Do Shade-Grown Coffee Plantations Pose a Disease Risk for Wild Birds?

Shade-grown coffee plantations are often promoted as a conservation strategy for wild birds. However, these agro-ecosystems are actively managed for food production, which may alter bird behaviors or interactions that could change bird health, compared to natural forest. To examine whether there is a difference between the health parameters of wild birds inhabiting shade-grown coffee plantations and natural forest, we evaluated birds in Costa Rica for (1) their general body condition, (2) antibodies to pathogens, (paramyxovirus and Mycoplasma spp.), and (3) the prevalence and diversity of endo-, ecto-, and hemoparasites. We measured exposure to Mycoplasma spp. and paramyxovirus because these are pathogens that could have been introduced with domestic poultry, one mechanism by which these landscapes could be detrimental to wild birds. We captured 1,561 birds representing 75 species. Although seasonal factors influenced body condition, we did not find bird general body condition to be different. A total of 556 birds of 31 species were tested for antibodies against paramyxovirus-1. Of these, five birds tested positive, four of which were from shade coffee. Out of 461 other tests for pathogens (for antibodies and nucleotide detection), none were positive. Pterolichus obtusus, the feather mite of chickens, was found on 15 birds representing two species and all were from shade-coffee plantations. Larvated eggs of Syngamus trachea, a nematode typically associated with chickens, were found in four birds captured in shade coffee and one captured in forest. For hemoparasites, a total of 1,121 blood smears from 68 bird species were examined, and only one species showed a higher prevalence of infection in shade coffee. Our results indicate that shade-coffee plantations do not pose a significant health risk to forest birds, but at least two groups of pathogens may deserve further attention: Haemoproteus spp. and the diversity and identity of endoparasites.     

Assessing “Dangerous Climate Change”: Required Reduction of Carbon Emissions to Protect Young People,Future Generations and Nature

We assess climate impacts of global warming using ongoing observations and paleoclimate data. We use Earth’s measured energy imbalance, paleoclimate data, and simple representations of the global carbon cycle and temperature to define emission reductions needed to stabilize climate and avoid potentially disastrous impacts on today’s young people, future generations, and nature. A cumulative industrial-era limit of ∼500 GtC fossil fuel emissions and 100 GtC storage in the biosphere and soil would keep climate close to the Holocene range to which humanity and other species are adapted. Cumulative emissions of ∼1000 GtC, sometimes associated with 2°C global warming, would spur “slow” feedbacks and eventual warming of 3–4°C with disastrous consequences. Rapid emissions reduction is required to restore Earth’s energy balance and avoid ocean heat uptake that would practically guarantee irreversible effects. Continuation of high fossil fuel emissions, given current knowledge of the consequences, would be an act of extraordinary witting intergenerational injustice. Responsible policymaking requires a rising price on carbon emissions that would preclude emissions from most remaining coal and unconventional fossil fuels and phase down emissions from conventional fossil fuels.     

Energy Expenditure Compared to Physical Activity Measured by Accelerometry and Self-Report in Adolescents: A Validation Study

Background

Physical inactivity is responsible for 5.3 million deaths annually worldwide. To measure physical activity energy expenditure, the doubly labeled water (DLW) method is the gold standard. However, questionnaires and accelerometry are more widely used. We compared physical activity measured by accelerometer and questionnaire against total (TEE) and physical activity energy expenditure (PAEE) estimated by DLW.

Methods

TEE, PAEE (TEE minus resting energy expenditure) and body composition were measured using the DLW technique in 25 adolescents (16 girls) aged 13 years living in Pelotas, Brazil. Physical activity was assessed using the Actigraph accelerometer and by self-report. Physical activity data from accelerometry and self-report were tested against energy expenditure data derived from the DLW method. Further, tests were done to assess the ability of moderate-to-vigorous intensity physical activity (MVPA) to predict variability in TEE and to what extent adjustment for fat and fat-free mass predicted the variability in TEE.

Results

TEE varied from 1,265 to 4,143 kcal/day. It was positively correlated with physical activity (counts) estimated by accelerometry (rho  = 0.57; p = 0.003) and with minutes per week of physical activity by questionnaire (rho  = 0.41; p = 0.04). An increase of 10 minutes per day in moderate-to-vigorous intensity physical activity (MVPA) relates to an increase in TEE of 141 kcal/day. PAEE was positively correlated with accelerometry (rho  = 0.64; p = 0.007), but not with minutes per week of physical activity estimated by questionnaire (rho  = 0.30; p = 0.15). Physical activity by accelerometry explained 31% of the vssariability in TEE. By incorporating fat and fat-free mass in the model, we were able to explain 58% of the variability in TEE.

Conclusion

Objectively measured physical activity significantly contributes to the explained variance in both TEE and PAEE in Brazilian youth. Independently, body composition also explains variance in TEE, and should ideally be taken into account when using accelerometry to predict energy expenditure values.     

Significance of the Natural Occurrence of L‐ Versus D‐Pipecolic Acid: A Review

Pipecolic acid naturally occurs in microorganisms, plants, and animals, where it plays many roles, including the interactions between these organisms, and is a key constituent of many natural and synthetic bioactive molecules. This article provides a review of current knowledge on the natural occurrence of pipecolic acid and the known and potential significance of its L‐ and D‐enantiomers in different scientific disciplines. Knowledge gaps with perspectives for future research identified within this article include the roles of the L‐ versus the D‐enantiomer of pipecolic acid in plant resistance, nutrient acquisition, and decontamination of polluted soils, as well as rhizosphere ecology and medical issues. Chirality 25:823–831, 2013. © 2013 Wiley Periodicals, Inc.     

Stand-replacing wildfires alter the community structure of wood-inhabiting fungi in southwestern ponderosa pine forests of the USA

Increases in stand-replacing wildfires in the western USA have widespread implications for ecosystem carbon (C) cycling, in part because the decomposition of trees killed by fire can be a long-term source of CO₂ to the atmosphere. Knowledge of the composition and function of decay fungi communities may be important to understanding how wildfire alters C cycles. We assessed the effects of stand-replacing wildfires on the community structure of wood-inhabiting fungi along a 32-yr wildfire chronosequence. Fire was associated with low species richness for up to 4 yr and altered species composition relative to unburned forest for the length of the chronosequence. A laboratory incubation demonstrated that species varied in their capacity to decompose wood; Hypocrea lixii, an indicator of the most recent burn, caused the lowest decomposition rate. Our results show that stand-replacing wildfires have long-term effects on fungal communities, which may have consequences for wood decomposition and C cycling.     

Using Linkage Analysis to Detect Gene-Gene Interactions. 2. Improved Reliability and Extension to More-Complex Models

Detecting gene-gene interaction in complex diseases has become an important priority for common disease genetics, but most current approaches to detecting interaction start with disease-marker associations. These approaches are based on population allele frequency correlations, not genetic inheritance, and therefore cannot exploit the rich information about inheritance contained within families. They are also hampered by issues of rigorous phenotype definition, multiple test correction, and allelic and locus heterogeneity. We recently developed, tested, and published a powerful gene-gene interaction detection strategy based on conditioning family data on a known disease-causing allele or a disease-associated marker allele⁴. We successfully applied the method to disease data and used computer simulation to exhaustively test the method for some epistatic models. We knew that the statistic we developed to indicate interaction was less reliable when applied to more-complex interaction models. Here, we improve the statistic and expand the testing procedure. We computer-simulated multipoint linkage data for a disease caused by two interacting loci. We examined epistatic as well as additive models and compared them with heterogeneity models. In all our models, the at-risk genotypes are “major” in the sense that among affected individuals, a substantial proportion has a disease-related genotype. One of the loci (A) has a known disease-related allele (as would have been determined from a previous analysis). We removed (pruned) family members who did not carry this allele; the resultant dataset is referred to as “stratified.” This elimination step has the effect of raising the “penetrance” and detectability at the second locus (B). We used the lod scores for the stratified and unstratified data sets to calculate a statistic that either indicated the presence of interaction or indicated that no interaction was detectable. We show that the new method is robust and reliable for a wide range of parameters. Our statistic performs well both with the epistatic models (false negative rates, i.e., failing to detect interaction, ranging from 0 to 2.5%) and with the heterogeneity models (false positive rates, i.e., falsely detecting interaction, ≤1%). It works well with the additive model except when allele frequencies at the two loci differ widely. We explore those features of the additive model that make detecting interaction more difficult. All testing of this method suggests that it provides a reliable approach to detecting gene-gene interaction.     

Ectomycorrhizal fungal exoenzyme activity differs on spruce seedlings planted in forests versus clearcuts

Key message

Ectomycorrhizal (ECM) fungal community structure and potential exoenzymatic activity change after clearcut harvesting, but functional complementarity and redundancy among those ECM fungal species remaining support growth of regenerating seedlings.

Abstract

Ectomycorrhizal (ECM) fungal community composition is altered by forest harvesting, but it is not clear if this shift in structure influences ECM fungal physiological function at the community level. In this study, we characterized activities of extracellular enzymes in the ectomycorrhizospheres of Picea engelmannii seedlings grown in forest and clearcut plots. These exoenzymes are critical for the breakdown of large organic molecules, from which nutrients are subsequently absorbed and translocated by ECM fungi to host plants. We found that ectomycorrhizae on seedlings planted in forests had different exoenzyme activity profiles than those on seedlings planted in clearcuts. Specifically, the activities of glucuronidase, laccase, and acid phosphatase were higher on forest seedlings (P ≤ 0.006). These differences may have been partly driven by soil properties. Total carbon, total nitrogen (N), extractable phosphorus, extractable ammonium-N, and mineralizable N were higher, while pH was lower in forest plots (P ≤ 0.01). However, we also found that enzyme activity only shifted where community composition also changed. Functional complementarity can be inferred within ECM fungal communities in both forests and clearcuts because ectomycorrhizae formed by different species in the same environment had distinct enzyme profiles (P < 0.0001). However, ectomycorrhizae of Thelephora terrestris exhibited high levels of N- and P-mobilizing exoenzyme activities. Seedling biomass did not differ between forest and clearcut environments, so the high abundance of T. terrestris ectomycorrhizae in the clearcuts may have sustained nutrient acquisition by clearcut seedlings even in soils with lower N and P and with reduced ECM fungal species richness.