[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-1-en-105":3,"doc-detail-244464-en":53,"doc-seo-244464-105":75},{"code":4,"msg":5,"data":6},0,"success",[7,14,19,24,29,34,39,44,49],{"id":8,"doc_module":9,"doc_module_name":10,"category_name":11,"show_sort_weight":12,"slug":13},11,1,"Template","Presentations",90,"presentations",{"id":15,"doc_module":9,"doc_module_name":10,"category_name":16,"show_sort_weight":17,"slug":18},12,"Resumes",80,"resumes",{"id":20,"doc_module":9,"doc_module_name":10,"category_name":21,"show_sort_weight":22,"slug":23},14,"Invoices",70,"invoices",{"id":25,"doc_module":9,"doc_module_name":10,"category_name":26,"show_sort_weight":27,"slug":28},15,"Posters",60,"posters",{"id":30,"doc_module":9,"doc_module_name":10,"category_name":31,"show_sort_weight":32,"slug":33},16,"Social Media",50,"social-media",{"id":35,"doc_module":9,"doc_module_name":10,"category_name":36,"show_sort_weight":37,"slug":38},17,"Forms",40,"forms",{"id":40,"doc_module":9,"doc_module_name":10,"category_name":41,"show_sort_weight":42,"slug":43},18,"Letters",30,"letters",{"id":45,"doc_module":9,"doc_module_name":10,"category_name":46,"show_sort_weight":47,"slug":48},21,"Paper Templates",5,"papers-templates",{"id":50,"doc_module":9,"doc_module_name":10,"category_name":51,"show_sort_weight":4,"slug":52},158,"General","general-158",{"code":4,"msg":5,"data":54},{"doc_id":55,"user_id":56,"nickname":57,"user_avatar":58,"doc_module":9,"category_id":50,"category_name":51,"doc_title":59,"doc_description":60,"doc_content":61,"file_id":62,"file_url":63,"file_type":64,"file_size":65,"view_count":66,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":67,"language":68,"language_code":69,"site_id":70,"html_lang":69,"table_of_contents":71,"faqs":72,"seo_title":73,"seo_description":60,"update_tm":74,"read_time":66},244464,2336478945519,"Franzy","https://ap-avatar.wpscdn.com/davatar_085a072bc5b1113ac321206ff7593b45","Designing Sustainable Landscapes - Stressor metrics for habitat loss, mowing and plowing, microclimate alterations, edge predators, domestic predators, invasive plants, and invasive earthworms metrics","A suite of stressor metrics evaluates how roads and development affect ecological integrity within the Designing Sustainable Landscapes (DSL) project. The metrics use a shared logistic kernel-weighted algorithm with metric-specific parameters, producing values from 0 (no effect) to 1 (severe effect). They quantify habitat loss, mowing and plowing, microclimate alterations, edge and domestic predator impacts, and non-native invasive plants and invasive earthworms. The index of ecological integrity (IEI) integrates 21 stressor and resiliency metrics across the northeast.","Designing Sustainable Landscapes:  \nHabitat loss, mowing and plowing, microclimate alterations, edge predators, domestic predators, invasive plants, and invasive earthworms metrics  \nA project of the University of Massachusetts Landscape Ecology Lab  \nPrincipals:  \n• Kevin McGarigal, Professor  \n• Brad Compton, Research Associate  \n• Ethan Plunkett, Research Associate  \n• Bill DeLuca, Research Associate  \n• Joanna Grand, Research Associate  \nWith support from:  \n• North Atlantic Landscape Conservation Cooperative (US Fish and Wildlife Service, Northeast Region)  \n• Northeast Climate Science Center (USGS)  \n• University of Massachusetts, Amherst  \nReference:  \nMcGarigalK, Compton BW, Plunkett EB, DeLuca WV, and Grand J.2018.Designing sustainable landscapes: habitat loss, mowing and plowing, microclimate alterations, edge predators, domestic predators, invasive plants, and invasive earthworms metrics.Report to the North Atlantic Conservation Cooperative, US Fish and Wildlife Service, Northeast Region.  \nGeneral description  \nThis document describes a suite of stressor metrics that assess different aspects of the effects of roads and development on ecologicalintegrity (see technical document on integrity, McGarigaletal 2017).They share a common algorithm, but each has unique parameters.These metrics are obviously highly correlated (Fig. 1), but each assesses a different aspect of the effects of roads and development on ecological integrity.  \nThese metrics are elements of the ecological integrity analysis of the Designing Sustainable Landscapes (DSL) project (McGarigaletal 2017).Consisting of a composite of 21 stressor and resiliency metrics, the index of ecological integrity (IEI) assesses the relative intactness and resiliency to environmental change of ecological systems throughout the northeast. These stressor metrics range from 0 (no effect) to 1 (severe effect).See Table 1 for parameters for each metric.  \nHabitat loss (Fig. 1b).Assesses the intensity of past habitat loss caused by all forms of development.Direct habitat loss is the primary cause of species decline and extinction; this metric is an index of indirect habitat loss—the decline of integrity in remaining natural lands due to the loss of former habitat in the neighborhood to past development.  \nMowing and plowing (Fig. 1c).Assess the intensity of agriculture in the neighborhood as a surrogate for mowing and plowing rates,which are direct sources of animal mortality. Agricultural machinery is a well-known cause of mortality for grassland bird nestlings and terrestrial and semi-aquatic turtles.  \nMicroclimate alterations (Fig. 1d).Assesses microclimatic alterations due to edge effects, such decreased moisture, higher wind,and more extreme temperatures.This metric includes the effects of both anthropogenic edges and natural edges (e.g., the effects of an open marsh on the surrounding forest).  \nEdge predators (Fig. 1e).Assesses the effect of human commensal mesopredators such as raccoons and skunks.Mesopredators often reach unusually high densities near human habitation, both due to food subsidies (garbage, bird feeders, and livestock grain) and mesopredator release.  \nDomestic predators (Fig. 1f).Assesses the effect of domestic predators (primarily housecats) due to development.Both pet and feral housecats kill large numbers of birds and small mammals.  \nInvasive plants (Fig. 1g).Assesses the effect of non-native invasive plants.Invasive plants often spread from sources in residential and agricultural areas, from humandisturbed areas, and along roads.  \nInvasive earthworms (Fig. 1h).Assesses the effect of non-native invasive earthworms. In the glaciated northeast, all terrestrial earthworms are non-native.Spreading from agricultural areas, home gardens, and fishing holes, they speed up the nutrient cycle in nearby forests, often greatly affecting understory plants and seedling regeneration.  \nUse and interpretation of these layers  \nThese metrics rely on several as","cbCaiqF4tYpIhmRl","https://ap.wps.com/l/cbCaiqF4tYpIhmRl","pdf",452505,2,6,"English","en",105,"# General description\n## Stressor metrics and ecological integrity\n## Habitat loss\n## Mowing and plowing\n## Microclimate alterations\n## Edge predators and domestic predators\n## Invasive plants and invasive earthworms\n# Use, interpretation, and derivation\n## Use and interpretation of these layers\n## Derivation of these layers\n## Data sources\n## Algorithm\n## GIS metadata\n## Figures and metric examples","[{\"question\":\"What do these stressor metrics measure in the DSL project?\",\"answer\":\"They assess different aspects of how roads and development affect ecological integrity across the northeast. Each metric targets a distinct stressor process while sharing a common algorithmic basis.\"},{\"question\":\"Why do the metrics range from 0 to 1?\",\"answer\":\"The layers are scaled so values represent the intensity of stress in the neighborhood, with 0 indicating no effect and 1 indicating severe effect. This scaling is consistent across the suite (theoretically up to 1).\"},{\"question\":\"What data and method are used to derive the metric layers?\",\"answer\":\"All metrics are based on mapped ecological systems in the DSLland ecological systems map. A logistic kernel-weighted sum uses landcover-class weights within the neighborhood of each focal cell, producing continuous geoTIFF rasters.\"}]","Designing Sustainable Landscapes - Stressor metrics for habitat loss, mowing and plowing, microclimate alterations, edge predators, domestic predators, invasive plants, and invasive earthworms metrics | PDF",1789217490,{"code":4,"msg":76,"data":77},"ok",{"site_id":70,"language":69,"slug":78,"title":59,"keywords":79,"description":60,"schema_data":80,"social_meta":135,"head_meta":137,"extra_data":139,"updated_unix":140},"designing-sustainable-landscapes-stressor-metrics-for-habitat-loss-mowing-and-plowing-microclimate-alterations-edge-predators-domestic-predators-invasive-plants-and-invasive-earthworms-metrics","",{"@graph":81,"@context":134},[82,97,117],{"@type":83,"itemListElement":84},"BreadcrumbList",[85,89,91,94],{"item":86,"name":87,"@type":88,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":90,"name":10,"@type":88,"position":66},"https://docshare.wps.com/template/",{"item":92,"name":51,"@type":88,"position":93},"https://docshare.wps.com/template/general/",3,{"item":95,"name":59,"@type":88,"position":96},"https://docshare.wps.com/template/designing-sustainable-landscapes-stressor-metrics-for-habitat-loss-mowing-and-plowing-microclimate-alterations-edge-predators-domestic-predators-invasive-plants-and-invasive-earthworms-metrics/244464/",4,{"url":95,"name":59,"@type":98,"image":99,"author":104,"headline":59,"publisher":106,"fileFormat":109,"inLanguage":69,"description":60,"dateModified":110,"datePublished":111,"encodingFormat":109,"isAccessibleForFree":112,"interactionStatistic":113},"DigitalDocument",{"url":100,"@type":101,"width":102,"height":103},"https://docshare.wps.com/thumbnails/designing-sustainable-landscapes-stressor-metrics-for-habitat-loss-mowing-and-plowing-microclimate-alterations-edge-predators-domestic-predators-invasive-plants-and-invasive-earthworms-metrics/244464.png","ImageObject",442,249,{"name":57,"@type":105},"Person",{"url":86,"name":107,"@type":108},"DocShare","Organization","application/pdf","2026-09-21","2026-09-12",true,{"@type":114,"interactionType":115,"userInteractionCount":66},"InteractionCounter",{"@type":116},"ViewAction",{"@type":118,"mainEntity":119},"FAQPage",[120,126,130],{"name":121,"@type":122,"acceptedAnswer":123},"What do these stressor metrics measure in the DSL project?","Question",{"text":124,"@type":125},"They assess different aspects of how roads and development affect ecological integrity across the northeast. Each metric targets a distinct stressor process while sharing a common algorithmic basis.","Answer",{"name":127,"@type":122,"acceptedAnswer":128},"Why do the metrics range from 0 to 1?",{"text":129,"@type":125},"The layers are scaled so values represent the intensity of stress in the neighborhood, with 0 indicating no effect and 1 indicating severe effect. This scaling is consistent across the suite (theoretically up to 1).",{"name":131,"@type":122,"acceptedAnswer":132},"What data and method are used to derive the metric layers?",{"text":133,"@type":125},"All metrics are based on mapped ecological systems in the DSLland ecological systems map. A logistic kernel-weighted sum uses landcover-class weights within the neighborhood of each focal cell, producing continuous geoTIFF rasters.","https://schema.org",{"og:url":95,"og:type":136,"og:title":59,"og:site_name":107,"og:description":60},"article",{"robots":138,"canonical":95},"index,follow",{"doc_id":55,"site_id":70},1790028814]