A multi-temporal image analysis of habitat modification in the Coastal Watershed, NH

Habitat modification has become a progressively important concern as human populations increase and urbanization continues to replace natural environments with anthropogenic landscapes. Habitat modification concerns both the loss and fragmentation of environments, and these actions can have profound effects on ecosystem function, including increasing the potential of invasion by exotic species in vulnerable landscapes. The Coastal Watershed of New Hampshire (NH) has seen a 52% growth in population over the last 30 years which has led to marked urbanization and land use change. However, little has been done to study current land cover types, levels of fragmentation, and how fragmentation might be affecting the spread of woody invasive species. This research investigated new ways of using remote sensing techniques, such as object-based image analysis (OBIA) and multi-temporal image analysis, to create accurate land cover maps and corresponding fragmentation metrics. These products were then used to determine if habitats of interest in the Coastal Watershed were potentially more susceptible to invasion by woody invasive species. To map the Coastal Watershed, new sampling protocols were designed and implemented for labeling forest types on Landsat 5 Thematic Mapper (TM) imagery. In classification, an OBIA approach, coupled with the multi-temporal analysis, performed better than creating maps using a single Landsat 5TM image. A new fragmentation program, PolyFrag was also created to compute fragmentation metrics from the vector land cover maps generated by the OBIA approach. Finally, The Nature Conservancy (TNC) woody invasive species data were used along with the PolyFrag fragmentation maps to create a predicted probability map of the presence of woody invasive species. When compared to other programs, PolyFrag performed equally well to the more prevalent FRAGSTATS program in creating a predictive model from fragmentation metrics. However, the advantage of PolyFrag over FRAGSTATS is that it creates a fragmentation map in addition to the patch, class, and landscape metrics. Interestingly, both predictive models indicated that woody invasive species were less likely to be found in deciduous forests than in either coniferous or mixed forests. The maps and methods designed in this research are useful for fragmentation and invasive species management

Regional Invasive Species & Climate Change Management Challenge: Forest Pest Risk is Heating Up

Insect pests and pathogens, and climate change, each threaten forest health. But what happens when the two are combined? Climate change brings pests to new areas, makes pests more damaging, reduces trees’ defenses to pests, and can alter how forests recover after pest disturbance. Strategies for managing the combined impacts of forest pests and climate change include preventing new pest introductions, resisting pest spread by treating individual trees and diversifying forest stands, promoting more resilient forests that can rebound from pests, and helping forests transition to a state better adapted to our future climate

Regional Invasive Species & Climate Change Management Challenge: Embracing the Future. Promoting adaptation and resilience to invasive species and climate change

Climate change and invasive species can interact to increase disturbances and magnify changes in ecosystem form and function (Double Trouble). Increasing resilience is one of several management approaches for enabling healthy ecosystems to persist despite these changes. While resilience can be complicated and take many forms, it can generally be thought of as the “ability [of an ecosystem] to experience disturbances or environmental change without changing to a fundamentally different state” [Holling, 1973]. The accumulating effects of climate change, invasive species, or interacting effects of multiple disturbances can push an ecosystem past a tipping point and into a new ecological state. These alternative states are characterized by a different suite of species or functions, which are difficult or impossible to recover from (e.g. a shift from a closed-canopy to an open-canopy forested wetland). Actions to increase resilience help an ecosystem to maintain or return to its fundamental structure or function after a disturbance. Resilience falls in the middle of a spectrum of management goals ranging from preventing change (resistance) to promoting change (transformation) in the species composition, structure, or functions provided by an ecosystem. Clear management goals (See Table) and an understanding of the range of disturbances affecting focal ecosystems are necessary for deciding between managing for resistance, resilience, or transformation and what actions are required for successful management outcomes

Regional Invasive Species & Climate Change Management Challenge: Taking Action. Managing invasive species in the context of climate change

Climate change is likely to alter the timing and effect of invasive species management, as well as the suite of species we are managing. Despite concern about the effects of climate change, lack of information about how and when to take action is a barrier to climate-smart invasive species management. Here, we outline strategies for incorporating climate change into management along with examples of tools that can inform proactive decision-making

PolyFrag: a vector-based program for computing landscape metrics

Landscape fragmentation is important in investigating changing biodiversity patterns. Several current software programs calculate landscape fragmentation metrics. The most prevalent of these programs are only compatible with raster-format land cover maps. However, with advancing classification techniques, vector-format maps are becoming more popular. The new program PolyFrag computes fragmentation metrics for vector-based maps, is flexible and comprehensive, and outputs metrics similar to those of the widely used raster-based programs, like FRAGSTATS. PolyFrag is written in Python, used as a tool in ArcGIS, and allows for several fragmented and fragmenter land cover classes, as well as different edge widths between interacting classes

A comparison of landscape fragmentation analysis programs for identifying possible invasive plant species locations in forest edge

Context: When predicting locations of invasive plant species, mapping habitat fragmentation can be an important part of the prediction process. There are many different fragmentation mapping programs, each computing a unique set of fragmentation metrics that can be used in modeling probabilities of invasive species presence. Objectives: In this study, we compare the results from five freely available fragmentation programs: FRAGSTATS; the Landscape Fragmentation Tool; Shape Metrics; Patch Analyst; and PolyFrag. We compare these programs quantitatively on their ability to predict invasive plant presence and qualitatively for ease of use. Methods: The programs were compared using invasive plant inventories completed by The Nature Conservancy on parcels within the Coastal Watershed in New Hampshire, USA. Known locations of invasive plants, pseudo-absence locations, and metrics derived from each of the fragmentation programs were used to create maps of predicted presence for the parcels. The maps were compared and assessed for accuracy. Results: FRAGSTATS and PolyFrag created prediction maps with the highest accuracies and were relatively easy to use. The other programs had lower accuracies or were more difficult to implement. Both FRAGSTATS and PolyFrag compute similar fragmentation metrics and the models found similar metrics significant in predicting presence. Both programs predicted that invasive plants were less likely to be found in deciduous forests than in either mixed or coniferous forests. Conclusions: At the parcel level, some fragmentation programs result in metrics with more predictive power. Based on this analysis, we recommend FRAGSTATS for use with raster datasets and PolyFrag for vector datasets

Investigating Issues in Map Accuracy When Using an Object-Based Approach to Map Benthic Habitats

In a recent study, benthic habitat maps were created of the Texas Gulf Coast from digital aerial imagery. The images were classified using an object-based image analysis (OBIA) approach and a classification and regression tree (CART) technique. The map was manually edited, changing 26% of the polygons\u27 labels. Accuracy assessments of the unedited map and the edited map revealed the two were not significantly different. The research in this paper evaluates why these maps may have similar accuracies. Our analyses indicate that the small segmentation scale parameter used over-segmented the imagery, reducing the effectiveness of the CART technique and editing

Applicability of multi-date land cover mapping using Landsat 5 TM imagery in the Northeastern US

In many situations, multi-date image classification improves classification accuracies. However, with improved accuracies comes increased image processing time and effort. This work investigates the circumstances under which multi-date image classification is significantly better than single-date classification using Landsat-5 TM imagery for southeastern New Hampshire. Multiple Landsat images were processed for every three years from 1986 to 2010 and classified using an object-based image analysis approach (OBIA) with a classification and regression tree (CART) technique. Two maps were created for each of the mapping years, one using a single image, and another using multiple images from that year. The multi-date classification process generally performed better than the single-date process. However, the significance of the improvement was primarily dependent on the accuracy of the single-date map. Therefore, if the accuracy of the singledate classification is acceptable, it may not be necessary to perform the multi-date classification