The role of moisture in the nest thermoregulation of social wasps

Paper nests of social wasps are intriguing constructions for both, biologists and engineers. We demonstrate that moisture and latent heat significantly influence the thermal performance of the nest construction. Two colonies of the hornet Vespa crabro were investigated in order to clarify the relation of the temperature and the moisture regime inside the nest. Next to fairly stable nest temperatures the hornets maintain a high relative humidity inside the nest. We found that in consequence a partial vapor-pressure gradient between nest and ambient drives a constant vapor flux through the envelope. The vapor flux is limited by the diffusion resistance of the envelope. The driving force of vapor flux is heat, which is consumed through evaporation inside the nest. The colony has to compensate this loss with metabolic heat production in order to maintain a stable nest temperature. However, humidity fluctuations inside the nest induce circadian adsorption and desorption cycles, which stabilize the nest temperature and thus contribute significantly to temperature homeostasis. Our study demonstrates that both mechanisms influence nest thermoregulation and need to be considered to understand the thermodynamic behavior of nests of wasps and social insects in general.     

Effects of sampling error and temporal correlations in population growth on process variance estimators

Estimates of a population’s growth rate and process variance from time-series data are often used to calculate risk metrics such as the probability of quasi-extinction, but temporal correlations in the data from sampling error, intrinsic population factors, or environmental conditions can bias process variance estimators and detrimentally affect risk predictions. It has been claimed (McNamara and Harding, Ecol Lett 7:16–20, 2004) that estimates of the long-term variance that incorporate observed temporal correlations in population growth are unaffected by sampling error; however, no estimation procedures were proposed for time-series data. We develop a suite of such long-term variance estimators, and use simulated data with temporally autocorrelated population growth and sampling error to evaluate their performance. In some cases, we get nearly unbiased long-term variance estimates despite ignoring sampling error, but the utility of these estimators is questionable because of large estimation uncertainty and difficulties in estimating correlation structure in practice. Process variance estimators that ignored temporal correlations generally gave more precise estimates of the variability in population growth and of the probability of quasi-extinction. We also found that the estimation of probability of quasi-extinction was greatly improved when quasi-extinction thresholds were set relatively close to population levels. Because of precision concerns, we recommend using simple models for risk estimates despite potential biases, and limiting inference to quantifying relative risk; e.g., changes in risk over time for a single population or comparative risk among populations.     

Simulating dynamic and mixed-severity fire regimes: A process-based fire extension for LANDIS-II

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and incorporate realistic fire characteristics (shapes, distributions, and effects) that can vary within and between fire events. We demonstrate the capabilities of the new extensions using two case study examples with very different ecosystem characteristics: a boreal forest system from central Labrador, Canada, and a mixed conifer system from the Sierra Nevada Mountains (California, USA). In Labrador, comparison between the more complex dynamic fire extension and a classic fire simulator based on a simple fire size distribution showed little difference in terms of mean fire rotation and potential severity, but cumulative burn patterns created by the dynamic fire extension were more heterogeneous due to feedback between fuel types and fire behavior. Simulations in the Sierra Nevada indicated that burn patterns were responsive to topographic features, fuel types, and an extreme weather scenario, although the magnitude of responses depended on elevation. In both study areas, simulated fire size and resulting fire rotation intervals were moderately sensitive to parameters controlling the curvilinear response between fire spread and weather, as well as to the assumptions underlying the correlation between weather conditions and fire duration. Potential fire severity was more variable within the Sierra Nevada landscape and also was more sensitive to the correlation between weather conditions and fire duration. The fire modeling approach described here should be applicable to questions related to climate change and disturbance interactions, particularly within locations characterized by steep topography, where temporally or spatially dynamic vegetation significantly influences spread rates, where fire severity is variable, and where multiple disturbance types of varying severities are common.     

Water Transactions for Streamflow Restoration,Water Supply Reliability,and Rural Economic Vitality in the Western United States

Across the western United States, environmental water transaction programs (EWTPs) restore environmental flows by acquiring water rights and incentivizing changes in water management. These programs have evolved over several decades, expanding from relatively simple two‐party transactions to multiobjective deals that simultaneously benefit the environment and multiple water‐using sectors. Such programs now represent an important water management tool and provide an impetus for collaboration among stakeholders; yet, most evaluations of their effectiveness focus exclusively on environmental outcomes, without adequate attention to impacts on other water users or local economies. To understand how these programs affect stakeholders, a systematic, multiobjective evaluation framework is needed. To meet this need, we developed a suite of environmental and socioeconomic indicators that can guide the design and track the implementation of water transaction portfolios, and we applied them to existing EWTPs in Oregon and Nevada. Application of the indicators quantifies impacts and helps practitioners design water transaction portfolios that avoid unintended consequences and generate mutually beneficial outcomes among environmental, agricultural, and municipal interests.     

Uncertainty-based quantitative assessment of sustainability for higher education institutions

Evaluation of sustainability in various facets of life is gaining increasing importance. Traditionally, different multi-criteria decision-making methods have been used for sustainability assessment. “Sustainability” can be a qualitative concept, and as such several researchers have attempted fuzzy logic for the quantitative assessment of sustainability. This paper outlines a new evaluation model based on fuzzy multi-criteria decision-making. The model is tested for sustainability assessment of higher education institutions (HEIs). It is based on a driving force–pressure–state–exposure–effect–action (DPSEEA) framework and is called uncertainty-based DPSEEA-Sustainability index Model (uD-SiM). The uD-SiM is a causality-based model in which the sustainability index is an outcome of nonlinear impacts of sustainability indicators in different stages of DPSEEA. The percent contribution of driving forces on the sustainability index of HEI is investigated using sensitivity analysis. The study reveals that education in sustainability and global and local research trends are the major driving forces for achieving sustainability in HEI, followed by financial and economic growth rate, social equity, energy requirements rate, and institutional enhancement, in descending order. The results of uD-SiM were found to be more realistic and rational than our earlier proposed approach, D-SiM.     

近期和长远时段内北极生态系统功能受到的影响

长期以来,就营养物质和碳循环而言,北极生态系统降低了初级生产力；能量,水和温室气体交换的水平已引起了局部和区域性的小幅度降温.大气CO2中的碳沉积在广袤而寒冷的有机土壤中,冰雪覆盖的低矮植被产生高的反射率,都影响了局部气候.然而,北极生态系统功能的许多方面都对气候变化及其产生的生物多样性影响敏感.当前的北极气候导致了低的有机物质分解速率,因此,尽管有机物和元素输入量较低,但北极生态系统还是趋向于积累有机物和元素,土壤中氮和磷等可利用元素结果成为促进碳固定以及生物量和有机物进一步积累的关键性限制因素.气候变暖可能增加特别是土壤中的碳和元素的周转,起初可能导致元素的丢失,但最后会慢慢的恢复.在北极生态系统中,单个物种和物种多样性已经明显地影响了元素的输入和滞留,另一方面,从长远来看,尽管CO2和紫外线增加对植物组织化学、分解和氮固定的影响可能变得重要,但对整个生态系统来说,影响可能很小.碳循环的示踪气体主要形式是CO2和CH4,大多数碳以CO2的形式损失,这些CO2是由植物和土壤生物产生.来自潮湿苔原生态系统以CH4形式释放的碳大约是CO2形式的5％,而且在没有任何其他变化的情况下,对变暖作出响应.冬天过程和植物类型也影响CH4释放和能量在生物圈和大气之间的交换,因为反射率从冬末到夏天存在很大的变化,在冬末,雪反射了入射的大部分光线,在夏天,生态系统吸收了入射的大部分光线,所以在所有的陆地生态系统中,北极生态系统在能量交换方面表现出巨大的季节性变化.植被深刻地影响北极生态系统水和能量交换.在冰雪覆盖期间,反射率从苔原、森林苔原、落叶林、常绿林依次降低.灌木和树增加了雪的深度,反过来又使冬天的土壤温度增加,因此,由气候变化而引起的未来植被方面的变化很可能深远地改变区域的气候.