Ectoenzyme kinetics in Florida Bay: Implications for bacterial carbon source and nutrient status

Ectoenzyme kinetics [alkaline phosphatase, aminopeptidase (AM), lipase, α-glucosidase, and β-glucosidase] were determined over a seasonal cycle at four stations, Little Madeira Bay (northeast), Duck Key (east), Bob Allen Key (south-central), and Whipray Basin (north-central), which represent distinct regions of Florida Bay. Spatial and temporal variations in ectoenzyme kinetics were related to biotic and abiotic drivers in order to discern potential ectoenzyme substrate sources. Generally, ectoenzyme activities were higher in the central bay and lowest in the eastern bay. One pronounced exception was AM activity, which was highest at the mangrove fringe along the northeastern bay and reflected increased contribution of organic nitrogen inputs from upstream Everglades wetlands. When ectoenzymes were normalized to bacterial abundances, these trends dissipated and highest cell-specific activities were observed consistently in the south-central region. Relationships between ectoenzyme kinetics and environmental and biological parameters were complex, but three main spatially determined differences were discernable. Ectoenzyme kinetics were controlled by phosphorus availability in the eastern bay, by organic matter availability in the south-central bay, by microbial community composition and organic matter availability in northeastern bay (wetlands transition area), and by microbial community composition in the north-central bay. These differences in enzyme kinetics further support the hypothesis of distinct microbial communities in different regions of Florida Bay and provide insight into biogeochemical cycles and the microbial food web within Florida Bay.     

Metapopulation shift and survival of woodland birds under climate change: will species be able to track?

Climate change has been widely recognized as a key factor driving changes in species distributions. In this study we use a metapopulation model, with a window of suitable climate moving polewards, to explore population shifts and survival of woodland birds under different climate change scenarios and landscape configurations. Extinction vulnerability and expansion ability are predicted for the middle spotted woodpecker Dendrocopus medius and two alternative r‐K strategies under west European climate change scenarios of 1, 2 and 4°C temperature increase per century, corresponding to isotemperature velocities of ca 2, 4 and 8 km yr^?1. The simulated northward expansion of the bird's distribution is typically in the range of only 0–3 km yr^?1, in spite of 10–20 times larger maximum dispersal distances. This is too slow to track the climate change‐driven range contraction of 4 or 8 km yr^?1 in the south resulting in metapopulation extinction. Especially K‐selected (large‐bodied) species are vulnerable in the simulations. With a temperature increase of 4°C per century bird species go extinct within 104–178 yr. We present a simple approximation formula to predict the mean time to metapopulation extinction using 1) the rate of climate change, which determines the speed of range contraction in the south, 2) the size of the distribution range, which serves as a buffer against extinction, and 3) the northward expansion velocity, determined by species traits and landscape properties. Finally, our results indicate that the northward expansion rate is not constant. It will be initially lagged suggesting that recently observed expansion rates might be underestimations of future northward expansion rates.     

Light from below matters: Quantifying the consequences of responses to far‐red light reflected upwards for plant performance in heterogeneous canopies

In vegetation stands, plants receive red to far‐red ratio (R:FR) signals of varying strength from all directions. However, plant responses to variations in R:FR reflected from below have been largely ignored despite their potential consequences for plant performance. Using a heterogeneous rose canopy, which consists of bent shoots down in the canopy and vertically growing upright shoots, we quantified upward far‐red reflection by bent shoots and its consequences for upright shoot architecture. With a three‐dimensional plant model, we assessed consequences of responses to R:FR from below for plant photosynthesis. Bent shoots reflected substantially more far‐red than red light, causing reduced R:FR in light reflected upwards. Leaf inclination angles increased in upright shoots which received low R:FR reflected from below. The increased leaf angle led to an increase in simulated plant photosynthesis only when this low R:FR was reflected off their own bent shoots and not when it reflected off neighbour bent shoots. We conclude that plant response to R:FR from below is an under‐explored phenomenon which may have contrasting consequences for plant performance depending on the type of vegetation or crop system. The responses are beneficial for performance only when R:FR is reflected by lower foliage of the same plants.     

Altering drug tolerance of surface plasmon resonance assays for the detection of anti-drug antibodies

Anti-drug antibody (ADA) responses are a concern for both drug efficacy and safety, and high drug concentrations in patient samples may inhibit ADA assays. We evaluated strategies to improve drug tolerance of surface plasmon resonance (SPR) assays that detect ADAs against a bispecific Adnectin drug molecule that consists of an anti-VEGFR2 domain linked to an anti-IGF-1R domain (V-I-Adnectin). Samples containing ADAs against V-I-Adnectin and various drug concentrations were tested in the presence of 1 M guanidine hydrochloride (Gdn), at pH values ranging from 4.5 to 7.4 and temperatures of up to 37 °C. Temperature had a negligible effect in weakening the affinity of interaction of monoclonal antibodies with polyethylene glycol(PEG)–V-I-Adnectin and did not increase drug tolerance of the ADA assay. Low pH increased drug tolerance of the assay relative to pH 7.4 but caused nonspecific binding of the drug during competition experiments. The chaotropic agent Gdn lowered the affinity of interaction between an anti-V-Adnectin monoclonal antibody and the drug (from K_D = 0.93 nM to K_D = 348 nM). That decrease in the affinity of drug–ADA interaction correlated with an increase of assay drug tolerance. Conditions that lower drug–ADA interaction affinity could also be used to develop drug-tolerant SPR assays for other systems.     

Partitioning net carbon dioxide fluxes into photosynthesis and respiration using neural networks

The eddy covariance (EC) technique is used to measure the net ecosystem exchange (NEE) of CO₂ between ecosystems and the atmosphere, offering a unique opportunity to study ecosystem responses to climate change. NEE is the difference between the total CO₂ release due to all respiration processes (RECO), and the gross carbon uptake by photosynthesis (GPP). These two gross CO₂ fluxes are derived from EC measurements by applying partitioning methods that rely on physiologically based functional relationships with a limited number of environmental drivers. However, the partitioning methods applied in the global FLUXNET network of EC observations do not account for the multiple co‐acting factors that modulate GPP and RECO flux dynamics. To overcome this limitation, we developed a hybrid data‐driven approach based on combined neural networks (NN_C‐part). NN_C‐part incorporates process knowledge by introducing a photosynthetic response based on the light‐use efficiency (LUE) concept, and uses a comprehensive dataset of soil and micrometeorological variables as fluxes drivers. We applied the method to 36 sites from the FLUXNET2015 dataset and found a high consistency in the results with those derived from other standard partitioning methods for both GPP (R² > .94) and RECO (R² > .8). High consistency was also found for (a) the diurnal and seasonal patterns of fluxes and (b) the ecosystem functional responses. NN_C‐part performed more realistic than the traditional methods for predicting additional patterns of gross CO₂ fluxes, such as: (a) the GPP response to VPD, (b) direct effects of air temperature on GPP dynamics, (c) hysteresis in the diel cycle of gross CO₂ fluxes, (d) the sensitivity of LUE to the diffuse to direct radiation ratio, and (e) the post rain respiration pulse after a long dry period. In conclusion, NN_C‐part is a valid data‐driven approach to provide GPP and RECO estimates and complementary to the existing partitioning methods.     

Rubisco Adaptation Is More Limited by Phylogenetic Constraint Than by Catalytic Trade-off

Rubisco assimilates CO₂ to form the sugars that fuel life on earth. Correlations between rubisco kinetic traits across species have led to the proposition that rubisco adaptation is highly constrained by catalytic trade-offs. However, these analyses did not consider the phylogenetic context of the enzymes that were analyzed. Thus, it is possible that the correlations observed were an artefact of the presence of phylogenetic signal in rubisco kinetics and the phylogenetic relationship between the species that were sampled. Here, we conducted a phylogenetically resolved analysis of rubisco kinetics and show that there is a significant phylogenetic signal in rubisco kinetic traits. We re-evaluated the extent of catalytic trade-offs accounting for this phylogenetic signal and found that all were attenuated. Following phylogenetic correction, the largest catalytic trade-offs were observed between the Michaelis constant for CO₂ and carboxylase turnover (∼21–37%), and between the Michaelis constants for CO₂ and O₂ (∼9–19%), respectively. All other catalytic trade-offs were substantially attenuated such that they were marginal (<9%) or non-significant. This phylogenetically resolved analysis of rubisco kinetic evolution also identified kinetic changes that occur concomitant with the evolution of C₄ photosynthesis. Finally, we show that phylogenetic constraints have played a larger role than catalytic trade-offs in limiting the evolution of rubisco kinetics. Thus, although there is strong evidence for some catalytic trade-offs, rubisco adaptation has been more limited by phylogenetic constraint than by the combined action of all catalytic trade-offs.