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Results for “biodiversity-ecosystem function”

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3 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

AMF diversity promotes plant community phosphorus acquisition and reduces carbon costs per unit of phosphorus

Plants may benefit from more diverse communities of arbuscular mycorrhizal fungi (AMF), as functional complementarity of AMF may allow for increased resource acquisition, and because a high AMF diversity increases the probability of plants matching with an optimal AMF symbiont. Here, we repeatedly radiolabeled plants and AMF in the glasshouse over c. 9 months to test how AMF species richness (SR) influences the exchange of plant C ( 14 C) for AMF P ( 32 P & 33 P) and resulting shoot nutrients and mass from a biodiversity–ecosystem functioning perspective. Plant P acquisition via AMF increased with sown AMF SR, as did shoot biomass, shoot P, and shoot N. The rate of plant C transferred to AMF for this P (C:P) decreased with sown AMF SR. Plants in plant communities benefit from inoculation with a variety of AMF species via more favorable resource exchange. Surprisingly, this effect did not differ among functionally distinct communities comprised entirely of either legumes, nonlegume forbs, or C3 grasses.

arbuscular mycorrhizal fungi↗
DOE OSTI2020

Community structure – Ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. In this work, we test these assertions using methane (CH 4 )-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH 4 oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Increasing the Uptake of Ecological Model Results in Policy Decisions to Improve Biodiversity Outcomes

Models help decision-makers anticipate the consequences of policies for ecosystems and people; for instance, improving our ability to represent interactions between human activities and ecological systems is essential to identify pathways to meet the 2030 Sustainable Development Goals. However, use of modeling outputs in decision-making remains uncommon. We share insights from a multidisciplinary National Socio-Environmental Synthesis Center working group on technical, communication, and process-related factors that facilitate or hamper uptake of model results. We emphasize that it is not simply technical model improvements, but active and iterative stakeholder involvement that can lead to more impactful outcomes. In particular, trust- and relationship-building with decision-makers are key for knowledge-based decision making. In this respect, nurturing knowledge exchange on the interpersonal (e.g., through participatory processes), and institutional level (e.g., through science-policy interfaces across scales), represent promising approaches. To this end, we offer a generalized approach for linking modeling and decision-making.

Biodiversity-ecosystem function relationships↗