Exploring the Links between Post-Industrial Landscape History and Ecology through Participatory Methods

PLOS_ONEPLOS One, Published online 26 August 2015

By Kevin J. Rich, Michael Ridealgh, Sarah E. West, Steve Cinderby, and Mike Ashmore

“There is increasing recognition of the importance for local biodiversity of post-mining sites, many of which lie near communities that have suffered significant social and economic deprivation as the result of mine closures. However, no studies to date have actively used the knowledge of local communities to relate the history and treatment of post-mining sites to their current ecological status. We report a study of two post-mining sites in the Yorkshire coalfield of the UK in which the local community were involved in developing site histories and assessing plant and invertebrate species composition. Site histories developed using participatory GIS revealed that the sites had a mixture of areas of spontaneous succession and technical reclamation, and identified that both planned management interventions and informal activities influenced habitat heterogeneity and ecological diversity.

 (a) timeline and (b) map of the Fitzwilliam site developed using PGIS and RAP-GIS differentiating in (a) activities and site impacts and in (b) observations and active interventions.

(a) timeline and (b) map of the Fitzwilliam site developed using PGIS and RAP-GIS differentiating in (a) activities and site impacts and in (b) observations and active interventions.

“Two groups of informal activity were identified as being of particular importance. Firstly, there has been active protection by the community of flower-rich habitats of conservation value (e.g. calcareous grassland) and distinctive plant species (e.g. orchids) which has also provided important foraging resources for butterfly and bumblebee species. Secondly, disturbance by activities such as use of motorbikes, informal camping, and cutting of trees and shrubs for fuel, as well as planned management interventions such as spreading of brick rubble, has provided habitat for plant species of open waste ground and locally uncommon invertebrate species which require patches of bare ground. This study demonstrates the importance of informal, and often unrecorded, activities by the local community in providing diverse habitats and increased biodiversity within a post-mining site, and shows that active engagement with the local community and use of local knowledge can enhance ecological interpretation of such sites and provide a stronger basis for successful future management.”

Mapping Seabed Sediments: Comparison of Manual, Geostatistical, Object-based Image Analysis and Machine Learning Approaches

Continental Shelf Research, Published online 17 May 2014

By Markus Diesing, Sophie L. Green, David Stephens, R. Murray Lark,
Heather A. Stewart, and Dayton Dove

“Marine spatial planning and conservation need underpinning with sufficiently detailed and accurate seabed substrate and habitat maps. Although multibeam echosounders enable us to map the seabed with high resolution and spatial accuracy, there is still a lack of fit-for-purpose seabed maps. This is due to the high costs involved in carrying out systematic seabed mapping programmes and the fact that the development of validated, repeatable, quantitative and objective methods of swath acoustic data interpretation is still in its infancy. We compared a wide spectrum of approaches including manual interpretation, geostatistics, object-based image analysis and machine-learning to gain further insights into the accuracy and comparability of acoustic data interpretation approaches based on multibeam echosounder data (bathymetry, backscatter and derivatives) and seabed samples with the aim to derive seabed substrate maps. Sample data were split into a training and validation data set to allow us to carry out an accuracy assessment.

seabed-OBIA

Results of the map comparisons: A—manual-OBIA; B—manual-Random Forest; C—manual-geostatistics; D—OBIA-Random Forest; E—OBIA-geostatistics; F—Random Forest geostatistics. Green indicates agreement and red indicates disagreement.(For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

“Overall thematic classification accuracy ranged from 67% to 76% and Cohen׳s kappa varied between 0.34 and 0.52. However, these differences were not statistically significant at the 5% level. Misclassifications were mainly associated with uncommon classes, which were rarely sampled. Map outputs were between 68% and 87% identical. To improve classification accuracy in seabed mapping, we suggest that more studies on the effects of factors affecting the classification performance as well as comparative studies testing the performance of different approaches need to be carried out with a view to developing guidelines for selecting an appropriate method for a given dataset. In the meantime, classification accuracy might be improved by combining different techniques to hybrid approaches and multi-method ensembles.”

Fine-Scale Cartography of Human Impacts along French Mediterranean Coasts: A Relevant Map for the Management of Marine Ecosystems

PLOS ONEPLOS One, Published 12 August 2015

By Florian Holon, Nicolas Mouquet, Pierre Boissery, Marc Bouchoucha,
Gwenaelle Delaruelle, Anne-Sophie Tribot, and Julie Deter

“Ecosystem services provided by oceans and seas support most human needs but are threatened by human activities. Despite existing maps illustrating human impacts on marine ecosystems, information remains either large-scale but rough and insufficient for stakeholders (1 km² grid, lack of data along the coast) or fine-scale but fragmentary and heterogeneous in methodology. The objectives of this study are to map and quantify the main pressures exerted on near-coast marine ecosystems, at a large spatial scale though in fine and relevant resolution for managers (one pixel = 20 x 20 m). It focuses on the French Mediterranean coast (1,700 km of coastline including Corsica) at a depth of 0 to 80 m.

Spatial distribution of cumulative impact scores. (A) Spatial distribution of cumulative impact scores (IC) and localization of coastal water bodies. (B, C, D) Zooms showing how water bodies are more or less impacted (IC categories). (E) Detailed map of the Golfe of St Tropez showing how the golfe is impacted (quantitative IC scores) Several cities are indicated by small squares.

Spatial distribution of cumulative impact scores. (A) Spatial distribution of cumulative impact scores (IC) and localization of coastal water bodies.(B, C, D) Zooms showing how water bodies are more or less impacted (IC categories). (E) Detailed map of the Golfe of St Tropez showing how the golfe is impacted (quantitative IC scores) Several cities are indicated by small squares.

“After completing and homogenizing data presently available under GIS on the bathymetry and anthropogenic pressures but also on the seabed nature and ecosystem vulnerability, we provide a fine modeling of the extent and impacts of 10 anthropogenic pressures on marine habitats. The considered pressures are man-made coastline, boat anchoring, aquaculture, urban effluents, industrial effluents, urbanization, agriculture, coastline erosion, coastal population and fishing. A 1:10 000 continuous habitat map is provided considering 11 habitat classes. The marine bottom is mostly covered by three habitats: infralittoral soft bottom, Posidonia oceanica meadows and circalittoral soft bottom.

fine-scale-cartography2

“Around two thirds of the bottoms are found within medium and medium high cumulative impact categories. Seagrass meadows are the most impacted habitats. The most important pressures (in area and intensity) are urbanization, coastal population, coastal erosion and man-made coastline. We also identified areas in need of a special management interest. This work should contribute to prioritize environmental needs, as well as enhance the development of indicators for the assessment of the ecological status of coastal systems. It could also help better apply and coordinate management measures at a relevant scale for biodiversity conservation.”

Associations between residence at birth and mental health disorders: a spatial analysis of retrospective cohort data

BMC Public Health
BMC Public Health, (2015) 15:688

By Kate Hoffman, Ann Aschengrau, Thomas F. Webster, Scott M. Bartell, and Verónica M. Vieira

Background: Mental healthdisorders impact approximately one in four US adults. While their causes are likely multifactorial, prior research has linked the risk of certain mental health disorders to prenatal and early childhood environmental exposures, motivating a spatial analysis to determine whether risk varies by birth location.

Methods: We investigated the spatial associations between residence at birth and odds of depression, bipolar disorder, and post-traumatic stress disorder (PTSD) in a retrospective cohort (Cape Cod, Massachusetts, 1969–1983) using generalized additive models to simultaneously smooth location and adjust for confounders. Birth location served as a surrogate for prenatal exposure to the combination of social and environmental factors related to the development of mental illness. We predicted crude and adjusted odds ratios (aOR) for each outcome across the study area. The results were mapped to identify areas of increased risk.

Geographic distribution of PTSD vs. no reported mental illness from analyses using the optimal span size for each model [unadjusted (a) and adjusted for sex, year of birth, family history of mental health diagnosis, father’s occupation, mother’s educational attainment, maternal smoking during pregnancy, and pre/postnatal PCE exposure (b)]. Black contour bands indicate areas of statistically significant increased or decreased odds of outcomes.The scale includes most, but not all, observed odds ratios.

Geographic distribution of PTSD vs. no reported mental illness from analyses using the optimal span size for each model [unadjusted (a) and adjusted for sex, year of birth, family history of mental health diagnosis, father’s occupation, mother’s educational attainment, maternal smoking during pregnancy, and pre/postnatal PCE exposure (b)]. Black contour bands indicate areas of statistically significant increased or decreased odds of outcomes.The scale includes most, but not all, observed odds ratios.

Results: We observed spatial variation in the crude odds ratios of depression that was still present even after accounting for spatial confounding due to geographic differences in the distribution of known risk factors (aOR range: 0.61–3.07, P = 0.03). Similar geographic patterns were seen for the crude odds of PTSD; however, these patterns were no longer present in the adjusted analysis (aOR range: 0.49–1.36, P = 0.79), with family history of mental illness most notably influencing the geographic patterns. Analyses of the odds of bipolar disorder did not show any meaningful spatial variation (aOR range: 0.58–1.17, P = 0.82).

Conclusion: Spatial associations exist between residence at birth and odds of PTSD and depression, but much of this variation can be explained by the geographic distributions of available risk factors. However, these risk factors did not account for all the variation observed with depression, suggesting that other social and environmental factors within our study area need further investigation.”

A Spatio-temporal Analysis of Crime at Washington, DC Metro Rail: Stations’ Crime-generating and Crime-attracting Characteristics as Transportation Nodes and Places

logoCrime Science, Published Online 16 July 2015

By Yasemin Irvin-Erickson and Nancy La Vigne

“Transit stations are acknowledged as particularly criminogenic settings. Transit stations may serve as crime “generators,” breeding crime because they bring together large volumes of people at particular geographies and times. They may also serve as crime “attractors,” providing well-known opportunities for crimes. This paper explores the node and place characteristics that can transform Washington DC, Metro stations to generators and attractors of different crimes at different times of the day. The crime-generating and crime-attracting characteristics of stations are modeled with Negative Binomial Regression analysis. To reflect the temporal trends in crime, crime counts are stratified into three temporal groups: peak hours, off-peak day hours, and off-peak night hours.

Robbery density at peak, non-peak day, and non-peak night hours

Robbery density at peak, non-peak day, and non-peak night hours

“The findings from this study not only suggest that stations assume different nodal and place-based crime-generating and crime-attracting characteristics, but also these roles vary for different crimes and different times. The level of activity and accessibility of a station, the level of crime at a station, and the connectedness of a station to other stations are consistent indicators of high crime rate ratios. Different characteristics of a station—such as being a remote station or belonging to a high or low socioeconomic status block group—are significant correlates for particular crime outcomes such as disorderly conduct, robbery, and larceny. ”

Metadata Topic Harmonization and Semantic Search for Linked-Data-Driven Geoportals: A Case Study Using ArcGIS Online

By Yingjie Hu, Krzysztof Janowicz, Sathya Prasad, and Song Gao

Transactions in GIS, Volume 19, Issue 3, June 2015, Pages 398–416

“Geoportals provide integrated access to geospatial resources, and enable both authorities and the general public to contribute and share data and services. An essential goal of geoportals is to facilitate the discovery of the available resources. Such a process relies heavily on the quality of metadata. While multiple metadata standards have been established, data contributers may adopt different standards when sharing their data via the same geoportal. This is especially the case for user-generated content where various terms and topics can be introduced to describe similar datasets. While this heterogeneity provides a wealth of perspectives, it also complicates resource discovery. With the fast development of the Semantic Web technologies, there is a rise of Linked-Data-driven portals. Although these novel portals open up new ways to organize metadata and retrieve resources, they lack effective semantic search methods.

Comparing estimated relevance scores with human judgments: (a) Without the interaction variable; and (b) With the interaction variable

Comparing estimated relevance scores with human judgments: (a) Without the interaction variable; and (b) With the interaction variable

“This article addresses the two challenges discussed above, namely the topic heterogeneity brought by multiple metadata standards and the lack of established semantic search in Linked-Data-driven geoportals. To harmonize the metadata topics, we employ a natural language processing method, namely Labeled Latent Dirichlet Allocation (LLDA), and train it using standardized metadata from Data.gov. With respect to semantic search, we construct thematic and geographic matching features from the textual metadata descriptions, and train a regression model via a human participants experiment. We evaluate our methods by examining their performances in addressing the two issues. Finally, we implement a semantics-enabled and Linked-Data-driven prototypical geoportal using a sample dataset from Esri’s ArcGIS Online.”

Exploring the Future of Cloud-based GIS in Public Gardens

Hosted by Esri and the American Public Gardens Association
July 20 – 22 , 2015
San Diego Convention Center, San Diego, CA

May 4 FINAL DRAFT APGA Esri 2015 Registration Brochure

Many public gardens are already using GIS to help manage their grounds and collections. Now, new cloud-based GIS tools promise to transform our garden’s collection maps into story-telling tools and apps that can help us engage with visitors, teach science literacy, and advance plant conservation worldwide. We need your voice at the table on how to best move these ideas forward!

Please join us for the APGA-Esri 2015 GIS Symposium on July 20 – 22, 2015, a special track within the 2015 Esri International User Conference in San Diego, CA. This symposium allows for a full immersion in the GIS experience, coupled with two break-away days–a “community conversation”–where we discuss alternatives and work together to design a path forward for the future of cloud-based GIS in public gardens.