Division of labor between scouts and recruits: genetic influence and mechanisms

Every recruitment system in social insects requires some individuals that serve as scouts, foragers that search independently for food sources. It is not well understood which factors influence whether an individual becomes a scout or a recruit, nor how the division of labor between the two forager groups is regulated. It is shown here for honeybees (Apis mellifera), using two different molecular techniques, that there is a genetically based difference in the probability that individuals will scout independently for food. In contrast to earlier suggestions, experimental tests showed that the age of a bee does not seem to influence its probability of becoming a scout or a recruit. Furthermore, scout bees do not search opportunistically for either pollen or nectar but, rather, individuals have preferences that are genetically based. These findings are discussed in the framework of foraging regulation by specialization in honeybees and the adaptive significance of polyandry. Received: 23 October 1997 / Accepted after revision: 10 April 1998     

Emission factors of atmospheric and climatic pollutants from crop residues burning

Biomass burning is a common agricultural practice, because it allows elimination of postharvesting residues; nevertheless, it involves an inefficient combustion process that generates atmospheric pollutants emission, which has implications on health and climate change. This work focuses on the estimation of emission factors (EFs) of PM_2.5, PM₁₀, organic carbon (OC), elemental carbon (EC), carbon monoxide (CO), carbon dioxide (CO₂), and methane (CH₄) of residues from burning alfalfa, barley, beans, cotton, maize, rice, sorghum, and wheat in Mexico. Chemical characteristics of the residues were determined to establish their relationship with EFs, as well as with the modified combustion efficiency (MCE). Essays were carried out in an open combustion chamber with isokinetic sampling, following modified EPA 201-A method. EFs did not present statistical differences among different varieties of the same crop, but were statistically different among different crops, showing that generic values of EFs for all the agricultural residues can introduce significant uncertainties when used for climatic and atmospheric pollutant inventories. EFs of PM_2.5 ranged from 1.19 to 11.30 g kg^?1, and of PM₁₀ from 1.77 to 21.56 g kg^?1. EFs of EC correlated with lignin content, whereas EFs of OC correlated inversely with carbon content. EFs of EC and OC in PM_2.5 ranged from 0.15 to 0.41 g kg^?1 and from 0.33 to 5.29 g kg^?1, respectively, and in PM₁₀, from 0.17 to 0.43 g kg^?1 and from 0.54 to 11.06 g kg^?1. CO₂ represented the largest gaseous emissions volume with 1053.35–1850.82 g kg^?1, whereas the lowest was CH₄ with 1.61–5.59 g kg^?1. CO ranged from 28.85 to 155.71 g kg^?1, correlating inversely with carbon content and MCE. EFs were used to calculate emissions from eight agricultural residues burning in the country during 2016, to know the potential mitigation of climatic and atmospheric pollutants, provided this practice was banned.

Implications: The emission factors of particles, short-lived climatic pollutants, and atmospheric pollutants from the crop residues burning of eight agricultural wastes crops, determined in this study using a standardized method, provides better knowledge of the emissions of those species in Latin America and other developing countries, and can be used as inputs in air quality models and climatic studies. The EFs will allow the development of more accurate inventories of aerosols and gaseous pollutants, which will lead to the design of effective mitigation strategies and planning processes for sustainable agriculture.     

Effect of scale on trait predictors of species responses to agriculture

Species persistence in human‐altered landscapes can depend on factors operating at multiple spatial scales. To understand anthropogenic impacts on biodiversity, it is useful to examine relationships between species traits and their responses to land‐use change. A key knowledge gap concerns whether these relationships vary depending on the scale of response under consideration. We examined how local‐ and large‐scale habitat variables influence the occupancy dynamics of a bird community in cloud forest zones in the Colombian Chocó‐Andes. Using data collected across a continuum of forest and agriculture, we examined which traits best predict species responses to local variation in farmland and which traits best predict species responses to isolation from contiguous forest. Global range size was a strong predictor of species responses to agriculture at both scales; widespread species were less likely to decline as local habitat cover decreased and as distance from forest increased. Habitat specialization was a strong predictor of species responses only at the local scale. Open‐habitat species were particularly likely to increase as pasture increased, but they were relatively insensitive to variation in distance to forest. Foraging plasticity and flocking behavior were strong predictors of species responses to distance from forest, but not their responses to local habitat. Species with lower plasticity in foraging behaviors and obligate flock‐following species were more likely to decline as distance from contiguous forest increased. For species exhibiting these latter traits, persistence in tropical landscapes may depend on the protection of larger contiguous blocks of forest, rather than the integration of smaller‐scale woodland areas within farmland. Species listed as threatened or near threatened on the International Union for Conservation of Nature Red List were also more likely to decline in response to both local habitat quality and isolation from forest relative to least‐concern species, underlining the importance of contiguous forests for threatened taxa.     

Combined effects of land use and hunting on distributions of tropical mammals

Land use and hunting are 2 major pressures on biodiversity in the tropics. Yet, their combined impacts have not been systematically quantified at a large scale. We estimated the effects of both pressures on the distributions of 1884 tropical mammal species by integrating species’ range maps, detailed land-use maps (1992 and 2015), species-specific habitat preference data, and a hunting pressure model. We further identified areas where the combined impacts were greatest (hotspots) and least (coolspots) to determine priority areas for mitigation or prevention of the pressures. Land use was the main driver of reduced distribution of all mammal species considered. Yet, hunting pressure caused additional reductions in large-bodied species’ distributions. Together, land use and hunting reduced distributions of species by 41% (SD 30) on average (year 2015). Overlap between impacts was only 2% on average. Land use contributed more to the loss of distribution (39% on average) than hunting (4% on average). However, hunting reduced the distribution of large mammals by 29% on average; hence, large mammals lost a disproportional amount of area due to the combination of both pressures. Gran Chaco, the Atlantic Forest, and Thailand had high levels of impact across the species (hotspots of area loss). In contrast, the Amazon and Congo Basins, the Guianas, and Borneo had relatively low levels of impact (coolspots of area loss). Overall, hunting pressure and human land use increased from 1992 to 2015 and corresponding losses in distribution increased from 38% to 41% on average across the species. To effectively protect tropical mammals, conservation policies should address both pressures simultaneously because their effects are highly complementary. Our spatially detailed and species-specific results may support future national and global conservation agendas, including the design of post-2020 protected area targets and strategies.     

Improving credibility and transparency of conservation impact evaluations through the partial identification approach

The fundamental challenge of evaluating the impact of conservation interventions is that researchers must estimate the difference between the outcome after an intervention occurred and what the outcome would have been without it (counterfactual). Because the counterfactual is unobservable, researchers must make an untestable assumption that some units (e.g., organisms or sites) that were not exposed to the intervention can be used as a surrogate for the counterfactual (control). The conventional approach is to make a point estimate (i.e., single number along with a confidence interval) of impact, using, for example, regression. Point estimates provide powerful conclusions, but in nonexperimental contexts they depend on strong assumptions about the counterfactual that often lack transparency and credibility. An alternative approach, called partial identification (PI), is to first estimate what the counterfactual bounds would be if the weakest possible assumptions were made. Then, one narrows the bounds by using stronger but credible assumptions based on an understanding of why units were selected for the intervention and how they might respond to it. We applied this approach and compared it with conventional approaches by estimating the impact of a conservation program that removed invasive trees in part of the Cape Floristic Region. Even when we used our largest PI impact estimate, the program's control costs were 1.4 times higher than previously estimated. PI holds promise for applications in conservation science because it encourages researchers to better understand and account for treatment selection biases; can offer insights into the plausibility of conventional point‐estimate approaches; could reduce the problem of advocacy in science; might be easier for stakeholders to agree on a bounded estimate than a point estimate where impacts are contentious; and requires only basic arithmetic skills.