Evaluation of inorganic pyrophosphate in amniotic fluid as a mode of prenatal diagnosis of osteogenesis imperfecta

Using a modified procedure by Solomons and Styner (1969), an evaluation of inorganic pyrophosphate (PPi) was performed on the amniotic fluid of two fetuses at risk for osteogenesis imperfecta (OI) at 14½ weeks gestation. The parents of both cases had a previous child with OI, Type II. The normal control group at 14–16 weeks gestation had PPi values ranging from 22.0–59.2 ug/100 ml, with a mean of 38.6±9.51 ug/100 ml. In each at-risk fetus, the amniotic fluid PPi value was within normal range. The first baby was born phenotypically normal at term. Intrauterine radiographic and fetal sonograms were done on the second fetus at approximately 19 weeks gestation. Both showed evidence of OI, Type II. The pregnancy was terminated at 21 weeks. Radiologic studies of the aborted fetus were consistent with OI, Type II. Our results indicate that the evaluation of PPi levels in amniotic fluid is not the method of choice for prenatal diagnosis of IO.     

Activity of biotin-dependent and gaba metabolizing enzymes in chorionic villus samples: Potential for 1st trimester prenatal diagnosis

We have documented the presence of five mitochondrial enzymes in samples of chorionic villus tissue and measured the levels of activity. Three of the enzymes catalyse biotindependent reactions. These are propionyl-CoA carboxylase, 3-methylcrotonyl-CoA carboxylase and pyruvate carboxylase. the other enzymes. 4-aminobutyric acid aminotransferase and succinic semialdehyde dehydrogenase, are involved inthe degradation of the central inhibitory neurotransmitter GABA. Distinct diseases in whichthere is deficiency of each of these enzymes have been documented in man. Significant levels of activity were observed for all five enzymes in chorionic villus tissue. This methodology should permit early prenatal diagnosis of deficiencies of these enzymes by chorionic villus biopsy in the first trimester.     

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.     

Cougar Dispersal Patterns, Metapopulation Dynamics, and Conservation

Abstract: We examined cougar (   Puma concolor ) dispersal, emigration, and immigration in the San Andres Mountains, New Mexico, from 1985 to 1995 to quantify the effects of dispersal on the local population and surrounding subpopulations. We captured, tagged, and radio-collared animals to detect the arrival of new immigrants and dispersal characteristics of progeny. We found that cougars in southern New Mexico exhibited a metapopulation structure in which cougar subpopulations were separated by expanses of noncougar habitat and linked by dispersers. Of 43 progeny (n = 20 males , 23 females ) studied after independence, only 13 females exhibited philopatric behavior. Males dispersed significantly farther than females, were more likely to traverse large expanses of noncougar habitat, and were probably most responsible for nuclear gene flow between habitat patches. We estimated that an average of 8.5 progeny (i.e., cougars born in the study area) successfully emigrated from and 4.3 cougars successfully immigrated to the San Andres Mountains each year. Concurrently, an average of 4.1 progeny were recruited into the San Andres cougar population. Protected cougar subpopulations can contribute to metapopulation persistence by supplying immigrants to surrounding subpopulations that are affected by fragmentation or offtake by humans. Cougar population dynamics and dispersal behavior dictate that cougar management and conservation should be considered on a regional scale.     

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.