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A new remote sensing-based Carbon Sequestration Potential Index (CSPI): A tool to support land carbon management

Integrating remote sensing into assessments of carbon stocks and fluxes has advanced our understanding of how global change affects landscapes and our capacity to support decision making about forest management. However, there remains a lack of detailed and actionable analyses conducted across widely ranging environmental conditions that are appropriate for tactical planning. We used airborne laser scanning data and multi-source satellite imagery to estimate forest aboveground carbon density and gross primary production, and to map forest cover across the main Hawaiian Islands. We used these measures to develop the Carbon Sequestration Potential Index (CSPI), which identifies where the potential for carbon sequestration following afforestation would be highest within a complex landscape of 304 management units. Variation in CSPI was high across islands and between ecosystems, with low values for cool, dry and largely intact forest systems and high values for warm, wet and largely non-forested systems. The CSPI provided a rapid, spatially-explicit and actionable assessment of Hawaiian forest reserves, which can help stewardship agencies contribute to state carbon neutrality goals through climate-smart and science-driven prescriptions that encompass conservation to restoration.

Hawaii↗

The physical characteristics of the sediments on and surrounding Dauphin Island, Alabama

Scientists from the U.S. Geological Survey, St. Petersburg Coastal and Marine Science Center collected 303 surface sediment samples from Dauphin Island, Alabama, and the surrounding water bodies in August 2015. These sediments were processed to determine physical characteristics such as organic content, bulk density, and grain-size. The environments where the sediments were collected include high and low salt marshes, washover deposits, dunes, beaches, sheltered bays, and open water. Sampling by the USGS was part of a larger study to assess the feasibility and sustainability of proposed restoration efforts for Dauphin Island, Alabama, and assess the island’s resilience to rising sea level and storm events. The data presented in this publication can be used by modelers to attempt validation of hindcast models and create predictive forecast models for both baseline conditions and storms. This study was funded by the National Fish and Wildlife Foundation, via the Gulf Environmental Benefit Fund. This report serves as an archive for sedimentological data derived from surface sediments. Downloadable data are available as Excel spreadsheets, JPEG files, and formal Federal Geographic Data Committee metadata.

Alabama↗

Linking monitoring and data analysis to predictions and decisions for the range-wide eastern black rail status assessment

The US Fish and Wildlife Service has initiated a re-envisioned approach for providing decision makers with the best available science and synthesis of that information, called the Species Status Assessment (SSA), for endangered species decision making. The SSA report is a descriptive document that provides decision makers with an assessment of a species’ current status and predicted future status. These analyses support all manner of decisions under the US Endangered Species Act, such as listing, reclassification, recovery planning, etc. Novel scientific analysis and predictive modeling in SSAs could be an important part of rooting species conservation decisions in current data and cutting edge analytical and modeling techniques. Here we describe a novel analysis of available data to assess current condition of eastern black rail across its range in a dynamic occupancy analysis. We used the results of the analysis to develop a site occupancy projection model where the model parameters (initial occupancy, site persistence, colonization) were linked to environmental covariates, such as land management and land cover change (sea-level rise, development, etc.). We used the projection model to predict future conditions under multiple sea-level rise and habitat management scenarios. Occupancy probability and site colonization were low in all analysis units and site persistence was also low, suggesting low resiliency and redundancy currently. Extinction probability was high for all analysis units in all simulated scenarios except one with significant effort to preserve existing habitat, suggesting low future resiliency and redundancy. With results of these data analyses and predictive modeling, the US Fish and Wildlife Service concluded that protections of the Endangered Species Act were warranted for this subspecies.

Endangered Species Research↗

Applications of optical sensors for high-frequency water-quality monitoring and research

The recent commercial availability of in-situ optical sensors, together with new techniques for data collection and analysis, provides the opportunity to monitor a wide range of water-quality constituents over time scales during which environmental conditions actually change. Traditional approaches for data collection (daily to monthly discrete samples) are often limited by high sample collection, processing, and analytical costs, difficult site access, and logistical challenges, particularly for long-term sampling at a large number of sites. Optical sensors that continuously measure constituents in the environment by absorbance or fluorescence properties (Figure 1) have had a long history of use in oceanography for measuring highly resolved concentrations and fluxes of organic matter, nutrients, and algal material. However, much of the work using commercially-available optical sensors in rivers and streams has taken place in only the last few years. Figure 1. [NOT SHOWN] Optical sensor technology is now sufficiently developed to warrant broader application for research and monitoring in coastal and freshwater systems, and the United States Geological Survey (a U.S. science agency) is now using these sensors in a variety of research and monitoring programs to better understand water quality in-situ and in real-time. Examples are numerous and range from the applications of nitrate sensors for calculating loads to estuaries susceptible to hypoxia (Pellerin et al., 2014) to the use of fluorometers to estimate methymercury fluxes (Bergamaschi et al., 2011) and disinfection byproduct formation (Carpenter et al., 2013). Transmitting these data in real-time provides information that can be used for early trend detection, help identify monitoring gaps critical for water management, and provide science-based decision support across a range of issues related to water quality, freshwater ecosystems, and human health. Despite the value of these sensors, collecting data that meet high-quality standards requires investment in and adherence to tested and established methods and protocols for sensor operation and data management (Pellerin et al., 2013). For example, optical sensor measurements can be strongly influenced by a variety of matrix effects, including water temperature, inner filtering from highly colored water, and scattering of light by suspended particles (Downing et al., 2012). Characterizing and correcting sensors for these effects – as well as the continued development of common methodologies and protocols for sensor use – will be critical to ensuring comparable measurements across sites and over time. In addition, collaborative efforts such as the Nutrient Sensor Challenge (www.nutrients-challenge.org) will continue to accelerate the development, production and use of affordable, reliable and accurate sensors for a range of environments. REFERENCES Bergamaschi .B.A., Fleck J.A., Downing B.D., Boss E., Pellerin B.A., Ganju N.K., Schoellhamer D.H., Byington A.A., Heim W.A., Stephenson M., Fujii R. (2011), Methyl mercury dynamics in a tidal wetland quantified using in situ optical measurements. Limnology and Oceanography, 56(4): 1355-1371. Carpenter K.D., Kraus T.E.C., Goldman J.H., Saraceno J., Downing B.D., Bergamaschi B.A., McGhee G., Triplett T. (2013), Sources and Characteristics of Organic Matter in the Clackamas River, Oregon, Related to the Formation of Disinfection By-products in Treated Drinking Water: U.S. Geological Survey Scientific Investigations Report 2013–5001, 78 p. Downing .B.D., Pellerin B.A., Bergamaschi B.A., Saraceno J., Kraus T.E.K. (2012), Seeing the light: The effects of particles, temperature and inner filtering on in situ CDOM fluorescence in rivers and streams. Limnology and Oceanography: Methods, 10: 767-775. Pellerin B.A., Bergamaschi B.A., Downing B.D., Saraceno J., Garrett J.D., Olsen L.D. (2013), Optical Techniques for the Determination of Nitrate in En

Conference Paper↗

Missing data in ecology: Syntheses, clarifications, and considerations

In ecology and related sciences, missing data are common and occur in a variety of different contexts. When missing data are not handled properly, subsequent statistical estimates tend to be biased, inefficient, and lack proper confidence interval coverage. Missing data are often grouped into three categories: missing completely at random (MCAR), missing at random (MAR), and missing not at random (MNAR). We review each category and compare their benefits and drawbacks. We review several approaches to handling missing data including complete case analysis, imputation, inverse probability weighting, and data augmentation. We clarify what types of variables should accompany imputation methods and how those variables are influenced by the analysis methods. Additionally, we discuss missing data that lack a formal basis for measurement and hence are fundamentally different from MCAR, MAR, and MNAR missing data. Throughout, we introduce concepts and numeric examples using both simulated data and data from the United States Environmental Protection Agency's 2016 National Wetland Condition Assessment. We conclude by providing five considerations for ecologists and other scientists handling missing data.

Ecological Monographs↗

Comparative evaluation of statistical and mechanistic models of Escherichia coli at beaches in southern Lake Michigan

Statistical and mechanistic models are popular tools for predicting the levels of indicator bacteria at recreational beaches. Researchers tend to use one class of model or the other, and it is difficult to generalize statements about their relative performance due to differences in how the models are developed, tested, and used. We describe a cooperative modeling approach for freshwater beaches impacted by point sources in which insights derived from mechanistic modeling were used to further improve the statistical models and vice versa. The statistical models provided a basis for assessing the mechanistic models which were further improved using probability distributions to generate high-resolution time series data at the source, long-term “tracer” transport modeling based on observed electrical conductivity, better assimilation of meteorological data, and the use of unstructured-grids to better resolve nearshore features. This approach resulted in improved models of comparable performance for both classes including a parsimonious statistical model suitable for real-time predictions based on an easily measurable environmental variable (turbidity). The modeling approach outlined here can be used at other sites impacted by point sources and has the potential to improve water quality predictions resulting in more accurate estimates of beach closures.

Lake Michigan, Ogden Dunes↗

EAARL coastal topography-western Florida, post-Hurricane Charley, 2004: seamless (bare earth and submerged.

Project Description These remotely sensed, geographically referenced elevation measurements of lidar-derived seamless (bare-earth and submerged) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Coastal and Marine Geology Program (CMGP), St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the western Florida coastline beachface, acquired post-Hurricane Charley on August 17 and 18, 2004. The datasets are made available for use as a management tool to research scientists and natural-resource managers. An innovative airborne lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multispectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for sub-meter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then processed using the Airborne Lidar Processing System (ALPS), a custom-built processing system developed in a NASA-USGS collaboration. ALPS supports the exploration and processing of lidar data in an interactive or batch mode. Modules for presurvey flight-line definition, flight-path plotting, lidar raster and waveform investigation, and digital camera image playback have been developed. Processing algorithms have been developed to extract the range to the first and last significant return within each waveform. ALPS is used routinely to create maps that represent submerged or sub-aerial topography. Specialized filtering algorithms have been implemented to determine the 'bare earth' under vegetation. For more information about similar projects, please visit the Decision Support for Coastal Science and Management website. Selected References Brock, J.C., Wright, C.W., Sallenger, A.H., Krabill, W.B., and Swift, R.N., 2002, Basis and methods of NASA airborne topographic mapper Lidar surveys for coastal studies: Journal of Coastal Research, v. 18, no. 1, p. 1-13. Crane, Michael, Clayton, Tonya, Raabe, Ellen, Stoker, Jason, Handley, Larry, Bawden, Gerald, Morgan, Karen, and Queija, Vivian, 2004, Report of the U.S. Geological Survey Lidar workshop sponsored by the Land Remote Sensing Program and held in St. Petersburg, FL, November 2002: U.S. Geological Survey Open-File Report 2004-1456, 72 p. Nayegandhi, Amar, Brock, J.C., and Wright, C.W., 2009, Small-footprint, waveform-resolving Lidar estimation of submerged and sub-canopy topography in coastal environments: International Journal of Remote Sensing, v. 30, no. 4, p. 861-878. Sallenger, A.H., Wright, C.W., and Lillycrop, Jeff, 2005, Coastal impacts of the 2004 hurricanes measured with airborne Lidar; initial results: Shore and Beach, v. 73, nos. 2-3, p. 10-14. Resources Included Readme.txt File

Data Series↗

Remote sensing enables basin-scale inventories of coal mine methane

Underground coal mines are important global sources of methane, but emission estimates are uncertain. We show that emission estimates for individual mines from aircraft remote-sensing surveys in the United States agree within 40% with direct measurements used for national emission reporting (IPCC Tier 3 estimate). Such direct measurements are unavailable in most countries, which rely on estimated emission factors (EFs) applied to coal-production rates. We find that EFs from IPCC Tier 1 and the Model for Calculating Coal Mine Methane (MC2M) methods overestimate U.S. emissions 3-fold due to incorrect dependence on mine depth. An IPCC Tier 2 method using measured basin-specific mine gas content agrees with direct emission measurements but does not account for gob well emissions and requires gas content data that are generally unavailable. We show that aircraft remote sensing for a small sample of mines can successfully estimate basin-specific EFs for ventilation shafts and gob wells, enabling estimates of basin- and national-scale emissions. We discuss how the method can be applied with satellite remote sensing to quantify coal emissions worldwide.

Alabama, Colorado, Kentucky, New Mexico, Ohio, Pen↗

Pesticides in U.S. streams and groundwater

A 10­-year study by the U.S. Geological Survey’s (USGS’s) National Water-­Quality Assessment (NAWQA) Program provides a national-­scale view of pesticide occurrence in streams and groundwater. The 1992-2001 study builds upon a preliminary analysis from NAWQA’s first phase of studies during 1992-1996 (1, 2). Pesticide data available from various studies prior to 1992 did not allow national assessment because of limited and variable geographic coverage (usually focusing on individual states or regions), sparse and inconsistent inclusion of pesticides in use, and variable sampling designs (3-5). The expanded geographic coverage and improved data following 10 years of study (Figure 1) confirm and reinforce previously reported findings and enable more detailed analyses of each topic. This article summarizes selected findings from a comprehensive report (6), with a focus on the nature of pesticide occurrence and potential significance to human health and stream ecosystems. Information on study design and methods as well as additional analysis of geographic patterns and trends in relation to use and management practices are available in the full report (6).

Environmental Science & Technology↗

Application of a rule-based model to estimate mercury exchange for three background biomes in the continental United States

Ecosystems that have low mercury (Hg) concentrations (i.e., not enriched or impactedbygeologic or anthropogenic processes) cover most of the terrestrial surface area of the earth yet their role as a net source or sink for atmospheric Hg is uncertain. Here we use empirical data to develop a rule-based model implemented within a geographic information system framework to estimate the spatial and temporal patterns of Hg flux for semiarid deserts, grasslands, and deciduous forests representing 45% of the continental United States. This exercise provides an indication of whether these ecosystems are a net source or sink for atmospheric Hg as well as a basis for recommendation of data to collect in future field sampling campaigns. Results indicated that soil alone was a small net source of atmospheric Hg and that emitted Hg could be accounted for based on Hg input by wet deposition. When foliar assimilation and wet deposition are added to the area estimate of soil Hg flux these biomes are a sink for atmospheric Hg. ?? 2009 American Chemical Society.

Environmental Science & Technology↗

Harnessing big data to rethink land heterogeneity in Earth system models

The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth system models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and computational constraints, these data are underused for global applications. As a proof of concept, this study explores how to effectively and efficiently harness these data in Earth system models over a 1/4° ( ∼ 25 km) grid cell in the western foothills of the Sierra Nevada in central California. First, a novel hierarchical multivariate clustering approach (HMC) is introduced that summarizes the high-dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this clustering approach impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled using HMC. The results over the test domain show that (1) the observed similarity over the landscape makes it possible to converge on the macroscale response of the fully distributed model with around 300 sub-grid land model tiles; (2) assembling the sub-grid tile configuration from available environmental data can have a large impact on the macroscale states and fluxes of the water, energy, and carbon cycles; for example, the defined subsurface connections between the tiles lead to a dampening of macroscale extremes; (3) connecting the fine-scale grid to the model tiles via HMC enables circumvention of the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth system models.

Hydrology and Earth System Sciences↗

Methods used for the collection and analysis of chemical and biological data for the Tapwater Exposure Study, United States, 2016–17

In 2016, the U.S. Geological Survey (USGS) Environmental Health Mission Area, initiated the Tapwater Exposure Study as part of an infrastructure project to assess human exposure to potential threats from complex mixtures of contaminants. In the pilot phase (2016), samples were collected from 11 States throughout the United States, and in the second phase (2017), the study focused on the Greater Chicago area, including North and South Chicago, Illinois, and East Chicago, Indiana. Residential tapwater samples were collected at private residences during both phases, and during the first phase, samples were collected from Federal office buildings and from one office 19-liter water-bottle source. During the second phase, raw intake and treated (pre-distributional) water samples also were collected from four drinking-water treatment facilities in the Greater Chicago area. Samples were sent to laboratories at the USGS, U.S. Environmental Protection Agency, National Institute of Environmental Health Sciences, and Colorado School of Mines Center for Environmental Risk Assessment, for potential drinking-water pathogens, chemical, and bioassay analyses. These analyses included more than 400 chemicals such as trace elements, steroid hormones, pharmaceuticals, volatile organic compounds, pesticides, per- and polyfluorinated alkyl substances, cyanotoxins, and other organic compounds. The in vitro bioassay analyses included estrogen, androgen, and glucocorticoid receptor activity.

Open-File Report↗

Direct photolysis rates and transformation pathways of the lampricides TFM and niclosamide in simulated sunlight

The lampricides 3-trifluoromethyl-4-nitrophenol (TFM) and 2′,5-dichloro-4′-nitrosalicylanilide (niclosamide) are directly added to many tributaries of the Great Lakes that harbor the invasive parasitic sea lamprey. Despite their long history of use, the fate of lampricides is not well understood. This study evaluates the rate and pathway of direct photodegradation of both lampricides under simulated sunlight. The estimated half-lives of TFM range from 16.6 ± 0.2 h (pH 9) to 32.9 ± 1.0 h (pH 6), while the half-lives of niclosamide range from 8.88 ± 0.52 days (pH 6) to 382 ± 83 days (pH 9) assuming continuous irradiation over a water depth of 55 cm. Both compounds degrade to form a series of aromatic intermediates, simple organic acids, ring cleavage products, and inorganic ions. Experimental data were used to construct a kinetic model which demonstrates that the aromatic products of TFM undergo rapid photolysis and emphasizes that niclosamide degradation is the rate-limiting step to dehalogenation and mineralization of the lampricide. This study demonstrates that TFM photodegradation is likely to occur on the time scale of lampricide applications (2–5 days), while niclosamide, the less selective lampricide, will undergo minimal direct photodegradation during its passage to the Great Lakes.

Environmental Science & Technology↗

Response to comment on "Pharmaceuticals, hormones, and other organic wastewater contaminants in U.S. streams, 1999-2000: A national reconnaissance"

We thank Ericson et al. (1) for their careful review and thoughtful comments on the synthetic hormone data presented in our recent publication summarizing the results from the USGS nationwide reconnaissance for pharmaceuticals and other organic wastewater contaminants (2). Their efforts have helped raise the awareness of the difficulties in accurately measuring these compounds at the low concentrations that occur in the environment and reinforce the need for continued research in the area of analytical methods development for synthetic hormones

Environmental Science & Technology↗

A fresh look at road salt: Aquatic toxicity and water-quality impacts on local, regional, and national scales

A new perspective on the severity of aquatic toxicity impact of road salt was gained by a focused research effort directed at winter runoff periods. Dramatic impacts were observed on local, regional, and national scales. Locally, samples from 7 of 13 Milwaukee, Wisconsin area streams exhibited toxicity in Ceriodaphnia dubia and Pimephales promelas bioassays during road-salt runoff. Another Milwaukee stream was sampled from 1996 to 2008 with 72% of 37 samples exhibiting toxicity in chronic bioassays and 43% in acute bioassays. The maximum chloride concentration was 7730 mg/L. Regionally, in southeast Wisconsin, continuous specific conductance was monitored as a chloride surrogate in 11 watersheds with urban land use from 6.0 to 100%. Elevated specific conductance was observed between November and April at all sites, with continuing effects between May and October at sites with the highest specific conductance. Specific conductance was measured as high as 30 800 ??S/cm (Cl = 11 200 mg/L). Chloride concentrations exceeded U.S. Environmental Protection Agency (USEPA) acute (860 mg/L) and chronic (230 mg/L) water-quality criteria at 55 and 100% of monitored sites, respectively. Nationally, U.S. Geological Survey historical data were examined for 13 northern and 4 southern metropolitan areas. Chloride concentrations exceeded USEPA water-quality criteria at 55% (chronic) and 25% (acute) of the 168 monitoring locations in northern metropolitan areas from November to April. Only 16% (chronic) and 1% (acute) of sites exceeded criteria from May to October. At southern sites, very few samples exceeded chronic water-quality criteria, and no samples exceeded acute criteria. ?? 2010 American Chemical Society.

Environmental Science & Technology↗

Risk of nitrate in groundwaters of the United States - A national perspective

Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as 'input' factors (population density end the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and 'aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.Nitrate contamination of groundwater occurs in predictable patterns, based on findings of the U.S. Geological Survey's (USGS) National Water Quality Assessment (NAWQA) Program. The NAWQA Program was begun in 1991 to describe the quality of the Nation's water resources, using nationally consistent methods. Variables affecting nitrate concentration in groundwater were grouped as `input' factors (population density and the amount of nitrogen contributed by fertilizer, manure, and atmospheric sources) and `aquifer vulnerability' factors (soil drainage characteristic and the ratio of woodland acres to cropland acres in agricultural areas) and compiled in a national map that shows patterns of risk for nitrate contamination of groundwater. Areas with high nitrogen input, well-drained soils, and low woodland to cropland ratio have the highest potential for contamination of shallow groundwater by nitrate. Groundwater nitrate data collected through 1992 from wells less than 100 ft deep generally verified the risk patterns shown on the national map. Median nitrate concentration was 0.2 mg/L in wells representing the low-risk group, and the maximum contaminant level (MCL) was exceeded in 3% of the wells. In contrast, median nitrate concentration was 4.8 mg/L in wells representing the high-risk group, and the MCL was exceeded in 25% of the wells.

Environmental Science & Technology↗

A recruitment niche framework for improving seed-based restoration

As larger tracts of land experience degradation, seed-based restoration (SBR) will be a primary tool to reestablish vegetation and ecosystem function. SBR has advanced in terms of technical and technological approaches, yet plant recruitment remains a major barrier in some systems, notably drylands. There is an unmet opportunity to test science-based approaches to seed mix design and application, based not only on diversity or local provenance, but on the unique recruitment strategies of species. We lay out a framework that uses a quantitative representation of species' recruitment niches to match them to targeted goals (e.g. drought or invasion resistance) and methods (e.g. precision tools and technologies) in SBR. We first describe how to quantify the recruitment niche with seed and seedling traits tied to observed recruitment responses to environmental factors. We then show how a quantified recruitment niche framework can serve as the foundation to address three major restoration challenges: (1) designing forward-looking seed mixes that increase resilience to future climate and disturbance, (2) accounting for natural recovery in SBR planning, and (3) applying precision seeding practices to maximize restoration success. Finally, we demonstrate these ideas with existing data and discuss key challenges to adoption in SBR practice. While the ideas in this framework are based in ecological theory, they will require substantial testing and refinement by scientists engaged in SBR efforts. If this framework is integrated into research agendas, we believe it has the potential to unify and advance diverse elements of seed-based restoration ecology and improve restoration outcomes.

Restoration Ecology↗

INVASIVESNET towards an International Association for Open Knowledge on Invasive Alien Species

In a world where invasive alien species (IAS) are recognised as one of the major threats to biodiversity, leading scientists from five continents have come together to propose the concept of developing an international association for open knowledge and open data on IAS—termed “INVASIVESNET”. This new association will facilitate greater understanding and improved management of invasive alien species (IAS) and biological invasions globally, by developing a sustainable network of networks for effective knowledge exchange. In addition to their inclusion in the CBD Strategic Plan for Biodiversity, the increasing ecological, social, cultural and economic impacts associated with IAS have driven the development of multiple legal instruments and policies. This increases the need for greater co-ordination, co-operation, and information exchange among scientists, management, the community of practice and the public. INVASIVESNET will be formed by linking new and existing networks of interested stakeholders including international and national expert working groups and initiatives, individual scientists, database managers, thematic open access journals, environmental agencies, practitioners, managers, industry, non-government organisations, citizens and educational bodies. The association will develop technical tools and cyberinfrastructure for the collection, management and dissemination of data and information on IAS; create an effective communication platform for global stakeholders; and promote coordination and collaboration through international meetings, workshops, education, training and outreach. To date, the sustainability of many strategic national and international initiatives on IAS have unfortunately been hampered by time-limited grants or funding cycles. Recognising that IAS initiatives need to be globally coordinated and ongoing, we aim to develop a sustainable knowledge sharing association to connect the outputs of IAS research and to inform the consequential management and societal challenges arising from IAS introductions. INVASIVESNET will provide a dynamic and enduring network of networks to ensure the continuity of connections among the IAS community of practice, science and management.

Management of Biological Invasions↗