ORCID Profile
0000-0003-0585-0832
Current Organisations
Washingston State Department of Ecology
,
Auburn University
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Publisher: Elsevier BV
Date: 04-2022
DOI: 10.1016/J.TREE.2021.12.002
Abstract: The International Union for Conservation of Nature (IUCN) Red List of Threatened Species is central in bio ersity conservation, but insufficient resources h er its long-term growth, updating, and consistency. Models or automated calculations can alleviate those challenges by providing standardised estimates required for assessments, or prioritising species for (re-)assessments. However, while numerous scientific papers have proposed such methods, few have been integrated into assessment practice, highlighting a critical research-implementation gap. We believe this gap can be bridged by fostering communication and collaboration between academic researchers and Red List practitioners, and by developing and maintaining user-friendly platforms to automate application of the methods. We propose that developing methods better encompassing Red List criteria, systems, and drivers is the next priority to support the Red List.
Publisher: Wiley
Date: 15-08-2018
DOI: 10.1111/DDI.12831
Publisher: American Geophysical Union (AGU)
Date: 29-11-2021
DOI: 10.1029/2021GL095264
Abstract: We synthesized N 2 O emissions over North America using 17 bottom‐up (BU) estimates from 1980–2016 and five top‐down (TD) estimates from 1998 to 2016. The BU‐based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007–2016, North American N 2 O emissions are estimated at 1.7 (1.0–3.0) Tg N yr −1 (BU) and 1.3 (0.9–1.5) Tg N yr −1 (TD). Anthropogenic emissions were twice as large as natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process‐based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories.
Publisher: MDPI AG
Date: 09-2022
DOI: 10.3390/D14090723
Abstract: Global bio ersity decline is continuing largely unabated. The International Union for Conservation of Nature (IUCN) Red List of Threatened Species (hereafter, Red List) provides us with the gold standard for assessments, but taxonomic coverage, especially for invertebrates and fungi, remains very low. Many players contribute to the Red List knowledge base, especially IUCN Red List partners, IUCN-led assessment projects, and the Specialist Groups and Red List Authorities (RLA) of the IUCN Species Survival Commission. However, it is vital that we develop the next generation of contributors and bring in new, erse voices to build capacity and to sustain the huge assessment effort required to fill data gaps. Here, we discuss a recently established partner network to build additional capacity for species assessments, by linking academia directly into the assessment processes run by Specialist Groups and RLAs. We aim to increase Red List “literacy” amongst potential future conservationists and help students to increase publication output, form professional networks, and develop writing and research skills. Professors can build Red List learning into their teaching and offer Red Listing opportunities to students as assignments or research projects that directly contribute to the Red List. We discuss the opportunities presented by the approach, especially for underrepresented species groups, and the challenges that remain.
Publisher: Springer Science and Business Media LLC
Date: 06-01-2020
Publisher: Wiley
Date: 02-08-2021
Publisher: American Geophysical Union (AGU)
Date: 02-2019
DOI: 10.1029/2018GB006091
Publisher: Springer Science and Business Media LLC
Date: 12-09-2021
Publisher: American Geophysical Union (AGU)
Date: 06-2022
DOI: 10.1029/2022GB007347
Abstract: Phosphorus (P) control is critical to mitigating eutrophication in aquatic ecosystems, but the effectiveness of controlling P export from soils has been limited by our poor understanding of P dynamics along the land‐ocean aquatic continuum as well as the lack of well‐developed process models that effectively couple terrestrial and aquatic biogeochemical P processes. Here, we coupled riverine P biogeochemical processes and water transport with terrestrial processes within the framework of the Dynamic Land Ecosystem Model to assess how multiple environmental changes, including fertilizer and manure P uses, land use, climate, and atmospheric CO 2 , have affected the long‐term dynamics of P loading and export from the Mississippi River Basin to the Gulf of Mexico during 1901–2018. Simulations show that riverine exports of dissolved inorganic phosphorus (DIP), dissolved organic phosphorus, particulate organic phosphorus (POP), and particulate inorganic phosphorus (PIP) increased by 42%, 53%, 60%, and 53%, respectively, since the 1960s. Riverine DIP and PIP exports were the dominant components of the total P flux. DIP export was mainly enhanced by the growing mineral P fertilizer use in croplands, while increased PIP and POP exports were a result of the intensified soil erosion due to increased precipitation. Climate variability resulted in substantial interannual and decadal variations in P loading and export. Soil legacy P continues to contribute to P loading. Our findings highlight the necessity to adopt effective P management strategies to control P losses through reductions in soil erosion, and additionally, to improve P use efficiency in crop production.
Publisher: Wiley
Date: 08-03-2021
DOI: 10.1111/COBI.13715
Abstract: The International Union for Conservation of Nature's Red List of Threatened Species (RLS) is the key global tool for objective, repeatable assessment of species’ extinction risk status, and plays an essential role in tracking bio ersity loss and guiding conservation action. Satellite remote sensing (SRS) data sets on global ecosystem distributions and functioning show exciting potential for informing range‐based RLS assessment, but their incorporation has been restricted by low temporal resolution and coverage of data sets, lack of incorporation of degradation‐driven habitat loss, and noninclusion of assumptions related to identification of changing habitat distributions for taxa with varying habitat dependency and ecologies. For poorly known mangrove‐associated Cuban hutias ( Mesocapromys spp.), we tested the impact of possible assumptions regarding these issues on range‐based RLS assessment outcomes. Specifically, we used annual (1985–2018) Landsat data and land‐cover classification and habitat degradation analyses across different internal time series slices to simulate range‐based RLS assessments for our case study taxa to explore potential assessment uncertainty arising from temporal SRS data set coverage, incorporating proxies of (change in) habitat quality, and assumptions on spatial scaling of habitat extent for RLS parameter generation. We found extensive variation in simulated species‐specific range‐based RLS assessments, and this variation was mostly associated with the time series over which parameters were estimated. However, results of some species‐specific assessments differed by up to 3 categories (near threatened to critically endangered) within the same time series, due to the effects of incorporating habitat quality and the spatial scaling used in RLS parameter estimation. Our results showed that a one‐size‐fits‐all approach to incorporating SRS information in RLS assessment is inappropriate, and we urge caution in conducting range‐based assessments with SRS for species for which habitat dependence on specific ecosystem types is incompletely understood. We propose novel revisions to parameter spatial scaling guidelines to improve integration of existing time series data on ecosystem change into the RLS assessment process.
Publisher: Springer Science and Business Media LLC
Date: 08-02-2020
Publisher: Wiley
Date: 17-12-2019
DOI: 10.1111/GCB.14514
Abstract: Our understanding and quantification of global soil nitrous oxide (N
Location: United States of America
No related grants have been discovered for Monika Bohm.