Robber-like pollinators: overwintered queen bumblebees foraging on Corydalis ambigua

ABSTRACT.

• 1 The behaviour of nectar-collecting Bombus hypocrita sapporensis Cockerell queens was observed on a population of a spring ephemeral plant Corydalis ambigua Cham, et Schlecht.
• 2 Daily patterns of activity and behaviour changed with the progress of flowering. Activity peaked shortly before sunset early in the flowering season but approximately at noon towards the end of flowering. In the peak flowering period the queens tended to visit nearby plants and to change direction often, whereas early or late in the flowering period they flew further between visits and were less likely to change direction.
• 3 Each plant was visited 0 to 24 times (mean 9.4 ±SD 5.2) by the queens during the whole flowering season.
• 4 The queens collected nectar, rarely through the front of the flowers but mostly through the spurs perforated by themselves or predecessors. At the beginning of the flowering season the illegitimate foragers often visited the front of the flowers before moving to the spurs; later, most queens quickly learned to land directly on the spurs.
• 5 Even the 59.7% of plants that were visited only by illegitimate foragers set seeds. Close observation confirmed that the illegitimate foragers opened the inner petals enclosing anthers and stigma frequently when visiting the front of the flowers before robbing, or occasionally when walking about on the flowers or collecting nectar through the perforated spurs.

     

Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 2. Carbon balance

This paper examines carbon stocks and their relative balance in terrestrial ecosystems simulated by Biome‐BGC, LPJ, and CASA in an ensemble model experiment conducted using the Terrestrial Observation and Prediction System. We developed the Hierarchical Framework for Diagnosing Ecosystem Models to separate the simulated biogeochemistry into a cascade of functional tiers and examine their characteristics sequentially. The analyses indicate that the simulated biomass is usually two to three times higher in Biome‐BGC than LPJ or CASA. Such a discrepancy is mainly induced by differences in model parameters and algorithms that regulate the rates of biomass turnover. The mean residence time of biomass in Biome‐BGC is estimated to be 40–80 years in temperate/moist climate regions, while it mostly varies between 5 and 30 years in CASA and LPJ. A large range of values is also found in the simulated soil carbon. The mean residence time of soil carbon in Biome‐BGC and LPJ is ～200 years in cold regions, which decreases rapidly with increases of temperature at a rate of ～10 yr °C^?1. Because long‐term soil carbon pool is not simulated in CASA, its corresponding mean residence time is only about 10–20 years and less sensitive to temperature. Another key factor that influences the carbon balance of the simulated ecosystem is disturbance caused by wildfire, for which the algorithms vary among the models. Because fire emissions are balanced by net ecosystem production (NEP) at steady states, magnitudes, and spatial patterns of NEP vary significantly as well. Slight carbon imbalance may be left by the spin‐up algorithm of the models, which adds uncertainty to the estimated carbon sources or sinks. Although these results are only drawn on the tested model versions, the developed methodology has potential for other model exercises.     

Tissue Distribution of an Immunogenic Melanoma Associated Antigen,D-1

A human melanoma-associated antigen immunogenic in patients was recently identified by screening an expression cDNA library constructed from cultured human melanoma cell line with sera from patients with melanoma. The nucleic acid sequence of the cloned D-1 cDNA has no significant homology with previously reported mammalian genes. The cDNA D-1 encodes a peptide of about 37 kDa, which showed fivefold higher reactivity with sera from patients with melanoma than with sera from normal donors. In order to detect D-1 gene expression in vivo, in-situ hybridization and immunostaining with cRNA probe and murine anti-D-1 sera were carried out on surgically removed tissues. Digoxigenin-labeled cRNA D-1 was exclusively hybridized with mRNA in the cytoplasm of melanoma cells but not with keratinocytes and fibroblasts adjacent to melanoma nests. Polyclonal anti-D-1 antibodies were obtained by immunization of Balb/c mice with recombinant D-1 peptide and clearly reacted with melanoma cells but not with keratinocytes and fibroblasts, similar to the results of in-situ hybridization. The above information will help to assess the suitability of recombinant D-1 peptide to implement active specific immunotherapy in patients with melanoma.     

Constraining rooting depths in tropical rainforests using satellite data and ecosystem modeling for accurate simulation of gross primary production seasonality

Accurate parameterization of rooting depth is difficult but important for capturing the spatio-temporal dynamics of carbon, water and energy cycles in tropical forests. In this study, we adopted a new approach to constrain rooting depth in terrestrial ecosystem models over the Amazon using satellite data [moderate resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI)] and Biome-BGC terrestrial ecosystem model. We simulated seasonal variations in gross primary production (GPP) using different rooting depths (1, 3, 5, and 10 m) at point and spatial scales to investigate how rooting depth affects modeled seasonal GPP variations and to determine which rooting depth simulates GPP consistent with satellite-based observations. First, we confirmed that rooting depth strongly controls modeled GPP seasonal variations and that only deep rooting systems can successfully track flux-based GPP seasonality at the Tapajos km67 flux site. Second, spatial analysis showed that the model can reproduce the seasonal variations in satellite-based EVI seasonality, however, with required rooting depths strongly dependent on precipitation and the dry season length. For example, a shallow rooting depth (1–3 m) is sufficient in regions with a short dry season (e.g. 0–2 months), and deeper roots are required in regions with a longer dry season (e.g. 3–5 and 5–10 m for the regions with 3–4 and 5–6 months dry season, respectively). Our analysis suggests that setting of proper rooting depths is important to simulating GPP seasonality in tropical forests, and the use of satellite data can help to constrain the spatial variability of rooting depth.     

Evaluating the impacts of climate and elevated carbon dioxide on tropical rainforests of the western Amazon basin using ecosystem models and satellite data

Forest inventories from the intact rainforests of the Amazon indicate increasing rates of carbon gain over the past three decades. However, such estimates have been questioned because of the poor spatial representation of the sampling plots and the incomplete understanding of purported mechanisms behind the increases in biomass. Ecosystem models, when used in conjunction with satellite data, are useful in examining the carbon budgets in regions where the observations of carbon flows are sparse. The purpose of this study is to explain observed trends in normalized difference vegetation index (NDVI) using climate observations and ecosystem models of varying complexity in the western Amazon basin for the period of 1984–2002. We first investigated trends in NDVI and found a positive trend during the study period, but the positive trend in NDVI was observed only in the months from August to December. Then, trends in various climate parameters were calculated, and of the climate variables considered, only shortwave radiation was found to have a corresponding significant positive trend. To compare the impact of each climate component, as well as increasing carbon dioxide (CO₂) concentrations, on evergreen forests in the Amazon, we ran three ecosystem models (CASA, Biome‐BGC, and LPJ), and calculated monthly net primary production by changing a climate component selected from the available climate datasets. As expected, CO₂ fertilization effects showed positive trends throughout the year and cannot explain the positive trend in NDVI, which was observed only for the months of August to December. Through these simulations, we demonstrated that the positive trend in shortwave radiation can explain the positive trend in NDVI observed for the period from August to December. We conclude that the positive trend in shortwave radiation is the most likely driver of the increasing trend in NDVI and the corresponding observed increases in forest biomass.     

Diagnosing and assessing uncertainties of terrestrial ecosystem models in a multimodel ensemble experiment: 1. Primary production

We conducted an ensemble modeling exercise using the Terrestrial Observation and Prediction System (TOPS) to evaluate sources of uncertainty in carbon flux estimates resulting from structural differences among ecosystem models. The experiment ran public‐domain versions of biome‐bgc, lpj, casa , and tops‐bgc over North America at 8 km resolution and for the period of 1982–2006. We developed the Hierarchical Framework for Diagnosing Ecosystem Models (HFDEM) to separate the simulated biogeochemistry into a cascade of three functional tiers and sequentially examine their characteristics in climate (temperature–precipitation) and other spaces. Analysis of the simulated annual gross primary production (GPP) in the climate domain indicates a general agreement among the models, all showing optimal GPP in regions where the relationship between annual average temperature (T, °C) and annual total precipitation (P, mm) is defined by P=50T+500. However, differences in simulated GPP are identified in magnitudes and distribution patterns. For forests, the GPP gradient along P=50T+500 ranges from ～50 g C yr^?1 m^?2 °C^?1 (casa ) to ～125 g C yr^?1 m^?2 °C^?1 (biome‐bgc ) in cold/temperate regions; for nonforests, the diversity among GPP distributions is even larger. Positive linear relationships are found between annual GPP and annual mean leaf area index (LAI) in all models. For biome‐bgc and lpj , such relationships lead to a positive feedback from LAI growth to GPP enhancement. Different approaches to constrain this feedback lead to different sensitivity of the models to disturbances such as fire, which contribute significantly to the diversity in GPP stated above. The ratios between independently simulated NPP and GPP are close to 50% on average; however, their distribution patterns vary significantly between models, reflecting the difficulties in estimating autotrophic respiration across various climate regimes. Although these results are drawn from our experiments with the tested model versions, the developed methodology has potential for other model exercises.