Exploring the uses and value of invertebrate DNA metabarcoding

This thesis reviews and explores the use of DNA metabarcoding techniques on invertebrates, moving beyond biodiversity audits to improve monitoring capabilities in terrestrial ecosystems. Here, metabarcoding is used to look at fine scale differences in arthropod biodiversity, foraging behaviour of native bees, and even to track vertebrate populations. This body of work demonstrates the immense value of this technique to monitor how whole ecosystems respond to change

Analysis of Insect-Plant Interactions Affected by Mining Operations, A Graph Mining Approach

The decline in ecological connections signifies the potential extinction of species, which can be attributed to disruptions and alterations. The decrease in interconnections among species reflects their susceptibility to changes. For example, certain insects and plants that rely on exclusive interactions with a limited number of species, or even a specific species, face the risk of extinction if they lose these crucial connections. Currently, mining activities pose significant harm to natural ecosystems, resulting in various adverse environmental impacts. In this study, we utilized network science techniques to analyze the ecosystem in a graph-based structure, aiming to conserve the ecosystem affected by mining operations in the northern region of Scotland. The research encompasses identifying the most vital members of the network, establishing criteria for identifying communities within the network, comparing, and evaluating them, using models to predict secondary extinctions that occur when a species is removed from the network, and assessing the extent of network damage. Our study's novelty is utilizing network science approaches to investigate the biological data related to interactions between insects and plants.Comment: 9 pages, 16 figure

Geovisualization of forest simulation modelling results: A case study of carbon sequestration and biodiversity

Sustainable forest management requires new tools to analyze spatial and temporal forest dynamics and to examine those forest parameters that are related to sustainability. We built a prototype system for data analysis and decision-making at forest enterprise level by integrating a forest ecosystem model EFIMOD-PRO (long-term prediction of forest growth and soil development) with an interactive visualization system CommonGIS for analysis of spatially and temporally related data. Using the prototype, a case study in Central European Russia simulated four silvicultural regimes over 200 years: natural development, selective forestry, legal forestry according to the Russian forestry legislation, and illegal forest practice. Exploratory analysis of the simulation results demonstrated that (1) natural stand development is the best alternative for carbon sequestration; (2) legal forest management is the best regime for timber production; (3) selective forestry combines the advantages of two previous strategies, and can be the best strategy for implementing sustainable forest management; and (4) illegal forest practices lead to a fast decrease in forest productivity and decreasing biodiversity. Interactive and dynamic visualizations with maps and statistical graphics played a crucial role in data cleaning, model validation, and analysis of simulation results. The case study demonstrated the potential of integrating forest ecosystem models with exploratory data visualization for the analysis and expert evaluation at the local level. The prototype can be used to present ecological and silvicultural consequences of various management practices to stakeholders and differing social groups, thus stimulating effective decision-making for sustainable forestry

Assessing the impacts of seabed mineral extraction in the deep sea and coastal marine environments : Current methods and recommendations for environmental risk assessment

Mineral extraction from the seabed has experienced a recent surge of interest from both the mining industry and marine scientists. While improved methods of geological investigation have enabled the mapping of new seafloor mineral reserves, the ecological impacts of mining in both the deep sea and the shallow seabed are poorly known. This paper presents a synthesis of the empirical evidence from experimental seabed mining and parallel industries to infer the effects of seabed mineral extraction on marine ecosystems, focusing on polymetallic nodules and ferromanganese concretions. We use a problem-structuring framework to evaluate causal relationships between pressures caused by nodule extraction and the associated changes in marine ecosystems. To ensure that the rationale behind impact assessments is clear, we propose that future impact assessments use pressure-specific expert elicitation. We further discuss integrating ecosystem services in the impact assessments and the implications of current methods for environmental risk assessments.Peer reviewe

Disturbance indicators for time series reconstruction and marine ecosystem health impact assessment

A systematic reconstruction of Multiple Marine Ecological Disturbances (MMEDs) involving disease occurrence, morbidity and mortality events has been undertaken so that a taxonomy of globally distributed marine disturbance types can be better quantified and common forcing factors identified. Combined disturbance data include indices of morbidity, mortality and disease events affecting humans, marine invertebrates, flora and wildlife populations. In the search for the best disturbance indicators of ecosystem change, the unifying solution for joining data from disparate fields is to organize data into space/time/topic hierarchies that permit convergence of data due to shared and appropriate scaling. The scale of the data selects for compatible methodologies, leading to better data integration, dine series reconstruction and the discovery of new relationships. Information technology approaches designed to assist this process include bibliographic keyword searches, data-mining, data-modeling and geographic information system design. Expert consensus, spatial, temporal, categorical and statistical data reduction methods are used to reclassify thousands of independent anomaly observations into eight functional impact groups representing anoxic-hypoxic, biotoxin-exposure, disease, keystone-chronic, mass-lethal, new-novel-invasive, physically forced and trophic-magnification disturbances. Data extracted from the relational database and Internet (http://www.heedmd.org) geographic information system demonstrate non-random patterns relative to expected dependencies. When data are combined they better reflect response to exogenous forcing factors at larger scales (e.g. North Atlantic and Southern Ocean Oscillation index scales) than is apparent without grouping. New hypotheses have been generated linking MMEDs to climate system forcing , variability and changes within the Northwestern Atlantic Ocean, Gulf of Mexico and Caribbean Sea. A more general global survey known collectively as the Health Ecological and Economic Dimensions (HEED) project demonstrates the potential application of the methodology to the Baltic Sea and other large marine ecosystems. The rescue of multi-decadal climatic, oceanographic, fisheries economic, and public health anomaly data combined with MMED data provides a tool to help researchers create regional disturbance regimes to illustrate disturbance impact. A recommendation for a central data repository is proposed to better coordinate the many data observers, resource managers, and agencies collecting pieces of marine disturbance information needed for monitoring ecosystem condition

Mapping the world’s intact forest landscapes by remote sensing

Protection of large natural forest landscapes is a highly important task to help fulfill different international strategic initiatives to protect forest biodiversity, to reduce carbon emissions from deforestation and forest degradation, and to stimulate sustainable forest management practices. This paper introduces a new approach for mapping large intact forest landscapes (IFL), defined as an unbroken expanse of natural ecosystems within areas of current forest extent, without signs of significant human activity, and having an area of at least 500 km2. A global IFL map was created using..

Monitoring Oil Exploitation Infrastructure and Dirt Roads with Object-Based Image Analysis and Random Forest in the Eastern Mongolian Steppe

Information on the spatial distribution of human disturbance is important for assessing and monitoring land degradation. In the Eastern Mongolian Steppe Ecosystem, one of the major driving factors of human-induced land degradation is the expansion of road networks mainly due to intensifications of oil exploration and exploitation. So far, neither the extents of road networks nor the extent of surrounding grasslands affected by the oil industry are monitored which is generally labor consuming. This causes that no information on the changes in the area which is affected by those disturbance drivers is available. Consequently, the study aim is to provide a cost-effective methodology to classify infrastructure and oil exploitation areas from remotely sensed images using object-based classifications with Random Forest. By combining satellite data with different spatial and spectral resolutions (PlanetScope, RapidEye, and Landsat ETM+), the product delivers data since 2005. For the classification variables, segmentation, spectral characteristics, and indices were extracted from all above mentioned imagery and used as predictors. Results show that overall accuracies of land use maps ranged 73%–93% mainly depending on satellites’ spatial resolution. Since 2005, the area of grassland disturbed by dirt roads and oil exploitation infrastructure increased by 88% with its highest expansion by 47% in the period 2005–2010. Settlements and croplands remained relatively constant throughout the 13 years. Comparison of multiscale classification suggests that, although high spatial resolutions are clearly beneficial, all datasets were useful to delineate linear features such as roads. Consequently, the results of this study provide an effective evaluation for the potential of Random Forest for extracting relatively narrow linear features such as roads from multiscale satellite images and map products that are possible to use for detailed land degradation assessments

Earth resources-regional transfer activity contracts review

A regional transfer activity contracts review held by the Earth Resources Office was summarized. Contracts in the earth resources field primarily directed toward applications of satellite data and technology in solution of state and regional problems were reviewed. A summary of the progress of each contract was given in order to share experiences of researchers across a seven state region. The region included Missouri, Kentucky, Tennessee, Mississippi, Alabama, Georgia, and North Carolina. Research in several earth science disciplines included forestry, limnology, water resources, land use, geology, and mathematical modeling. The use of computers for establishment of information retrieval systems was also emphasized

Oil Extraction Infrastructure Development And Resulting Land-Cover Change In Mckenzie County, North Dakota, 2009 To 2014

Improved techniques and methods in directional drilling and hydraulic fracturing have allowed once inaccessible resources to become profitably accessible in the Bakken Region of North Dakota (Fershee 2011). This recent development has been rapid, and associated land-cover change can be described as spatially extensive (Baker et al. 2012). After an extensive literature review and to the best of my knowledge, little research has been conducted in the Bakken Region regarding land-cover change associated with oil development. Using high-spatial-resolution, four-band imagery from the National Agriculture Imagery Program (NAIP) in conjunction with Geographic Object-Based Image Analysis (GEOBIA) techniques, it is possible to identify narrow-linear and small-area features on the landscape associated with oil development. The overall accuracy for McKenzie County was 41.2 percent, significantly lower than overall accuracies seen in similar studies. These results suggest this method is not entirely suitable for land-cover change analysis in the grassland biome without additional data analysis and/or editing. Further analysis of a selected smaller portion of the county displaying land-cover characteristics amenable for accurate classification found oil extraction infrastructure contributed to an expected but minimal decrease in grassland and agricultural land-cover