Search for: All records

Despite long‐standing theory for classifying plant ecological strategies, limited data directly link organismal traits to whole‐plant growth rates (GRs). We compared trait‐growth relationships based on three prominent theories: growth analysis, Grime's competitive–stress tolerant–ruderal (CSR) triangle, and the leaf economics spectrum (LES). Under these schemes, growth is hypothesized to be predicted by traits related to relative biomass investment, leaf structure, or gas exchange, respectively. We also considered traits not included in these theories but that might provide potential alternative best predictors of growth. In phylogenetic analyses of 30 diverse milkweeds (Asclepiasspp.) and 21 morphological and physiological traits, GR (total biomass produced per day) varied 50‐fold and was best predicted by biomass allocation to leaves (as predicted by growth analysis) and the CSR traits of leaf size and leaf dry matter content. Total leaf area (LA) and plant height were also excellent predictors of whole‐plant GRs. Despite two LES traits correlating with growth (mass‐based leaf nitrogen and area‐based leaf phosphorus contents), these were in the opposite direction of that predicted by LES, such that higher N and P contents corresponded to slower growth. The remaining LES traits (e.g., leaf gas exchange) were not predictive of plant GRs. Overall, differences in GR were driven more by whole‐plant characteristics such as biomass fractions and total LA than individual leaf‐level traits such as photosynthetic rate or specific leaf area. Our results are most consistent with classical growth analysis—combining leaf traits with whole‐plant allocation to best predict growth. However, given that destructive biomass measures are often not feasible, applying easy‐to‐measure leaf traits associated with the CSR classification appear more predictive of whole‐plant growth than LES traits. Testing the generality of this result across additional taxa would further improve our ability to predict whole‐plant growth from functional traits across scales.

 

Sea star wasting (SSW) disease describes a condition affecting asteroids that resulted in significant Northeastern Pacific population decline following a mass mortality event in 2013. The etiology of SSW is unresolved. We hypothesized that SSW is a sequela of microbial organic matter remineralization near respiratory surfaces, one consequence of which may be limited O 2 availability at the animal-water interface. Microbial assemblages inhabiting tissues and at the asteroid-water interface bore signatures of copiotroph proliferation before SSW onset, followed by the appearance of putatively facultative and strictly anaerobic taxa at the time of lesion genesis and as animals died. SSW lesions were induced in Pisaster ochraceus by enrichment with a variety of organic matter (OM) sources. These results together illustrate that depleted O 2 conditions at the animal-water interface may be established by heterotrophic microbial activity in response to organic matter loading. SSW was also induced by modestly (∼39%) depleted O 2 conditions in aquaria, suggesting that small perturbations in dissolved O 2 may exacerbate the condition. SSW susceptibility between species was significantly and positively correlated with surface rugosity, a key determinant of diffusive boundary layer thickness. Tissues of SSW-affected individuals collected in 2013–2014 bore δ 15 N signatures reflecting anaerobic processes, which suggests that this phenomenon may have affected asteroids during mass mortality at the time. The impacts of enhanced microbial activity and subsequent O 2 diffusion limitation may be more pronounced under higher temperatures due to lower O 2 solubility, in more rugose asteroid species due to restricted hydrodynamic flow, and in larger specimens due to their lower surface area to volume ratios which affects diffusive respiratory potential. 

The fundamental tradeoff between carbon gain and water loss has long been predicted as an evolutionary driver of plant strategies across environments. Nonetheless, challenges in measuring carbon gain and water loss in ways that integrate over leaf lifetime have limited our understanding of the variation in and mechanistic bases of this tradeoff. Furthermore, the microevolution of plant traits within species versus the macroevolution of strategies among closely related species may not be the same, and accordingly, the latter must be addressed using comparative phylogenetic analyses.

Here we introduce the concept of ‘integrated metabolic strategy’ (IMS) to describe the ratio between carbon isotope composition (δ¹³C) and oxygen isotope composition above source water (Δ¹⁸O) of leaf cellulose. IMS is a measure of leaf‐level conditions that integrate several mechanisms contributing to carbon gain (δ¹³C) and water loss (Δ¹⁸O) over leaf lifespan, with larger values reflecting higher metabolic efficiency and hence less of a tradeoff. We tested how IMS evolves among closely related yet ecologically diverse milkweed species, and subsequently addressed phenotypic plasticity in response to water availability in species with divergent IMS.

Integrated metabolic strategy varied strongly among 20Asclepiasspecies when grown under controlled conditions, and phylogenetic analyses demonstrate species‐specific tradeoffs between carbon gain and water loss. Larger IMS values were associated with species from dry habitats, with larger carboxylation capacity, smaller stomatal conductance and smaller leaves; smaller IMS was associated with wet habitats, smaller carboxylation capacity, larger stomatal conductance and larger leaves. The evolution of IMS was dominated by changes in species’ demand for carbon (δ¹³C) more so than water conservation (Δ¹⁸O). Although some individual physiological traits showed phylogenetic signal, IMS did not.

In response to experimental decreases in soil moisture, three species maintained similar IMS across levels of water availability because of proportional increases inδ¹³C and Δ¹⁸O (or little change in either), while one species increased IMS due to disproportional changes inδ¹³C relative to Δ¹⁸O.

Synthesis.IMS is a broadly applicable mechanistic tool; IMS variation among and within species may shed light on unresolved questions relating to the evolution and ecology of plant ecophysiological strategies.

 

Abstract. Methane (CH4) emissions from natural landscapes constituteroughly half of global CH4 contributions to the atmosphere, yet largeuncertainties remain in the absolute magnitude and the seasonality ofemission quantities and drivers. Eddy covariance (EC) measurements ofCH4 flux are ideal for constraining ecosystem-scale CH4emissions due to quasi-continuous and high-temporal-resolution CH4flux measurements, coincident carbon dioxide, water, and energy fluxmeasurements, lack of ecosystem disturbance, and increased availability ofdatasets over the last decade. Here, we (1) describe the newly publisheddataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset ofCH4 EC measurements (available athttps://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4includes half-hourly and daily gap-filled and non-gap-filled aggregatedCH4 fluxes and meteorological data from 79 sites globally: 42freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drainedecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverageglobally because the majority of sites in FLUXNET-CH4 Version 1.0 arefreshwater wetlands which are a substantial source of total atmosphericCH4 emissions; and (3) we provide the first global estimates of theseasonal variability and seasonality predictors of freshwater wetlandCH4 fluxes. Our representativeness analysis suggests that thefreshwater wetland sites in the dataset cover global wetland bioclimaticattributes (encompassing energy, moisture, and vegetation-relatedparameters) in arctic, boreal, and temperate regions but only sparselycover humid tropical regions. Seasonality metrics of wetland CH4emissions vary considerably across latitudinal bands. In freshwater wetlands(except those between 20∘ S to 20∘ N) the spring onsetof elevated CH4 emissions starts 3 d earlier, and the CH4emission season lasts 4 d longer, for each degree Celsius increase in meanannual air temperature. On average, the spring onset of increasing CH4emissions lags behind soil warming by 1 month, with very few sites experiencingincreased CH4 emissions prior to the onset of soil warming. Incontrast, roughly half of these sites experience the spring onset of risingCH4 emissions prior to the spring increase in gross primaryproductivity (GPP). The timing of peak summer CH4 emissions does notcorrelate with the timing for either peak summer temperature or peak GPP.Our results provide seasonality parameters for CH4 modeling andhighlight seasonality metrics that cannot be predicted by temperature or GPP(i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resourcefor diagnosing and understanding the role of terrestrial ecosystems andclimate drivers in the global CH4 cycle, and future additions of sitesin tropical ecosystems and site years of data collection will provide addedvalue to this database. All seasonality parameters are available athttps://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021).Additionally, raw FLUXNET-CH4 data used to extract seasonality parameterscan be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a completelist of the 79 individual site data DOIs is provided in Table 2 of this paper.