Visualizing mushroom body response to a conditioned odor in honeybees

Combining differential conditioning with optophysiological recordings of bee brain activity allows the investigation of learning-related changes in complex neural systems. In this study we focused on the mushroom bodies of the bee brain. Presenting different odors to the animal leads to significant activation of the mushroom body lips. After differential conditioning, the rewarded odor leads to stronger activation than it did before training. Activation by the unrewarded odor remains unchanged. These results resemble findings in the bee's antennal lobes, which are the first olfactory relay station in the insect brain. As an integrative neural network, enhanced activation of the mushroom body lip may carry additional information, i.e., for processing odor concentrations.     

Superovulation fails to increase human blastocyst yield after uterine lavage

Uterine lavage affords the potential for non-invasive human blastocyst recovery, with obvious potential for preimplantation genetic diagnosis. In an effort to duplicate in women the multiple blastocyst recovery per cycle that can be achieved in several other species, we initiated a programme in which fertile women underwent superovulation, followed by lavage and embryo collection. We superovulated 15 fertile women, aged 21–40, in 29 cycles using one of four regimens. Insemination was by either intercourse or artificial intracervical donor insemination with cryopreserved sperm from men of proven fertility. In 28 of 29 cycles, the uterus was lavaged daily for 1, 2, or 3 days between 5 and 10 days after human chorionic gonadotropin (hCG) administration or luteinizing hormone (LH) surge. Almost total fluid volume was recovered in every lavage. There were no retained pregnancies and no complications. Surprisingly, only two morulae, one blastocyst, and four unfertilized ova were recovered. Thus, alterations in ovulation induction, insemination timing, or lavage techniques must be contemplated in order to increase the blastocyst yield and thus fulfil the potential of uterine lavage for preimplantation diagnosis.     

Accelerated soil dissipation of tebuconazole following multiple applications to peanut

Repeated application may increase rates of pesticide dissipation in soil and reduce persistence. The potential for this to occur was investigated for the fungicide, tebuconazole (alpha-[2-(4-chlorophenyl)ethyl]-alpha-(1,1-dimethylethyl)-1H-1,2,4-triazole-1-ethanol), when used for peanut (Arachis hypogaea L.) production. Soil samples were collected from peanut plots after each of four tebuconazole applications at 2-wk intervals. Soil moisture was adjusted to field capacity as necessary and samples were incubated in the laboratory for 63 d at 30 degrees C. Untreated plot samples spiked with the compound served as controls. Results indicated accelerated dissipation in field-treated samples with the time to fifty percent dissipation (DT50) decreasing from 43 to 5 d after three tebuconazole applications. Corresponding increases in rates of accumulation and decay of degradates were also indicated. Best-fit equations (r2 = 0.84-0.98) to dissipation kinetic data combined with estimates of canopy interception rates were used to predict tebuconazole and degradates concentration in soil after each successive application. Predicted concentrations compared with values measured in surface soil samples were from twofold less to twofold greater. Use of kinetic data will likely enhance assessments of treatment efficacy and human and ecological risks from normal agronomic use of tebuconazole on peanut. However, the study indicated that varying soil conditions (in particular, soil temperature and water content) may have an equal or greater impact on field dissipation rate than development of accelerated dissipation. Results emphasize that extension of laboratory-derived kinetic data to field settings should be done with caution.     

Analyzing the Impacts of Dams on Riparian Ecosystems: A Review of Research Strategies and Their Relevance to the Snake River Through Hells Canyon

River damming provides a dominant human impact on river environments worldwide, and while local impacts of reservoir flooding are immediate, subsequent ecological impacts downstream can be extensive. In this article, we assess seven research strategies for analyzing the impacts of dams and river flow regulation on riparian ecosystems. These include spatial comparisons of (1) upstream versus downstream reaches, (2) progressive downstream patterns, or (3) the dammed river versus an adjacent free-flowing or differently regulated river(s). Temporal comparisons consider (4) pre- versus post-dam, or (5) sequential post-dam conditions. However, spatial comparisons are complicated by the fact that dams are not randomly located, and temporal comparisons are commonly limited by sparse historic information. As a result, comparative approaches are often correlative and vulnerable to confounding factors. To complement these analyses, (6) flow or sediment modifications can be implemented to test causal associations. Finally, (7) process-based modeling represents a predictive approach incorporating hydrogeomorphic processes and their biological consequences. In a case study of Hells Canyon, the upstream versus downstream comparison is confounded by a dramatic geomorphic transition. Comparison of the multiple reaches below the dams should be useful, and the comparison of Snake River with the adjacent free-flowing Salmon River may provide the strongest spatial comparison. A pre- versus post-dam comparison would provide the most direct study approach, but pre-dam information is limited to historic reports and archival photographs. We conclude that multiple study approaches are essential to provide confident interpretations of ecological impacts downstream from dams, and propose a comprehensive study for Hells Canyon that integrates multiple research strategies.     

Volunteer Macroinvertebrate Monitoring: Tensions Among Group Goals,Data Quality,and Outcomes

Volunteer monitoring of natural resources is promoted for its ability to increase public awareness, to provide valuable knowledge, and to encourage policy change that promotes ecosystem health. We used the case of volunteer macroinvertebrate monitoring (VMM) in streams to investigate whether the quality of data collected is correlated with data use and organizers' perception of whether they have achieved these outcomes. We examined the relation between site and group characteristics, data quality, data use, and perceived outcomes (education, social capital, and policy change). We found that group size and the degree to which citizen groups perform tasks on their own (rather than aided by professionals) positively correlated with the quality of data collected. Group size and number of years monitoring positively influenced whether a group used their data. While one might expect that groups committed to collecting good-quality data would be more likely to use it, there was no relation between data quality and data use, and no relation between data quality and perceived outcomes. More data use was, however, correlated with a group's feeling of connection to a network of engaged citizens and professionals. While VMM may hold promise for bringing citizens and scientists together to work on joint conservation agendas, our data illustrate that data quality does not correlate with a volunteer group's desire to use their data to promote regulatory change. Therefore, we encourage scientists and citizens alike to recognize this potential disconnect and strive to be explicit about the role of data in conservation efforts.     

River-Stream Connectivity Affects Fish Bioassessment Performance

Stream fish bioassessment methods assume that fish assemblages observed in sample sites reflect responses to local stressors, but fish assemblages are influenced by local factors as well as regional dispersal to and from connected streams. We hypothesized that fish movement to and from refugia and source populations in connected rivers (i.e., riverine dispersal) would weaken or decouple relations between fish community metrics and local environmental conditions. We compared fish-environment relations between streams that flow into large rivers (mainstem tributaries) and streams that lack riverine confluences (headwater tributaries) at multiple spatial grains using data from the USEPA's Environmental Monitoring and Assessment Program in the mid-Atlantic highlands, USA (n = 157 sites). Headwater and mainstem tributaries were not different in local environmental conditions, but showed important differences in fish metric responses to environmental quality gradients. Stream sites flowing into mainstem channels within 10 fluvial km showed consistently weaker relations to local environmental conditions than stream sites that lacked such mainstem connections. Moreover, these patterns diminished at longer distances from riverine confluences, consistent with the hypothesis of riverine dispersal. Our results suggest that (1) the precision of fish bioassessment metrics may be improved by calibrating scoring criteria based on the spatial position of sites within stream networks and (2) the spatial grain of fish bioassessment studies may be manipulated to suit objectives by including or excluding fishes exhibiting riverine dispersal.     

Soil C and N models that integrate microbial diversity

Industrial agriculture is yearly responsible for the loss of 55–100 Pg of historical soil carbon and 9.9 Tg of reactive nitrogen worldwide. Therefore, management practices should be adapted to preserve ecological processes and reduce inputs and environmental impacts. In particular, the management of soil organic matter (SOM) is a key factor influencing C and N cycles. Soil microorganisms play a central role in SOM dynamics. For instance, microbial diversity may explain up to 77 % of carbon mineralisation activities. However, soil microbial diversity is actually rarely taken into account in models of C and N dynamics. Here, we review the influence of microbial diversity on C and N dynamics, and the integration of microbial diversity in soil C and N models. We found that a gain of microbial richness and evenness enhances soil C and N dynamics on the average, though the improvement of C and N dynamics depends on the composition of microbial community. We reviewed 50 models integrating soil microbial diversity. More than 90 % of models integrate microbial diversity with discrete compartments representing conceptual functional groups (64 %) or identified taxonomic groups interacting in a food web (28 %). Half of the models have not been tested against an empirical dataset while the other half mainly consider fixed parameters. This is due to the difficulty to link taxonomic and functional diversity.