Forest landscape ecology and global change: an introduction

Forest landscape ecology examines broad-scale patterns and processes and their interactions in forested systems and informs the management of these ecosystems. Beyond being among the richest and the most complex terrestrial systems, forest landscapes serve society by providing an array of products and services and, if managed properly, can do so sustainably. In this chapter, we provide an overview of the field of forest landscape ecology, including major historical and present topics of research, approaches, scales, and applications, particularly those concerning edges, fragmentation, connectivity, disturbance, and biodiversity. In addition, we discuss causes of change in forest landscapes, particularly land-use and management changes, and the expected structural and functional consequences that may result from these drivers. This chapter is intended to set the context and provide an overview for the remainder of the book and poses a broad set of questions related to forest landscape ecology and global change that need answers

Representative Landscapes in the Forested Area of Canada

Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada’s land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative—or “exemplar”—from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada’s ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada’s forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach

Evaluation of potential habitat with an integrated analysis of a spatial conservation strategy for David’s deer, Elaphurus davidians

How to assess the potential habitat integrating landscape dynamics and population research, and how to reintroduce animals to potential habitats in environments highly human disturbed are still questions to be answered in conservation biology. According to behavioral research on Elaphurus davidians, we have developed a suitability index and a risk index to evaluate the potential habitats for the deer. With these indices, we conducted two transect assessments to evaluate the gradient change of the target region. Then, taking rivers as border lines, we tabulated the forest areas, high grassland area and total area and then compared the forest and high grassland area in each subregion. Furthermore, we computed the land use transfer matrix for the whole Yancheng coast during 1987–2000. We also computed human modified index (HMI) in six subregions. Lastly with a geographical information system support we obtained the spatial distribution of the indices and evaluation of the whole potential habitats from a neighborhood analysis. The transect assessment showed that the suitability of the coastal area was higher than that of the inland area for the deer, while the southern area was higher than the northern. Landscape metrics and HMI analysis showed that different landscape patterns and different anthropogenic disturbance existed within the region, and the increasing human disturbance was the key factor causing the pattern dynamics. The evaluation of potential habitats showed that there was an estimated carrying capacity of no more than 10,000 for David’s deer reintroduction into the natural area. Also the reintroduction strategy was discussed. This integrated approach linked the population research and the landscape metrics, and the dataset with different scale; thus, it is an approach likely to be useful for the protection of other large animal in a landscape highly disturbed by humans

Forest Insect Defoliation and Carbon Dynamics: Simulating Multiple Defoliator Species in Shared Landscapes With Landis-II

Defoliation outbreaks are dynamic forest disturbances with unique spatial and temporal characteristics that produce distinct changes in forest composition and carbon balance. We simulated defoliation outbreaks using a new module for the forest disturbance and succession model, Landis-II, to better understand the long-term consequences of defoliation on forest carbon. This new module recreates the spatial dynamics of defoliation outbreaks by stochastically drawing parameters that describe spatial pattern from empirical distributions derived from Landsat defoliation maps. The module also captures species specific growth and mortality responses to accumulated defoliation stress. We demonstrate how these simulated defoliation events mimic spatial and temporal patterns of gypsy moth (GM, Lymantria dispar L.) defoliation outbreaks and their effects in the central Appalachian mountains of western Maryland, U.S.A. We simulated aboveground carbon dynamics over 400 years with and without GM defoliation in this mixed deciduous landscape. These simulations facilitated estimation of (1) the impacts of a generalist defoliator on long-term changes in forest composition and carbon storage, and (2) comparison of aboveground carbon dynamics expected in the absence of GM with those following introduction. Simulations were also run with forest tent caterpillar (Malacosoma disstria Hbn.) defoliation, individually and with GM, to examine how multiple defoliators with shared hosts alter long-term aboveground carbon dynamics. Preliminary results show that the introduction of GM disturbance changes the trajectory of forest species composition, facilitating increases in non-host species that would not otherwise occur. Forest carbon storage is temporarily reduced following individual outbreaks, as are long-term means, once GM enters the landscape. Changes in forest carbon storage are even more pronounced when a native defoliator has periodic outbreaks in the same landscape. The results directly illustrate how temperate forest carbon cycles, particularly aboveground carbon pools, are affected by interacting insect disturbances that are a fundamental, but changing part of forest ecosystems

Analysis of Waveform Lidar Data Using Shape-based Metrics

Models that use large-footprint waveform light detection and ranging (lidar) to estimate forest height, structure, and biomass have typically used either point data extracted from the waveforms or cumulative distributions of the waveform energy, disregarding potential information latent within the waveform shape. Shape-based metrics such as the centroid and the radius of gyration can capture features missed by height-based metrics that are likely related to forest structure and biomass. Noise analyses demonstrated the relative insensitivity of and , supporting the hypothesis that these metrics could be used to identify similar shapes within noisy waveforms [such as the Laser Vegetation Imaging Sensor (LVIS) and Geoscience Laser Altimeter Sensor (GLAS)] or to discriminate among waveforms with different underlying shapes. These findings suggest that and can be successfully used in future lidar studies of forest structure and that further research should be conducted to develop additional shape-based metrics, as well as to investigate the relationship between forest structure and lidar waveform shape