Developmental change in aggregation,defense and escape behavior of buckmoth caterpillars,Hemileuca lucina (Saturniidae)

Summary Changes in response to attack and the tendency to aggregate were examined in the six larval instars of the buckmoth, Hemileuca lucina (Saturniidae). In response to simulation of attack by a parasitoid and of biting by a predator, early instars (I, II, and III) exhibited defensive behavior much more often than escape behaviors, whereas late instar larvae (IV, V, and VI) usually resorted to escape rather than defend themselves. The situations in which attacked larvae were most likely to stimulate other group members to respond were: second and third instar larvae thrashing in response to simulation of a parasitoid or headrearing in response to simulation of a biting predator; and fourth, fifth and sixth instar larvae dropping in response to either stimulus. An index of reaggregation indicated that first instar larvae had difficulty reaggregating; second, third and fourth instar larvae reaggregated quickly; and fifth and sixth larvae dispersed. As larvae developed, the change from predominantly defense to escape behaviors paralleled the decline in tendency to aggregate.     

Baselines for land-use change in the tropics: application to avoided deforestation projects

Although forest conservation activities, particularly in the tropics, offer significant potential for mitigating carbon (C) emissions, these types of activities have faced obstacles in the policy arena caused by the difficulty in determining key elements of the project cycle, particularly the baseline. A baseline for forest conservation has two main components: the projected land-use change and the corresponding carbon stocks in applicable pools in vegetation and soil, with land-use change being the most difficult to address analytically. In this paper we focus on developing and comparing three models, ranging from relatively simple extrapolations of past trends in land use based on simple drivers such as population growth to more complex extrapolations of past trends using spatially explicit models of land-use change driven by biophysical and socioeconomic factors. The three models used for making baseline projections of tropical deforestation at the regional scale are: the Forest Area Change (FAC) model, the Land Use and Carbon Sequestration (LUCS) model, and the Geographical Modeling (GEOMOD) model. The models were used to project deforestation in six tropical regions that featured different ecological and socioeconomic conditions, population dynamics, and uses of the land: (1) northern Belize; (2) Santa Cruz State, Bolivia; (3) Paraná State, Brazil; (4) Campeche, Mexico; (5) Chiapas, Mexico; and (6) Michoacán, Mexico. A comparison of all model outputs across all six regions shows that each model produced quite different deforestation baselines. In general, the simplest FAC model, applied at the national administrative-unit scale, projected the highest amount of forest loss (four out of six regions) and the LUCS model the least amount of loss (four out of five regions). Based on simulations of GEOMOD, we found that readily observable physical and biological factors as well as distance to areas of past disturbance were each about twice as important as either sociological/demographic or economic/infrastructure factors (less observable) in explaining empirical land-use patterns. We propose from the lessons learned, a methodology comprised of three main steps and six tasks can be used to begin developing credible baselines. We also propose that the baselines be projected over a 10-year period because, although projections beyond 10 years are feasible, they are likely to be unrealistic for policy purposes. In the first step, an historic land-use change and deforestation estimate is made by determining the analytic domain (size of the region relative to the size of proposed project), obtaining historic data, analyzing candidate baseline drivers, and identifying three to four major drivers. In the second step, a baseline of where deforestation is likely to occur–a potential land-use change (PLUC) map—is produced using a spatial model such as GEOMOD that uses the key drivers from step one. Then rates of deforestation are projected over a 10-year baseline period based on one of the three models. Using the PLUC maps, projected rates of deforestation, and carbon stock estimates, baseline projections are developed that can be used for project GHG accounting and crediting purposes: The final step proposes that, at agreed interval (e.g., about 10 years), the baseline assumptions about baseline drivers be re-assessed. This step reviews the viability of the 10-year baseline in light of changes in one or more key baseline drivers (e.g., new roads, new communities, new protected area, etc.). The potential land-use change map and estimates of rates of deforestation could be re-done at the agreed interval, allowing the deforestation rates and changes in spatial drivers to be incorporated into a defense of the existing baseline, or the derivation of a new baseline projection.     

Scale-dependent variation in coral community similarity across sites, islands, and island groups

Community similarity is the proportion of species richness in a region that is shared on average among communities within that region. The slope of local richness (alpha diversity) regressed on regional richness (gamma diversity) can serve as an index of community similarity across regions with different regional richness. We examined community similarity in corals at three spatial scales (among transects at a site, sites on an island, and islands within an island group) across a 10 000-km longitudinal diversity gradient in the west-central Pacific Ocean. When alpha diversity was regressed on gamma diversity, the slopes, and thus community similarity, increased with scale (0.085, 0.261, and 0.407, respectively) because a greater proportion of gamma diversity was subsumed within alpha diversity as scale increased. Using standard randomization methods, we also examined how community similarity differed between observed and randomized assemblages and how this difference was affected by spatial separation of species within habitat types and specialization of species to three habitat types (reef flats, crests, and slopes). If spatial separation within habitat types and/or habitat specialization (i.e., underdispersion) occurs, fewer species are shared among assemblages than the random expectation. When the locations of individual coral colonies were randomized within and among habitat types, community similarity was 46-47% higher than that for observed assemblages at all three scales. We predicted that spatial separation of coral species within habitat types should increase with scale due to dispersal/extinction dynamics in this insular system, but that specialization of species to different habitat types should not change because habitat differences do not change with scale. However, neither habitat specialization nor spatial separation within habitat types differed among scales. At the two larger scales, each accounted for 22-24% of the difference in community similarity between observed and randomized assemblages. At the smallest scale (transect-site), neither spatial separation within habitat types nor habitat specialization had significant effects on community similarity, probably due to the small size of transect samples. The results suggest that coral species can disperse among islands in an island group as easily as they can among sites on an island over time scales that are relevant to their establishment and persistence on reefs.     

Metacommunity models predict the local-regional species richness relationship in a natural system

Many natural communities exhibit positive relationships between local and regional species richness (LSR-RSR relationships), which can be either linear or curvilinear. Previous models have shown that the form of this relationship depends on the relative rates of colonization and extinction and the sensitivity of these rates to competition. We use simple models to show that the LSR-RSR relationship also depends on the type of metacommunity structure (Levins-like or mainland-island), and our models generate a wider range of realistic forms than do most previous models. We parameterize and test our models with two independent data sets for Daphnia in rock pools on islands in Finland and Sweden. We find that the Levins-like model with competition correctly predicts the observed LSR-RSR relationship and provides the best fit to the average local species richness per island. Simulations show that our models are robust to relaxing our assumption of identical species properties. Our study is one of the first to make and successfully test quantitative predictions for how a widely studied community pattern, the LSR-RSR relationship, arises from metacommunity dynamics.     

Measures of health,fitness, and functional movement among firefighter recruits

Aim. The purpose of this study was to examine the associations between various health and fitness measures and Functional Movement Screen? (FMS?) scores among 78 firefighter recruits. Methods. Relationships between FMS? scores and age, body mass index (BMI), sit and reach (S&R) distance, estimated maximal aerobic capacity (V˙_O2max), estimated one-repetition maximum squat (1RM-Squat_max), and plank endurance (%Plank_max) were examined. Results. Total FMS? scores were significantly correlated with BMI (r?=??0.231, p?=?0.042), estimated 1RM-Squat_max (r?=?0.302, p?=?0.007), and %Plank_max (r?=?0.320, p?=?0.004). Multiple regression analyses indicated that this combination of predictors significantly predicted (F(3, 74)?=?5.043, p?=?0.003) Total FMS? score outcomes and accounted for 17% of the total variance (R²?=?0.170). In addition, logistic regression analyses indicated that estimated 1RM-Squat_max also significantly predicted (χ²?=?6.662, df?=?1, p?=?0.010) FMS? group membership (≤14 or ≥15). Conclusion. These results suggest that the health and fitness measures of obesity (BMI), bilateral lower extremity strength (estimated 1RM-Squat_max), and core muscular endurance (%Plank_max) are significantly associated with functional movement patterns among firefighter recruits. Consequently, injury prevention programs implemented among firefighter recruits should target these aspects of health and fitness.     

Biopolymers in the Existing Postconsumer Plastics Recycling Stream

The existing plastic bottle reclaiming industry has working technology, satisfied customers, raw material, and investors. Adding new materials to the current mix requires satisfying all four needs for those materials. Rigid plastic container recycling focuses on high-density polyethylene (HDPE) and polyethylene terephthalate (PET) bottles, the overwhelming percentage of bottles sold in North America. Bottles of other resins, including polyvinyl chloride (PVC), polypropylene and biopolymers, lack critical mass necessary for independent reclamation. To be mechanically recycled, biopolymers must be either completely fungible with existing recycled resins or be available in sufficient quantity to achieve the needed critical mass. So far, biopolymer volume projections are not encouraging. Biopolymers, like all minor bottle resins, must pay their own way in sorting and processing without subsidy from PET and HDPE recycling. Based on limited data, some biopolymers may have little effect on recycled HDPE performance, but will represent a yields loss and added economic burden at some level of occurrence. Biopolymers have not been shown to be compatible with PET and likely will represent performance problems and economic burdens at even low levels of occurrence. Applications for biopolymers should be carefully selected so as to not interfere with currently recycled materials unless critical mass can be achieved quickly.

Atmospheric nitrogen deposition: revisiting the question of the importance of the organic component

The organic component of atmospheric reactive nitrogen plays a role in biogeochemical cycles, climate and ecosystems. Although its deposition has long been known to be quantitatively significant, it is not routinely assessed in deposition studies and monitoring programmes. Excluding this fraction, typically 25-35%, introduces significant uncertainty in the determination of nitrogen deposition, with implications for the critical loads approach. The last decade of rainwater studies substantially expands the worldwide dataset, giving enough global coverage for specific hypotheses to be considered about the distribution, composition, sources and effects of organic-nitrogen deposition. This data collation and meta-analysis highlights knowledge gaps, suggesting where data-gathering efforts and process studies should be focused. New analytical techniques allow long-standing conjectures about the nature and sources of organic N to be investigated, with tantalising indications of the interplay between natural and anthropogenic sources, and between the nitrogen and carbon cycles.     

Downscaling species occupancy from coarse spatial scales

The measurement and prediction of species' populations at different spatial scales is crucial to spatial ecology as well as conservation biology. An efficient yet challenging goal to achieve such population estimates consists of recording empirical species' presence and absence at a specific regional scale and then trying to predict occupancies at finer scales. So far the majority of the methods have been based on particular species' distributional features deemed to be crucial for downscaling occupancy. However, only a minority of them have dealt explicitly with specific spatial features. Here we employ a wide class of spatial point processes, the shot noise Cox processes (SNCP), to model species occupancies at different spatial scales and show that species' spatial aggregation is crucial for predicting population estimates at fine scales starting from coarser ones. These models are formulated in continuous space and locate points regardless of the arbitrary resolution that one employs to study the spatial pattern. We compare the performances of nine models, calibrated at regional scales and demonstrate that a very simple class of SNCP, the Thomas process, is able to outperform other published models in predicting occupancies down to areas four orders of magnitude smaller than the ones employed for the parameterization. We conclude by explaining the ability of the approach to infer spatially explicit information from spatially implicit measures, the potential of the framework to combine niche and spatial models, and the possibility of reversing the method to allow upscaling.     

Aggregation influences coral species richness at multiple spatial scales

The spatial dispersion of individuals across multiple spatial scales can significantly influence biodiversity patterns. Here we characterize the dispersion of corals in reef assemblages distributed across a 10000-km longitudinal biodiversity gradient from Indonesia to the Society Islands, using a multiscale sampling design. Our results indicate that most coral species were aggregated among 10-m transect samples across this vast distance. Using observed and randomized species sampling curves, we show that aggregation reduced the number of species per transect, site, and island sample on average by 13-27%. Across site, island, and regional scales, aggregation also reduced the area under species sampling curves by an average of 2.7-6.5%. The level of aggregation was relatively constant across spatial scales within regions and did not vary among habitats. However, there was significant variation among regions using transect samples across individual sites. Specifically, aggregation reduced the species richness per transect and the area under species sampling curves nearly twice as much in the Indonesian biodiversity hotspot than in the Society Islands. As a significant component of the spatial structure of coral assemblages, aggregation should be integrated into our understanding of coral community dynamics and the development of conservation strategies designed to protect these communities.