Modelling ecosystem services in terrestrial systems

Over the past few decades, a multi-disciplinary research community has documented the goods and services provided by ecosystems in specific sites scattered across the world. This research community has now begun to focus on creating methods and tools for mapping and valuing the ecosystem services produced on any landscape in the world. We describe some of these methods and tools and how they calculate and express ecosystem service provision and value on landscapes. We also describe methods for predicting landscape change. These predictions can be used by multi-ecosystem service models to assess potential changes and trade-offs in ecosystem service provision and values into the future

Identifying the Opportunity Cost of Critical Habitat Designation under the U.S. Endangered Species Act

We determine the effect of the US Endangered Species Act’s Critical Habitat designation on land use change from 1992 to 2011. We find that the rate of change in developed land (constructed material) and agricultural land is not significantly affected by Critical Habitat designation. Therefore, Sections 7 and 9 of the Endangered Species Act do not appear to be more heavily applied in lands designated as Critical Habitat areas versus lands within listed species’ ranges, but without critical habitat designation. Further, there does not appear to be any extraordinary conservation activity in critical habitat areas; for example, environmental non-profits and land trusts do not appear to be concentrating activity in these areas. Before we conclude that the opportunity cost of Critical Habitat designation is negligible we need to examine the land management impacts of designation

An optical surface resonance may render photonic crystals ineffective

In this work we identify and study the presence of extremely intense surface resonances that frustrate the coupling of photons into a photonic crystal over crucial energy ranges. The practical utility of photonic crystals demands the capability to exchange photons with the external medium, therefore, it is essential to understand the cause of these surface resonances and a route to their elimination. We demonstrate that by modifying the surface geometry it is possible to tune the optical response or eliminate the resonances to enable full exploitation of the photonic crystal.Comment: 6 pages, 8 figures, submitted to PR

Where does stress happen? Ecological momentary assessment of daily stressors using a mobile phone app. [Journal article]

Despite the importance of daily stress to individuals' health and wellbeing, few studies have explored where stress happens in real time, that is, dynamic stress processes in different spaces. As such, stress interventions rarely account for the environment in which stress occurs. We used mobile phone based ecological momentary assessment (EMA) to collect daily stress data. Thirty-three participants utilized a mobile-phone-based EMA app to self-report stressors as they went about their daily lives. Geographic coordinates were automatically collected with each stress report. Data from thematic analysis of stressors by location (home, work, work from home, other) were used to determine whether certain stressors were more prevalent in certain environments. Nine daily stressors significantly differed by location. Work-related stress was reported more often at work. Pets, household chores, sleep, and media-related stressors were reported most at home. Physical illnesses, vehicle issues, and safety/security stressors occurred most often while participants were "working from home." Traffic-related stress was experienced more commonly in "other" environments. Other 18 stressors were generated regardless of location, suggesting that these stressors were persistent and without respect to location. Study findings expand the understanding of environments in which specific stressors occur, providing baseline data for potential targeted "just-in-time" stress interventions tailored to unique stressors in specific environments. We also provide findings related to the "work from home" phenomenon. Further work is needed to better understand the unique stressors among the large number of individuals who transitioned to working from home during and after the COVID-19 pandemic

Lidar sampling for large-area forest characterization: A review

The ability to use digital remotely sensed data for forest inventory is often limited by the nature of the measures, which, with the exception of multi-angular or stereo observations, are largely insensitive to vertically distributed attributes. As a result, empirical estimates are typically made to characterize attributes such as height, volume, or biomass, with known asymptotic relationships as signal saturation occurs. Lidar (light detection and ranging) has emerged as a robust means to collect and subsequently characterize vertically distributed attributes. Lidar has been established as an appropriate data source for forest inventory purposes; however, large area monitoring and mapping activities with lidar remain challenging due to the logistics, costs, and data volumes involved.The use of lidar as a sampling tool for large-area estimation may mitigate some or all of these problems. A number of factors drive, and are common to, the use of airborne profiling, airborne scanning, and spaceborne lidar systems as sampling tools for measuring and monitoring forest resources across areas that range in size from tens of thousands to millions of square kilometers. In this communication, we present the case for lidar sampling as a means to enable timely and robust large-area characterizations. We briefly outline the nature of different lidar systems and data, followed by the theoretical and statistical underpinnings for lidar sampling. Current applications are presented and the future potential of using lidar in an integrated sampling framework for large area ecosystem characterization and monitoring is presented. We also include recommendations regarding statistics, lidar sampling schemes, applications (including data integration and stratification), and subsequent information generation. © 2012

Modeling multiple ecosystem services, biodiversity conservation, commodity production, and tradeoffs at landscape scales

Nature provides a wide range of benefits to people. There is increasing consensus about the importance of incorporating these ecosystem services into resource management decisions, but quantifying the levels and values of these services has proven difficult. We use a spatially explicit modeling tool, Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), to predict changes in ecosystem services, biodiversity conservation, and commodity production levels. We apply InVEST to stakeholder-defined scenarios of land-use/land-cover change in the Willamette Basin, Oregon. We found that scenarios that received high scores for a variety of ecosystem services also had high scores for biodiversity, suggesting there is little tradeoff between biodiversity conservation and ecosystem services. Scenarios involving more development had higher commodity production values, but lower levels of biodiversity conservation and ecosystem services. However, including payments for carbon sequestration alleviates this tradeoff. Quantifying ecosystem services in a spatially explicit manner, and analyzing tradeoffs between them, can help to make natural resource decisions more effective, efficient, and defensible. © The Ecological Society of America

Projected land-use change impacts on ecosystem services in the United States

Providing food, timber, energy, housing, and other goods and services, while maintaining ecosystem functions and biodiversity that underpin their sustainable supply, is one of the great challenges of our time. Understanding the drivers of land-use change and how policies can alter land-use change will be critical to meeting this challenge. Here we project land-use change in the contiguous United States to 2051 under two plausible baseline trajectories of economic conditions to illustrate how differences in underlying market forces can have large impacts on land-use with cascading effects on ecosystem services and wildlife habitat. We project a large increase in croplands (28.2 million ha) under a scenario with high crop demand mirroring conditions starting in 2007, compared with a loss of cropland (11.2 million ha) mirroring conditions in the 1990s. Projected land-use changes result in increases in carbon storage, timber production, food production from increased yields, and \u3e10% decreases in habitat for 25% of modeled species. We also analyze policy alternatives designed to encourage forest cover and natural landscapes and reduce urban expansion. Although these policy scenarios modify baseline land-use patterns, they do not reverse powerful underlying trends. Policy interventions need to be aggressive to significantly alter underlying land-use change trends and shift the trajectory of ecosystem service provision

Agreement Between Experts and an Untrained Crowd for Identifying Dermoscopic Features Using a Gamified App: Reader Feasibility Study

Background Dermoscopy is commonly used for the evaluation of pigmented lesions, but agreement between experts for identification of dermoscopic structures is known to be relatively poor. Expert labeling of medical data is a bottleneck in the development of machine learning (ML) tools, and crowdsourcing has been demonstrated as a cost- and time-efficient method for the annotation of medical images. Objective The aim of this study is to demonstrate that crowdsourcing can be used to label basic dermoscopic structures from images of pigmented lesions with similar reliability to a group of experts. Methods First, we obtained labels of 248 images of melanocytic lesions with 31 dermoscopic “subfeatures” labeled by 20 dermoscopy experts. These were then collapsed into 6 dermoscopic “superfeatures” based on structural similarity, due to low interrater reliability (IRR): dots, globules, lines, network structures, regression structures, and vessels. These images were then used as the gold standard for the crowd study. The commercial platform DiagnosUs was used to obtain annotations from a nonexpert crowd for the presence or absence of the 6 superfeatures in each of the 248 images. We replicated this methodology with a group of 7 dermatologists to allow direct comparison with the nonexpert crowd. The Cohen κ value was used to measure agreement across raters. Results In total, we obtained 139,731 ratings of the 6 dermoscopic superfeatures from the crowd. There was relatively lower agreement for the identification of dots and globules (the median κ values were 0.526 and 0.395, respectively), whereas network structures and vessels showed the highest agreement (the median κ values were 0.581 and 0.798, respectively). This pattern was also seen among the expert raters, who had median κ values of 0.483 and 0.517 for dots and globules, respectively, and 0.758 and 0.790 for network structures and vessels. The median κ values between nonexperts and thresholded average–expert readers were 0.709 for dots, 0.719 for globules, 0.714 for lines, 0.838 for network structures, 0.818 for regression structures, and 0.728 for vessels. Conclusions This study confirmed that IRR for different dermoscopic features varied among a group of experts; a similar pattern was observed in a nonexpert crowd. There was good or excellent agreement for each of the 6 superfeatures between the crowd and the experts, highlighting the similar reliability of the crowd for labeling dermoscopic images. This confirms the feasibility and dependability of using crowdsourcing as a scalable solution to annotate large sets of dermoscopic images, with several potential clinical and educational applications, including the development of novel, explainable ML tools