The effects of spatial legacies following shifting management practices and fire on boreal forest age structure

Forest age structure and its spatial arrangement are important elements of sustainable forestry because of their effects on biodiversity and timber availability. Forest management objectives that include specific forest age structure may not be easily attained due to constraints imposed by the legacies of historical management and natural disturbance. We used a spatially explicit stochastic model to explore the synergetic effects of forest management and fire on boreal forest age structure. Specifically, we examined (1) the duration of spatial legacies of different management practices in the boreal forest, (2) how multiple shifts in management practices affect legacy duration and the spatial trajectories of forest age structure, and (3) how fire influences legacy duration and pattern development in combination with harvesting. Results based on 30 replicates of 500 years for each scenario indicate that (1) spatial legacies persist over 200 years and the rate at which legacies are overcome depends on whether new management targets are in synchrony with existing spatial pattern; (2) age specific goals were met faster after multiple management shifts due to the similar spatial scale of the preceding management types; (3) because large fires can erase the spatial pattern created by smaller disturbances, scenarios with fire had shorter lags than scenarios without fire. These results suggest that forest management goals can be accelerated by applying management at a similar spatial scale as existing spatial patterns. Also, management planning should include careful consideration of historical management as well as current and likely future disturbances

Categorical maps, comparisons, and confidence

Categorical maps, Map comparison, Accuracy assessment, Change detection, Stochastic processes, Spatial pattern, Inference,

Local configuration measures for categorical spatial data: binary regular lattices

Categorical spatial data, Local spatial statistics, Configuration measures, C0, C15, C49,

Integrating Landscape Ecology and Geoinformatics to Decipher Landscape Dynamics for Regional Planning

We used remote sensing and GIS in conjunction with multivariate statistical methods to: (i) quantify landscape composition (land cover types) and configuration (patch density, diversity, fractal dimension, contagion) for five coastal watersheds of Kalloni gulf, Lesvos Island, Greece, in 1945, 1960, 1971, 1990 and 2002/2003, (ii) evaluate the relative importance of physical (slope, geologic substrate, stream order) and human (road network, population density) variables on landscape composition and configuration, and (iii) characterize processes that led to land cover changes through land cover transitions between these five successive periods in time. Distributions of land cover types did not differ among the five time periods at the five watersheds studied because the largest cumulative changes between 1945 and 2002/2003 did not take place at dominant land cover types. Landscape composition related primarily to the physical attributes of the landscape. Nevertheless, increase in population density and the road network were found to increase heterogeneity of the landscape mosaic (patchiness), complexity of patch shape (fractal dimension), and patch disaggregation (contagion). Increase in road network was also found to increase landscape diversity due to the creation of new patches. The main processes involved in land cover changes were plough-land abandonment and ecological succession. Landscape dynamics during the last 50 years corroborate the ecotouristic-agrotouristic model for regional development to reverse trends in agricultural land abandonment and human population decline and when combined with hypothetical regulatory approaches could predict how this landscape could develop in the future, thus, providing a valuable tool to regional planning

Are landscape ecologists addressing uncertainty in their remote sensing data

In this quantitative review, we investigate the degree to which landscape ecology studies that use spatial data address spatial uncertainty when conducting analyses. We identify three broad categories of spatial uncertainty that are important in determining the characterisation of landscape pattern and affect the outcome of analysis in landscape ecology: (i) classification scheme uncertainty, (ii) spatial scale and (iii) classification error. The second category, spatial scale, was further subdivided into five scale dependent factors (i) pixel size, (ii) minimum mappable unit, (iii) smoothing, (iv) thematic resolution and (v) extent. We reviewed all articles published in the journal Landscape ecology in 2007 and recorded how spatial data was used and whether spatial uncertainty was addressed or reported in ecological analyses. This review found that spatial uncertainty was rarely addressed and/or reported