Primate socioecology at the crossroads: Past, present, and future

Attempts to explain differences in the size and structure of primate groups have argued that they are a consequence of variation in the intensity of feeding competition caused by contrasts in food distribution. However, although feeding competition can limit the size of female groups, many other factors affect the costs and the benefits of sociality to females and contribute to differences in group size. Moreover, interspecific differences in social relationships between females, in female philopatry, and in kinship between group members appear to be more closely associated with variation in life‐history parameters, reproductive strategies, and phylogeny than with contrasts in food distribution or feeding competition. The mismatch between predictions of socioecological theory and observed variation in primate social behavior has led to protracted arguments about the future of primate socioecology. We argue that future attempts to understand the diversity of primate societies need to be based on an approach that explores separate explanations for different components of social organization, combines ecological and phylogenetic information, and integrates research on primates with similar studies of other groups of mammals. © 2012 Wiley Periodicals, Inc.     

Characterization of larval habitats of Anopheles albimanus, Anopheles pseudopunctipennis, Anopheles punctimacula, and Anopheles oswaldoi s.l. populations in lowland and highland Ecuador

Recent collection data indicate that at least four potential malaria vectors occupy more widespread distributions within the Andean highlands than in the past. Since habitat elimination is an important aspect of malaria control, it is vital to characterize larval habitats for Anopheles species within both lowland and highland sites. To that end, 276 sites within Ecuador were surveyed between 2008 and 2010. Characteristics of Anopheles‐present sites for four species were compared to Anopheles‐absent sites within the same geographical range and also to Anopheles‐absent sites within a highland range representing potential future habitats. Thermochron iButtons^© were used to describe the daily temperature variation within a subset of potential habitats. Anopheles albimanus (W.) was positively associated with permanent habitats, sand substrates, floating algae (cyanobacterial mats), and warmer temperatures in both comparisons. Anopheles pseudopunctipennis (T.) was associated with floating algae (cyanobacterial mats), warmer temperatures, and higher water clarity in both comparisons. Anopheles punctimacula (D.&K.) was negatively associated with floating algae and positively associated with dissolved oxygen in both comparisons. Anopheles oswaldoi s.l. (P.) was not significantly associated with any parameters more often than expected given larval‐absent sites. The results indicate that minimum water temperatures might limit the upper altitudinal distribution of An. albimanus (18.7° C) and An. pseudopunctipennis (16.0° C).     

The effect of rainstorms on adult Anopheles funestus behavior and survival

We describe the effect that the passage of a cold front, with a subsequent heavy rainstorm ten days later, had on a population of Anopheles funestus mosquitoes collected exiting houses or in light-traps from a village in southern Mozambique. Temperature effects explained 40% (r=0.634; p <0.001) of the variation in numbers of males collected and 19% of the variation in gravid females collected (r=0.437; p=0.033). The age structure of mosquitoes varied according to distance from the breeding site (χ(2) = 64.1, df 6, p <0.001). The proportion of parous insects that were caught in the light-traps with sacs (χ(2) = 6.33, d.f. 2, p=0.042) and young insects that had mated before being collected (χ(2) = 13,3, d.f. 2, p=0.001) were reduced on the night of the rain but this effect was short lived. It is concluded that the effect of rain on mosquito populations depends on the kind of water body used for larval development.     

Fast Carbon Footprinting for Large Product Portfolios

Publicly Available Specification 2050‐2011 (PAS 2050), the Green House Gas Product Protocol (GHGPP) standard and forthcoming guideline 14067 from the International Organization for Standardization (ISO) have helped to propel carbon footprinting from a subdiscipline of life cycle assessment (LCA) to the mainstream. However, application of carbon footprinting to large portfolios of many distinct products and services is immensely resource intensive. Even if achieved, it often fails to inform company‐wide carbon reduction strategies because footprint data are disjointed or don't cover the whole portfolio. We introduce a novel approach to generate standard‐compliant product carbon footprints (CFs) for companies with large portfolios at a fraction of previously required time and expertise. The approach was developed and validated on an LCA dataset covering 1,137 individual products from a global packaged consumer goods company. Three novel techniques work in concert in a single approach that enables practitioners to calculate thousands of footprints virtually simultaneously: (i) a uniform data structure enables footprinting all products and services by looping the same algorithm; (ii) concurrent uncertainty analysis guides practitioners to gradually improve the accuracy of only those data that materially impact the results; and (iii) a predictive model generates estimated emission factors (EFs) for materials, thereby eliminating the manual mapping of a product or service's inventory to EF databases. These autogenerated EFs enable non‐LCA experts to calculate approximate CFs and alleviate resource constraints for companies embarking on large‐scale product carbon footprinting. We discuss implementation roadmaps for companies, including further road‐testing required to evaluate the effectiveness of the approach for other product portfolios, limitations, and future improvements of the fast footprinting methodology.     

Response to Wiedmann

This commentary is prompted by Thomas Wiedmann's “Defining (Urban) Producer and Consumer Sinks” published in this issue. In his article, Wiedmann presents a new framework for categorizing carbon sinks by borrowing practices from carbon emissions accounting and, essentially, proposing a “carbon sink footprint” model for urban inventories. While this is a valuable new concept, we argue that it is difficult to apply accurately given current knowledge and practices in urban life cycle assessment. Instead, a direct versus embodied classification based on where the sequestration service exists, not where the sink is located, is more useful from the perspective of municipal control and influence over creating and managing carbon sinks. This is ultimately important for the development of urban climate change mitigation measures.     

Estimation of Copper In‐use Stocks in Nanjing,China

Copper (Cu) is an essential but supply‐restricted resource in China. Characterization of in‐use stocks can provide useful instruction for the future recycling of copper. This article attempts to estimate copper in‐use stocks in a Chinese city. To this purpose, an extensive bottom‐up estimate of copper stocks in use in Nanjing in the year 2009 was conducted. The results are a total stock estimate of 295 gigagrams (Gg) of copper or 46.9 kilograms (kg) of copper per capita for 2009. Infrastructure, equipment, and buildings contain 42.0%, 26.1%, and 28.1% of the total stock, respectively, indicating that these three categories are principal potential reservoirs of a secondary copper resource. The copper in transportation amounts to only about 3.7% of the total amount. The per capita stock was compared with similar studies carried out in other regions of the world, and the results show that the Nanjing level is significantly lower than developed countries. On the whole, our results show that electric power transmission and distribution systems, buildings, household durables, and industrial equipment are the four largest potential reservoirs of copper scrap.     

Redefining Industrial Symbiosis

The most commonly cited definition of industrial symbiosis (IS), by Chertow (2000) , has served well to foster discussion and research for more than a decade. The definition reflected the state of research and practice at the time; as both have advanced, some terms have been interpreted in substantially different ways. In this article we analyze those generally used terms for their connection to the ecological metaphor that is the root of industrial ecology, and their varied interpretations in IS research and practice over time. We then propose an updated definition intended to communicate the essence of IS as a tool for innovative green growth: IS engages diverse organizations in a network to foster eco‐innovation and long‐term culture change. Creating and sharing knowledge through the network yields mutually profitable transactions for novel sourcing of required inputs and value‐added destinations for non‐product outputs, as well as improved business and technical processes. We posit that, although geographic proximity is often associated with IS, it is neither necessary nor sufficient—nor is a singular focus on physical resource exchange.     

Does phylogeny matter? Assessing the impact of phylogenetic information in ecological meta‐analysis

Meta-analysis is increasingly used in ecology and evolutionary biology. Yet, in these fields this technique has an important limitation: phylogenetic non-independence exists among taxa, violating the statistical assumptions underlying traditional meta-analytic models. Recently, meta-analytical techniques incorporating phylogenetic information have been developed to address this issue. However, no syntheses have evaluated how often including phylogenetic information changes meta-analytic results. To address this gap, we built phylogenies for and re-analysed 30 published meta-analyses, comparing results for traditional vs. phylogenetic approaches and assessing which characteristics of phylogenies best explained changes in meta-analytic results and relative model fit. Accounting for phylogeny significantly changed estimates of the overall pooled effect size in 47% of datasets for fixed-effects analyses and 7% of datasets for random-effects analyses. Accounting for phylogeny also changed whether those effect sizes were significantly different from zero in 23 and 40% of our datasets (for fixed- and random-effects models, respectively). Across datasets, decreases in pooled effect size magnitudes after incorporating phylogenetic information were associated with larger phylogenies and those with stronger phylogenetic signal. We conclude that incorporating phylogenetic information in ecological meta-analyses is important, and we provide practical recommendations for doing so.