Discrete Global Grid Systems as scalable geospatial frameworks for characterizing coastal environments

Development of a generalized pseudo-probabilistic approach for characterizing ecological conditions in estuaries using secondary data

Under the best circumstances, achieving or sustaining optimum ecological conditions in estuaries is challenging. Persistent information gaps in estuarine data make it difficult to differentiate natural variability from potential regime shifts. Long-term monitoring is critical for tracking ecological change over time. In the United States (US), many resource management programs are working at maximum capacity to address existing state and federal water quality mandates (e.g., pollutant load limits, climate impact mitigation, and fisheries management) and have little room to expand routine sampling efforts to conduct periodic ecological baseline assessments, especially at state and local scales. Alternative design, monitoring, and assessment approaches are needed to help offset the burden of addressing additional data needs to increase understanding about estuarine system resilience when existing monitoring data are sparse or spatially limited. Research presented here offers a pseudo-probabilistic approach that allows for the use of found or secondary data, such as data on hand and other acquired data, to generate statistically robust characterizations of ecological conditions in estuaries. Our approach uses a generalized pseudo-probabilistic framework to synthesize data from different contributors to inform probabilistic-like baseline assessments. The methodology relies on simple geospatial techniques and existing tools (R package functions) developed for the US Environmental Protection Agency to support ecological monitoring and assessment programs like the National Coastal Condition Assessment. Using secondary estuarine water quality data collected in the Northwest Florida (US) estuaries, demonstrations suggest that the pseudo-probabilistic approach produces estuarine condition assessment results with reasonable statistical confidence, improved spatial representativeness, and value-added information. While the pseudo-probabilistic framework is not a substitute for fully evolved monitoring, it offers a scalable alternative to bridge the gap between limitations in resource management capability and optimal monitoring strategies to track ecological baselines in estuaries over time.

A Phanerozoic gridded dataset for palaeogeographic reconstructions

Global Plate Models are widely used in the Earth Sciences to reconstruct the past geographic position of geological and palaeontological samples. However, the application of Global Plate Models to retrieve 'palaeocoordinates' is not trivial. Different Global Plate Models exist which vary in their complexity, spatiotemporal coverage, reference frame, and intended use. Consequently, careful consideration of which models are appropriate for any given research question is required. Here, we document and provide access to reconstruction datasets for five Global Plate Models in the palaeomagnetic reference frame. These datasets provide 'true' palaeolatitudes for three discrete global grids reconstructed at one-million-year intervals throughout the Phanerozoic (540-0 Ma), offering three key benefits for the Earth Science community: (1) allow users to look up palaeocoordinates for their samples (e.g. fossil occurrences) through simple indexing without having to learn additional software packages; (2) provide palaeocoordinates which have been generated consistently with thorough documentation; (3) provide static files which preserve model output and which can be used to evaluate palaeogeographic differences between Global Plate Models.

Methods for a composite ecological suitability measure to inform cumulative restoration assessments in Gulf of Mexico estuaries

Ecosystem management requires a systematic, holistic approach that considers ecological and social outcomes. Effective restoration practices promote a balance of ecological and social goals by addressing ecological integrity, efficiently maximizing benefits while minimizing investment, and encompassing collaborative stakeholder engagement. Socio-ecological assessments can inform adaptive management and be utilized to prioritize restoration activities and monitor restoration effectiveness. In estuarine systems, socio-ecological assessments should evaluate the ability of habitats to support both ecologically and locally important species. The composite measure presented utilizes a combination of ecological and social measures to characterize ecological suitability for individual and multiple Gulf of Mexico estuarine species. The ecological suitability value (ES) for a given spatial unit is based on a suite of biophysical measures of the quality and extent of suitable habitat for each species, the species' trophic importance in a food web context, and the importance of each species in relation to stakeholder values and benefits. ES values for individual spatial units can be aggregated to estimate the distribution of ecological suitability at the estuarine scale. The ES values are calculated using examples for each step in the process. The information provided by ecological suitability characterizations can support restoration prioritization decisions for Gulf of Mexico estuaries and can provide a baseline measure to gauge restoration effectiveness over time to inform cumulative restoration assessments.

Metabarcoding of soil environmental DNA to estimate plant diversity globally

Introduction

Traditional approaches to collecting large-scale biodiversity data pose huge logistical and technical challenges. We aimed to assess how a comparatively simple method based on sequencing environmental DNA (eDNA) characterises global variation in plant diversity and community composition compared with data derived from traditional plant inventory methods.

Methods

We sequenced a short fragment (P6 loop) of the chloroplast trnL intron from from 325 globally distributed soil samples and compared estimates of diversity and composition with those derived from traditional sources based on empirical (GBIF) or extrapolated plant distribution and diversity data.

Results

Large-scale plant diversity and community composition patterns revealed by sequencing eDNA were broadly in accordance with those derived from traditional sources. The success of the eDNA taxonomy assignment, and the overlap of taxon lists between eDNA and GBIF, was greatest at moderate to high latitudes of the northern hemisphere. On average, around half (mean: 51.5% SD 17.6) of local GBIF records were represented in eDNA databases at the species level, depending on the geographic region.

Discussion

eDNA trnL gene sequencing data accurately represent global patterns in plant diversity and composition and thus can provide a basis for large-scale vegetation studies. Important experimental considerations for plant eDNA studies include using a sampling volume and design to maximise the number of taxa detected and optimising the sequencing depth. However, increasing the coverage of reference sequence databases would yield the most significant improvements in the accuracy of taxonomic assignments made using the P6 loop of the trnL region.

Research on Navigation Safety Evaluation of Coastal Waters Based on Dynamic Irregular Grid

Despite being a minor probability event, marine accidents can cause serious consequences such as casualties, environmental damage, and even massive economic losses. As an important part of the marine traffic safety system, the evaluation of navigation safety in coastal waters is of great significance to ensure the safety of ship navigation. In order to objectively evaluate the safety of navigation, this paper proposes an irregular grid division method that combines influencing factors including seabed topography, ship traffic flow, electronic charts, and marine meteorology. In this work, the navigable boundary was extracted by spatial analysis algorithms of the slope calculation. Based on the alpha-shape algorithm and the Voronoi diagram, the constrained Delaunay triangulation was used to extract the inner and outer boundaries of the ship′s navigation area, and the time-varying factors of marine hydrology and meteorology were integrated to form a dynamic irregular grid. The navigation safety evaluation indicators in coastal waters were divided into five risk levels, namely lower, low, medium, high, and higher. Then, the entropy weight theory was used to calculate the weight of the evaluation index. Finally, a safety evaluation model was constructed to evaluate the risk of navigation safety in coastal waters. Herein, taking the coastal waters of Lianyungang Port as a demonstration area, this paper divided the dynamic irregular grid and conducted the navigation safety analysis and evaluation based on the grid. The experimental results show that our method fully considers the influence of objective factors and the uncertainty of safety evaluation indicators and has favorable adaptability to the evaluation of navigation safety in coastal waters.