Global potential net primary production predicted from vegetation class, precipitation, and temperature

Net primary production (NPP), the difference between CO2 fixed by photosynthesis and CO2 lost to autotrophic respiration, is one of the most important components of the carbon cycle. Our goal was to develop a simple regression model to estimate global NPP using climate and land cover data. Approximately 5600 global data points with observed mean annual NPP, land cover class, precipitation, and temperature were compiled. Precipitation was better correlated with NPP than temperature, and it explained much more of the variability in mean annual NPP for grass- or shrub-dominated systems (r2 = 0.68) than for tree-dominated systems (r2 = 0.39). For a given precipitation level, tree-dominated systems had significantly higher NPP (approximately 100-150 g C m(-2) yr(-1)) than non-tree-dominated systems. Consequently, previous empirical models developed to predict NPP based on precipitation and temperature (e.g., the Miami model) tended to overestimate NPP for non-tree-dominated systems. Our new model developed at the National Center for Ecological Analysis and Synthesis (the NCEAS model) predicts NPP for tree-dominated systems based on precipitation and temperature; but for non-tree-dominated systems NPP is solely a function of precipitation because including a temperature function increased model error for these systems. Lower NPP in non-tree-dominated systems is likely related to decreased water and nutrient use efficiency and higher nutrient loss rates from more frequent fire disturbances. Late 20th century aboveground and total NPP for global potential native vegetation using the NCEAS model are estimated to be approximately 28 Pg and approximately 46 Pg C/yr, respectively. The NCEAS model estimated an approximately 13% increase in global total NPP for potential vegetation from 1901 to 2000 based on changing precipitation and temperature patterns.     

Putting free-riding to work: A Partnership Solution to the common-property problem

The common-property problem results in excessive mining, hunting, and extraction of oil and water. The same phenomenon is also responsible for excessive investment in R&D and excessive outlays in rent-seeking contests. We propose a “Partnership Solution” to eliminate or at least mitigate these excesses. Each of N players joins a partnership in the first stage and chooses his effort in the second stage. Under the rules of a partnership, each member must pay his own cost of effort but receives an equal share of the partnership's revenue. The incentive to free-ride created by such partnerships turns out to be beneficial since it naturally offsets the excessive effort inherent in such problems. In our two-stage game, this institutional arrangement can, under specified circumstances, induce the social optimum in a subgame-perfect equilibrium: no one has a unilateral incentive (1) to switch to another partnership (or create a new partnership) in the first stage or (2) to deviate from socially optimal actions in the second stage. The game may have other subgame-perfect equilibria, but the one associated with the “Partnership Solution” is strictly preferred by every player. We also propose a modification of the first stage which generates a unique subgame-perfect equilibrium. Antitrust authorities should recognize that partnerships can have a less benign use. By organizing as competing partnerships, an industry can reduce the “excessive” output of Cournot oligopoly to the monopoly level. Since no partner has any incentive to overproduce in the current period, there is no need to deter cheating with threats of future punishments.     

Using social network analysis tools in ecology: Markov process transition models applied to the seasonal trophic network dynamics of the Chesapeake Bay

Ecosystem components interact in complex ways and change over time due to a variety of both internal and external influences (climate change, season cycles, human impacts). Such processes need to be modeled dynamically using appropriate statistical methods for assessing change in network structure. Here we use visualizations and statistical models of network dynamics to understand seasonal changes in the trophic network model described by Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329–364] for the Chesapeake Bay (USA). Visualizations of carbon flow networks were created for each season by using a network graphic analysis tool (NETDRAW). The structural relations of the pelagic and benthic compartments (nodes) in each seasonal network were displayed in a two-dimensional space using spring-embedder analyses with nodes color-coded for habitat associations (benthic or pelagic). The most complex network was summer, when pelagic species such as sea nettles, larval fishes, and carnivorous fishes immigrate into Chesapeake Bay and consume prey largely from the plankton and to some extent the benthos. Winter was the simplest of the seasonal networks, and exhibited the highest ascendency, with fewest nodes present and with most of the flows shifting to the benthic bacteria and sediment POC compartments. This shift in system complexity corresponds with a shift from a pelagic- to benthic-dominated system over the seasonal cycle, suggesting that winter is a mostly closed system, relying on internal cycling rather than external input. Network visualization tools are useful in assessing temporal and spatial changes in food web networks, which can be explored for patterns that can be tested using statistical approaches. A simulation-based continuous-time Markov Chain model called SIENA was used to determine the dynamic structural changes in the trophic network across phases of the annual cycle in a statistical as opposed to a visual assessment. There was a significant decrease in outdegree (prey nodes with reduced link density) and an increase in the number of transitive triples (a triad in which i chooses j and h, and j also chooses h, mostly connected via the non-living detritus nodes in position i), suggesting the Chesapeake Bay is a simpler, but structurally more efficient, ecosystem in the winter than in the summer. As in the visual analysis, this shift in system complexity corresponds with a shift from a pelagic to a more benthic-dominated system from summer to winter. Both the SIENA model and the visualization in NETDRAW support the conclusions of Baird and Ulanowicz [Baird, D., Ulanowicz, R.E., 1989. Seasonal dynamics of the Chesapeake Bay ecosystem. Ecol. Monogr. 501 (59), 329–364] that there was an increase in the Chesapeake Bay ecosystem's ascendancy in the winter. We explain such reduced complexity in winter as a system response to lowered temperature and decreased solar energy input, which causes a decline in the production of new carbon, forcing nodes to go extinct; this causes a change in the structure of the system, making it simpler and more efficient than in summer. It appears that the seasonal dynamics of the trophic structure of Chesapeake Bay can be modeled effectively using the SIENA statistical model for network change.     

Assessing drought-related ecological risk in the Florida Everglades

In the winter-spring of 2001, South Florida experienced one of the worst droughts in its recorded history. Out of a myriad of ecological concerns identified during this time, the potential for catastrophic peat fire and negative impacts to wading bird reproduction emerged as critical issues. Water managers attempted to strike a balance between the environment and protection of water supplies for agriculture and urban interests. It became evident, however, that a broad-scale, integrated way to portray and prioritise ecological stress was lacking in the Florida Everglades, despite this being considered a necessary tool for addressing issues of environmental protection. In order to provide a framework for evaluating various water management operations using real-time information, we developed GIS-based indices of peat-fire risk and wading bird habitat suitability. These indices, based on real physical, chemical, and biological data, describe two ecological conditions that help define the physical and biological integrity of the Everglades. In addition to providing continuous, updated assessments throughout the drought period, we incorporated predictive models of water levels to evaluate how various water management alternatives might exacerbate or alleviate ecological stress during this time.     

Synergistic interactions between edge and area effects in a heavily fragmented landscape

Both area and edge effects have a strong influence on ecological processes in fragmented landscapes, but there is little understanding of how these two factors might interact to exacerbate local species declines. To test for synergistic interactions between area and edge effects, we sampled a diverse beetle community in a heavily fragmented landscape in New Zealand. More than 35,000 beetles of approximately 900 species were sampled over large gradients in habitat area (10(-2) 10(6) ha) and distance from patch edge (2(0)-2(10) m from the forest edge into both the forest and adjacent matrix). Using a new approach to partition variance following an ordination analysis, we found that a synergistic interaction between habitat area and distance to edge was a more important determinant of patterns in beetle community composition than direct edge or area effects alone. The strength of edge effects in beetle-species composition increased nonlinearly with increasing fragment area. One important consequence of the synergy is that the slopes of species area (SA) curves constructed from habitat islands depend sensitively on the distance from edge at which sampling is conducted. Surprisingly, we found negative SA curves for communities sampled at intermediate distances from habitat edges, caused by differential edge responses of matrix- vs. forest-specialist species in fragments of increasing area. Our data indicate that distance to habitat edge has a consistently greater impact on beetle community composition than habitat area and that variation in the strength of edge effects may underlie many patterns that are superficially related to habitat area.     

Hagfish in the New Zealand fjords are supported by chemoautotrophy of forest carbon

Forest litter is often considered to be a minor energy source to marine communities due to its refractory nature. Large volumes of forest litter are deposited in the New Zealand fjords, and likely recycled into available energy by microbial activity. In this study we used evidence from stable isotope analyses to test whether recycled carbon from chemoautotrophs was an important contributor to the diet of hagfish (Eptatretus cirrhatus). We then analyzed fatty acid biomarkers from the chemoautotrophic clam Solemya parkinsoni and E. cirrhatus to further discriminate the contribution of marine, terrestrial, and chemoautotrophic sources. Bulk isotopic signatures of E. cirrhatus varied considerably (delta13C, from -29.2 per thousand to -16.7 per thousand; delta15N, from -2.8 per thousand to +15.5 per thousand; delta34S, from -21.7 per thousand to +16.7 per thousand) and indicated that a significant percentage of organic matter (38-51%) originated from chemoautotrophs (delta13C, -31.3 per thousand +/- 0.1 per thousand [mean +/- SE]; delta15N, -5.7 per thousand +/- 0.2 per thousand; delta34S, -32.per thousand +/- 3.8 per thousand). Fatty acid biomarkers were depleted in 13C, particularly cis-vaccenic acid (18:1omega7: delta13C, -39.0 per thousand) indicating specific microbial origins of carbon. A high proportion of forest litter in sediments, coupled with isotopic and fatty acid biomarker results, indicates that terrestrial organic matter is a dominant contributor to this marine benthic system. This study demonstrates a clear linkage between terrestrial and marine ecological processes.     

金属基工程纳米颗粒与水生高等植物的相互作用：研究现状综述

如今释放到水体环境中的工程纳米颗粒(ENP)数量与日俱增。为确保生态健康,需要进行相关的风险评估。本文综述了金属基ENP与水生高等植物之间的相互作用,找到了信息缺口并提出对未来研究的构想,为在该领域内的进一步探索提供了基础。本文讨论集中在以下3点：1. ENP的生物利用性;2. 生物对ENP的摄取、消化、转移以及生物累积;3. ENP对水生高等植物的毒性效果。由于ENP自身特性所带来的影响不明确以及水质状况记载情况不佳,ENP的摄取及相关动力学方面存在着很大的信息差距。分解似乎是驱动ENP生物累积的一种关键机制,然而纳米颗粒却常常被一些有着极少内化作用的植物的表面所吸收。然而,关于ENP在植物内的内化作用鲜有记载,因此纳米颗粒的内化作用对于生物累积及毒性的影响尚不明确。即使金属基ENP的纳米毒性已被报道,分解依然被认为是其毒性的主要机制。为推动该领域内的研究发展,未来的研究需结合ENP自身特性的影响、水体的理化参数以及它们之间的相互作用。相互作用对于ENP的生物利用性和对水生高等植物健康的风险都有重要影响。为了快速追踪类似数据的产生,我们建议测试方案趋向一致化。
精选自Melusi Thwala, Stephen J. Klaine, Ndeke Musee. Interactions of metal-based engineered nanoparticles with aquatic higher plants: a review of the state of current knowledge. Environmental Toxicology and Chemistry: Volume 35, Issue 7, pages 1677–1694, July 2016. DOI: 10.1002/etc.3364
详情请见http://onlinelibrary.wiley.com/doi/10.1002/etc.3364/full
     

Explaining the fragmentation in the Brazilian Amazonian forest

Although vast literature exists on the drivers of tropical deforestation and its ecological consequences, less is known about how patterns of forest fragmentation emerge in the first place. The purpose of this paper is to address this issue for the Brazilian portion of the Amazon basin by analyzing the social processes generative of five specific patterns, including rectangular, fishbone, radial, dendritic, and what we refer to as ‘the stem of the rose.’ We argue that forest fragmentation patterns in the Brazilian Amazon are largely determined by the types and arrival times of the agents who engage in land clearing. We also argue that the patterns manifest in the landscape by virtue of road construction and agricultural property formation, which often occur in tandem. We conclude by placing our discussion within legal and institutional contexts, and observe that fragmentation stemming from formal colonization projects is more consistent with biodiversity conservation than that associated with a laissez-faire occupation. However, erosive impacts may be greater in topographically sensitive areas.     

Bacterial Degradation of Vegetable Oils

Following initial experiments presented elsewhere (2IOPS), the bacterial degradation of two vegetable oils was investigated in some detail. the number of aerobic and anaerobic heterotrophic bacteria, oil degrading and sulphate reducing bacteria were quantified during simulated spills on a salt marsh. the sediment fatty acid composition was also studied using GC-MS analysis. Degradation of linseed and sunflower oils was concomitant with an increase in the numbers of aerobic and anaerobic bacteria. Fatty acids analysis revealed preferential degradation of the principal components of the oils (18:3ω3 for linseed oil and 18:2ω6 for sunflower oil). the presence of several isomers of the usual polyunsaturated fatty acids was also detected. the identification of some of these new fatty acids has been carried out. Possible pathways of degradation of these vegetable oils are suggested.     

Catching the Boomerang: EM,The World Bank,and Excess Accountability: A Case Study of the Bujagali Falls Hydropower Project Uganda

The World Bank has shifted its accountability over the past two decades away from borrowing countries towards external groups, such as advocacy non-governmental organizations (NGOs). One conduit for this external accountability is the environmental impact assessment (EM) process. EIA has both theoretical and practical challenges when applied in developing countries, but is bound by Bank guidelines designed in developed countries. Using the Bujagali Falls Hydropower Project, Uganda as a case study, this paper will demonstrate that the increase in external accountability at the World Bank via EIA has a negative effect on governments and civil society in the South and on global governance.