Energy‐based top‐down and bottom‐up relationships between fish community energy demand or production and phytoplankton across lakes at a continental scale

2020 ◽  
Vol 65 (4) ◽  
pp. 892-902 ◽  
Author(s):  
Mireia Bartrons ◽  
Thomas Mehner ◽  
Christine Argillier ◽  
Meryem Beklioglu ◽  
Petr Blabolil ◽  
...  
2018 ◽  
Vol 18 (2) ◽  
pp. 735-756 ◽  
Author(s):  
Kelley C. Wells ◽  
Dylan B. Millet ◽  
Nicolas Bousserez ◽  
Daven K. Henze ◽  
Timothy J. Griffis ◽  
...  

Abstract. We present top-down constraints on global monthly N2O emissions for 2011 from a multi-inversion approach and an ensemble of surface observations. The inversions employ the GEOS-Chem adjoint and an array of aggregation strategies to test how well current observations can constrain the spatial distribution of global N2O emissions. The strategies include (1) a standard 4D-Var inversion at native model resolution (4° × 5°), (2) an inversion for six continental and three ocean regions, and (3) a fast 4D-Var inversion based on a novel dimension reduction technique employing randomized singular value decomposition (SVD). The optimized global flux ranges from 15.9 Tg N yr−1 (SVD-based inversion) to 17.5–17.7 Tg N yr−1 (continental-scale, standard 4D-Var inversions), with the former better capturing the extratropical N2O background measured during the HIAPER Pole-to-Pole Observations (HIPPO) airborne campaigns. We find that the tropics provide a greater contribution to the global N2O flux than is predicted by the prior bottom-up inventories, likely due to underestimated agricultural and oceanic emissions. We infer an overestimate of natural soil emissions in the extratropics and find that predicted emissions are seasonally biased in northern midlatitudes. Here, optimized fluxes exhibit a springtime peak consistent with the timing of spring fertilizer and manure application, soil thawing, and elevated soil moisture. Finally, the inversions reveal a major emission underestimate in the US Corn Belt in the bottom-up inventory used here. We extensively test the impact of initial conditions on the analysis and recommend formally optimizing the initial N2O distribution to avoid biasing the inferred fluxes. We find that the SVD-based approach provides a powerful framework for deriving emission information from N2O observations: by defining the optimal resolution of the solution based on the information content of the inversion, it provides spatial information that is lost when aggregating to political or geographic regions, while also providing more temporal information than a standard 4D-Var inversion.


Ecosystems ◽  
2017 ◽  
Vol 21 (1) ◽  
pp. 166-177 ◽  
Author(s):  
Pieter Lemmens ◽  
Steven A. J. Declerck ◽  
Karen Tuytens ◽  
Maarten Vanderstukken ◽  
Luc De Meester

2015 ◽  
Vol 112 (32) ◽  
pp. 9839-9843 ◽  
Author(s):  
Peter A. Turner ◽  
Timothy J. Griffis ◽  
Xuhui Lee ◽  
John M. Baker ◽  
Rodney T. Venterea ◽  
...  

N2O is an important greenhouse gas and the primary stratospheric ozone depleting substance. Its deleterious effects on the environment have prompted appeals to regulate emissions from agriculture, which represents the primary anthropogenic source in the global N2O budget. Successful implementation of mitigation strategies requires robust bottom-up inventories that are based on emission factors (EFs), simulation models, or a combination of the two. Top-down emission estimates, based on tall-tower and aircraft observations, indicate that bottom-up inventories severely underestimate regional and continental scale N2O emissions, implying that EFs may be biased low. Here, we measured N2O emissions from streams within the US Corn Belt using a chamber-based approach and analyzed the data as a function of Strahler stream order (S). N2O fluxes from headwater streams often exceeded 29 nmol N2O-N m−2⋅s−1 and decreased exponentially as a function of S. This relation was used to scale up riverine emissions and to assess the differences between bottom-up and top-down emission inventories at the local to regional scale. We found that the Intergovernmental Panel on Climate Change (IPCC) indirect EF for rivers (EF5r) is underestimated up to ninefold in southern Minnesota, which translates to a total tier 1 agricultural underestimation of N2O emissions by 40%. We show that accounting for zero-order streams as potential N2O hotspots can more than double the agricultural budget. Applying the same analysis to the US Corn Belt demonstrates that the IPCC EF5r underestimation explains the large differences observed between top-down and bottom-up emission estimates.


AMBIO ◽  
2021 ◽  
Author(s):  
Brian E. Reichert ◽  
Mylea Bayless ◽  
Tina L. Cheng ◽  
Jeremy T. H. Coleman ◽  
Charles M. Francis ◽  
...  

AbstractCollaborative monitoring over broad scales and levels of ecological organization can inform conservation efforts necessary to address the contemporary biodiversity crisis. An important challenge to collaborative monitoring is motivating local engagement with enough buy-in from stakeholders while providing adequate top-down direction for scientific rigor, quality control, and coordination. Collaborative monitoring must reconcile this inherent tension between top-down control and bottom-up engagement. Highly mobile and cryptic taxa, such as bats, present a particularly acute challenge. Given their scale of movement, complex life histories, and rapidly expanding threats, understanding population trends of bats requires coordinated broad-scale collaborative monitoring. The North American Bat Monitoring Program (NABat) reconciles top-down, bottom-up tension with a hierarchical master sample survey design, integrated data analysis, dynamic data curation, regional monitoring hubs, and knowledge delivery through web-based infrastructure. NABat supports collaborative monitoring across spatial and organizational scales and the full annual lifecycle of bats.


PsycCRITIQUES ◽  
2005 ◽  
Vol 50 (19) ◽  
Author(s):  
Michael Cole
Keyword(s):  
Top Down ◽  

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