions of forest floor and mineral soil carbon, nitrogen and mercury pools and relationships with fire severity for the Pagami Creek Fire in the Boreal Forest of northern Minnesota

Forest fires cause large emissions of C (carbon), N (nitrogen) and Hg (mercury) to the atmosphere and thus have important implications for global warming (e.g. via CO2 and N2O emissions), anthropogenic fertilisation of natural ecosystems (e.g. via N deposition), and bioaccumulation of harmful metals in aquatic and terrestrial systems (e.g. via Hg deposition). Research indicates that fires are becoming more severe over much of North America, thus increasing element emissions during fire. However, there has been little research relating forest floor and mineral soil losses of C, N and Hg to on-the-ground indices of fire severity that enable scaling up those losses for larger-scale accounting of fire-level emissions. We investigated the relationships between forest floor and mineral soil elemental pools across a range of soil-level fire severities following the 2011 Pagami Creek wildfire in northern Minnesota, USA. We were able to statistically differentiate losses of forest floor C, N and Hg among a five-class soil-level fire severity classification system. Regression relationships using soil fire severity class were able to predict remaining forest floor C, N and Hg pools with 82–96% confidence. We correlated National Aeronautics and Space Administration Airborne Visible and Infrared Imaging Spectrometer-Classic imagery to ground-based plot-scale estimates of soil fire severity to upscale emissions of C, N and Hg to the fire level. We estimate that 468 000 Mg C, 11 000 Mg of N and over 122 g of Hg were emitted from the forest floor during the burning of the 28 310 ha upland area of the Pagami Creek fire.

Landscape host abundance and configuration regulate periodic outbreak behavior in spruce budworm (Choristoneura fumiferana Clem.)

Landscape‐level forest management has long been hypothesized to affect forest insect outbreak dynamics, but empirical evidence remains elusive. We hypothesized that the combination of increased hardwood relative to host tree species, prevalence of younger forests, and fragmentation of those forests due to forest harvesting legacies would reduce outbreak intensity, increase outbreak frequency, and decrease spatial synchrony in spruce budworm Choristoneura fumiferana outbreaks. We investigated these hypotheses using tree ring samples collected across 51 sites pooled into 16 subareas distributed across a large ecoregion spanning the international border between Ontario (Canada), and Minnesota (USA). This ecoregion contains contrasting land management zones with clear differences in forest landscape structure (i.e. forest composition and spatial configuration) while minimizing the confounding influence of climate. Cluster analyses of the 76‐yr time‐series generally grouped by subareas found within the same land management zone. Spatial nonparametric covariance analysis indicated that the highest and lowest degree of spatial synchrony of spruce budworm outbreaks were found within unmanaged wilderness and lands managed at fine spatial scales in Minnesota, respectively. Using multivariate analysis, we also found that forest composition, configuration, and climate together accounted for a total of 40% of the variance in outbreak chronologies, with a high level of shared variance between composition and configuration (13%) and between composition and climate (9%). At the scale of our study, climate on its own did not explain any of the spatial variation in outbreaks. Outbreaks were of higher frequency, lower intensity, and less spatially synchronized in more fragmented, younger forests with a lower proportion of host species, with opposing outbreak characteristics observed in regions characterised by older forests with more concentrated host species. Our study is the first quantitative evaluation of the long‐standing ‘silvicultural hypothesis’ of spruce budworm management specifically conducted at a spatio‐temporal scale for which it was intended.

Land Use Change and Policy in Iowa’s Loess Hills

Land use changes have important implications on ecosystems and society. Detailed identification of the nature of land use changes in any local region is critical for policy design. In this paper, we quantify land use change in Iowa’s Loess Hills ecoregion, which contains much of the state’s remaining prairie grasslands. We employ two distinct panel datasets, the National Resource Inventory data and multi-year Cropland Data Layers, that allow us to characterize spatially-explicit land use change in the region over the period 1982-2010. We analyze land use trends, land use transitions and crop rotations within the ecoregion, and contrast these with county and state-level changes. To better comprehend the underlying land use changes, we evaluate our land use characterizing metrics conditional on soil quality variables such as slope and erodibility. We also consider the role of contemporary agricultural policy and commodity markets to seek explanations for land use changes during the period of our study. Although crop production has expanded on the Loess Hills landform since 2005, much of the expansion in corn acres has been from reduced soybean acreage. We find that out of the total 258 km2 increase in corn acreage during 2005-’10, about 100 km2 transitioned from soybeans. Data also indicate intensifying monoculture with higher percentage of corn plantings for two to four consecutive years during 2000-’10. In addition, crop production is found to have moved away from more heavily sloped land. Cropping does not appear to have increased on lands with higher crop productivity.

Quantifying Early-Seral Forest Composition with Remote Sensing

Abstract Spatially explicit modeling of recovering forest structure within two years following wildfire disturbance has not been attempted, yet such knowledge is critical for determining successional pathways. We used remote sensing and field data, along with digital climate and terrain data, to model and map early-seral aspen structure and vegetation species richness following wildfire. Richness was the strongest model ( rmse = 2.47 species, Adj. R 2 = 0.60), followed by aspen stem diameter, basal area ( ba ), height, density, and percent cover (Adj. R 2 range = 0.22 to 0.53). Effects of pre-fire aspen ba and fire severity on post-fire aspen structure and richness were analyzed. Post-fire recovery attributes were not significantly related to fire severity, while all but percent cover and richness were sensitive to pre-fire aspen ba (Adj. R 2 range = 0.12 to 0.33, p

Satellite-Based Management Tool for Oak Savanna Ecosystem Restoration

Abstract The structure and function of oak Quercus spp. savanna ecosystems in the North American Midwest were originally maintained by an active disturbance regime (often fire). Subsequent reductions in the frequency of disturbance after European settlement have facilitated rapid, regional conversion of these ecosystems to more closed-canopy forest. Hence, regional-scale management strategies are now needed to restore critical spatial gradients of light, temperature, soil moisture, and soil organic matter for recovery and sustenance of the unique mosaic of understory grass and forb species assemblages that define oak savannas. Tree species composition, distribution, mortality, basal area, and canopy cover are important forest structural parameters that are intrinsically linked to oak savanna restoration ecology. In this benchmark study, we seek to determine whether Landsat-based monitoring protocols can be developed as a tool to guide and monitor regional-scale restoration and management efforts. Using th...

Tracking land cover change along the western edge of the U.S. Corn Belt from 1984 through 2016 using satellite sensor data: observed trends and contributing factors

ABSTRACT The Cropland Data Layers (CDL) are high-resolution geo-referenced data products made available by the U.S. Department of Agriculture. However, the CDL lacks in its ability to be employed as a tool to identify the impact of the gradually evolving drivers of land use change, e.g., climate change, due to its limited historical depth. We implement a robust, phenology-based satellite image classification algorithm to identify historical cropland allocation in eastern South Dakota and North Dakota predating the initial CDL by 13 and 22 years, respectively. Five major land covers, i.e., corn, soybeans, wheat, alfalfa and grass (including native grass, hay and pasture) are identified using archived Landsat-5 surface reflectance data, while achieving CDL-like accuracy. The long-term rate of grassland loss during 1985–2011 is found to be significantly lower (26,781 hectares or 1.5% annually) relative to the near-term rate of grassland loss during 2006-’11 (84,545 hectares or 5.2% annually). We find similar discrepancy in regional corn expansion rates. Our value-added raster data provide opportunities for improved identification of land use drivers, whereas relying solely on the CDL’s restricted historical extent may lead to biased land use change estimates and misguide policy.