skip to main content


Title: A roadmap for sampling and scaling biological nitrogen fixation in terrestrial ecosystems
Abstract

Accurately quantifying rates and patterns of biological nitrogen fixation (BNF) in terrestrial ecosystems is essential to characterize ecological and biogeochemical interactions, identify mechanistic controls, improve BNF representation in conceptual and numerical modelling, and forecast nitrogen limitation constraints on future carbon (C) cycling.

While many resources address the technical advantages and limitations of different methods for measuring BNF, less systematic consideration has been given to the broader decisions involved in planning studies, interpreting data, and extrapolating results. Here, we present a conceptual and practical road map to study design, study execution, data analysis and scaling, outlining key considerations at each step.

We address issues including defining N‐fixing niches of interest, identifying important sources of temporal and spatial heterogeneity, designing a sampling scheme (including method selection, measurement conditions, replication, and consideration of hotspots and hot moments), and approaches to analysing, scaling and reporting BNF. We also review the comparability of estimates derived using different approaches in the literature, and provide sample R code for simulating symbiotic BNF data frames and upscaling.

Improving and standardizing study design at each of these stages will improve the accuracy and interpretability of data, define limits of extrapolation, and facilitate broader use of BNF data for downstream applications. We highlight aspects—such as quantifying scales of heterogeneity, statistical approaches for dealing with non‐normality, and consideration of rates versus ecological significance—that are ripe for further development.

 
more » « less
Award ID(s):
1754126
NSF-PAR ID:
10451097
Author(s) / Creator(s):
 ;  ;  ;  ;  ;  ;  ;  ;  ;  ;  
Publisher / Repository:
Wiley-Blackwell
Date Published:
Journal Name:
Methods in Ecology and Evolution
Volume:
12
Issue:
6
ISSN:
2041-210X
Page Range / eLocation ID:
p. 1122-1137
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    The interface between field biology and technology is energizing the collection of vast quantities of environmental data. Passive acoustic monitoring, the use of unattended recording devices to capture environmental sound, is an example where technological advances have facilitated an influx of data that routinely exceeds the capacity for analysis. Computational advances, particularly the integration of machine learning approaches, will support data extraction efforts. However, the analysis and interpretation of these data will require parallel growth in conceptual and technical approaches for data analysis. Here, we use a large hand‐annotated dataset to showcase analysis approaches that will become increasingly useful as datasets grow and data extraction can be partially automated.

    We propose and demonstrate seven technical approaches for analyzing bioacoustic data. These include the following: (1) generating species lists and descriptions of vocal variation, (2) assessing how abiotic factors (e.g., rain and wind) impact vocalization rates, (3) testing for differences in community vocalization activity across sites and habitat types, (4) quantifying the phenology of vocal activity, (5) testing for spatiotemporal correlations in vocalizations within species, (6) among species, and (7) using rarefaction analysis to quantify diversity and optimize bioacoustic sampling.

    To demonstrate these approaches, we sampled in 2016 and 2018 and used hand annotations of 129,866 bird vocalizations from two forests in New Hampshire, USA, including sites in the Hubbard Brook Experiment Forest where bioacoustic data could be integrated with more than 50 years of observer‐based avian studies. Acoustic monitoring revealed differences in community patterns in vocalization activity between forests of different ages, as well as between nearby similar watersheds. Of numerous environmental variables that were evaluated, background noise was most clearly related to vocalization rates. The songbird community included one cluster of species where vocalization rates declined as ambient noise increased and another cluster where vocalization rates declined over the nesting season. In some common species, the number of vocalizations produced per day was correlated at scales of up to 15 km. Rarefaction analyses showed that adding sampling sites increased species detections more than adding sampling days.

    Although our analyses used hand‐annotated data, the methods will extend readily to large‐scale automated detection of vocalization events. Such data are likely to become increasingly available as autonomous recording units become more advanced, affordable, and power efficient. Passive acoustic monitoring with human or automated identification at the species level offers growing potential to complement observer‐based studies of avian ecology.

     
    more » « less
  2. Abstract

    Community composition is driven by a few key assembly processes: ecological selection, drift and dispersal. Nested parasite communities represent a powerful study system for understanding the relative importance of these processes and their relationship with biological scale. Quantifyingβ‐diversity across scales and over time additionally offers mechanistic insights into the ecological processes shaping the distributions of parasites and therefore infectious disease.

    To examine factors driving parasite community composition, we quantified the parasite communities of 959 amphibian hosts representing two species (the Pacific chorus frog,Pseudacris regillaand the California newt,Taricha torosa) sampled over 3 months from 10 ponds in California. Using additive partitioning, we estimated how much of regional parasite richness (γ‐diversity) was composed of within‐host parasite richness (α‐diversity) and turnover (β‐diversity) at three biological scales: across host individuals, across species and across habitat patches (ponds). We also examined howβ‐diversity varied across time at each biological scale.

    Differences among ponds comprised the majority (40%) of regional parasite diversity, followed by differences among host species (23%) and among host individuals (12%). Host species supported parasite communities that were less similar than expected by null models, consistent with ecological selection, although these differences lessened through time, likely due to high dispersal rates of infectious stages. Host individuals within the same population supported more similar parasite communities than expected, suggesting that host heterogeneity did not strongly impact parasite community composition and that dispersal was high at the individual host-level. Despite the small population sizes of within‐host parasite communities, drift appeared to play a minimal role in structuring community composition.

    Dispersal and ecological selection appear to jointly drive parasite community assembly, particularly at larger biological scales. The dispersal ability of aquatic parasites with complex life cycles differs strongly across scales, meaning that parasite communities may predictably converge at small scales where dispersal is high, but may be more stochastic and unpredictable at larger scales. Insights into assembly mechanisms within multi‐host, multi‐parasite systems provide opportunities for understanding how to mitigate the spread of infectious diseases within human and wildlife hosts.

     
    more » « less
  3. Abstract

    Understanding parasite transmission in communities requires knowledge of each species' capacity to support transmission. This property, ‘competence’, is a critical currency for modelling transmission under community change and for testing diversity–disease theory. Despite the central role of competence in disease ecology, we lack a clear understanding of the factors that generate competence and drive its variation.

    We developed novel conceptual and quantitative approaches to systematically quantify competence for a multi‐host, multi‐parasite community. We applied our framework to an extensive dataset: five amphibian host species exposed to four parasitic trematode species across five ecologically realistic exposure doses. Together, this experimental design captured 20 host–parasite interactions while integrating important information on variation in parasite exposure. Using experimental infection assays, we measured multiple components of the infection process and combined them to produce competence estimates for each interaction.

    With directly estimated competence values, we asked which components of the infection process best explained variation in competence: barrier resistance (the initial fraction of administered parasites blocked from infecting a host), internal clearance (the fraction of established parasites lost over time) or pre‐transmission mortality (the probability of host death prior to transmission). We found that variation in competence among the 20 interactions was best explained by differences in barrier resistance and pre‐transmission mortality, underscoring the importance of host resistance and parasite pathogenicity in shaping competence.

    We also produced dose‐integrated estimates of competence that incorporated natural variation in exposure to address questions on the basis and extent of variation in competence. We found strong signals that host species identity shaped competence variation (as opposed to parasite species identity). While variation in infection outcomes across hosts, parasites, individuals and doses was considerable, individual heterogeneity was limited compared to among‐species differences. This finding highlights the robustness of our competence estimates and suggests that species‐level values may be strong predictors for community‐level transmission in natural systems.

    Competence emerges from distinct underlying processes and can have strong species‐level characteristics; thus, this property has great potential for linking mechanisms of infection to epidemiological patterns.

    Read the freePlain Language Summaryfor this article on the Journal blog.

     
    more » « less
  4. Abstract

    The predicted intensification of the North American Monsoon is expected to alter growing season rainfall patterns in the southwestern United States. These patterns, which have historically been characterized by frequent small rain events, are anticipated to shift towards a more extreme precipitation regime consisting of fewer, but larger rain events. Furthermore, human activities are contributing to increased atmospheric nitrogen deposition throughout this dryland region.

    Alterations in rainfall size and frequency, along with changes in nitrogen availability, are likely to have significant consequences for above‐ground net primary production (ANPP) and plant community dynamics in drylands. The conceptual bucket model predicts that a shift towards fewer, but larger rain events could promote greater rates of ANPP in these regions by maintaining soil moisture availability above drought stress thresholds for longer periods during the growing season. However, only a few short‐term studies have tested this hypothesis, and none have explored the interaction between altered rainfall patterns and nitrogen enrichment.

    To address this knowledge gap, we conducted a 14‐year rainfall addition and nitrogen fertilization experiment in a northern Chihuahuan Desert grassland to explore the long‐term impacts of changes in monsoon rainfall size and frequency, along with chronic nitrogen enrichment, on ANPP (measured as peak biomass) and plant community dynamics.

    Contrary to bucket model predictions, small frequent rain events promoted comparable rates of ANPP to large infrequent rain events in the absence of nitrogen enrichment. It was only when nitrogen limitation was alleviated that large infrequent rain events resulted in the greatest ANPP. Furthermore, we found that nitrogen enrichment had the greatest impact on plant community composition under the small frequent rainfall regime.

    Synthesis. Our long‐term field experiment highlights limitations of the bucket model by demonstrating that water and nitrogen availability sequentially limit dryland ecological processes. Specifically, our findings suggest that while water availability is the primary limiting factor for above‐ground net primary production in these ecosystems, nitrogen limitation becomes increasingly important when water is not limiting. Moreover, our findings reveal that small frequent rain events play an important but underappreciated role in driving dryland ecosystem dynamics.

     
    more » « less
  5. Abstract

    Quantifying human impacts on the nitrogen (N) cycle and investigating natural ecosystem N cycling depend on the magnitude of inputs from natural biological nitrogen fixation (BNF). Here, we present two bottom‐up approaches to quantify tree‐based symbiotic BNF based on forest inventory data across the coterminous United States and SE Alaska. For all major N‐fixing tree genera, we quantify BNF inputs using (1) ecosystem N accretion rates (kg N ha−1yr−1) scaled with spatial data on tree abundance and (2) percent of N derived from fixation (%Ndfa) scaled with tree N demand (from tree growth rates and stoichiometry). We estimate that trees fix 0.30–0.88 Tg N yr−1across the study area (1.4–3.4 kg N ha−1yr−1). Tree‐based N fixation displays distinct spatial variation that is dominated by two genera,Robinia(64% of tree‐associated BNF) andAlnus(24%). The third most important genus,Prosopis, accounted for 5%. Compared to published estimates of other N fluxes, tree‐associated BNF accounted for 0.59 Tg N yr−1, similar to asymbiotic (0.37 Tg N yr−1) and understory symbiotic BNF (0.48 Tg N yr−1), while N deposition contributed 1.68 Tg N yr−1and rock weathering 0.37 Tg N yr−1. Overall, our results reveal previously uncharacterized spatial patterns in tree BNF that can inform large‐scale N assessments and serve as a model for improving tree‐based BNF estimates worldwide. This updated, lower BNF estimate indicates a greater ratio of anthropogenic to natural N inputs, suggesting an even greater human impact on the N cycle.

     
    more » « less