Partitioning Theory Research Articles

Biomass, Carbon and Nitrogen Partitioning and Water Use Efficiency Differences of Five Types of Alpine Grasslands in the Northern Tibetan Plateau.

(1) Background: Grassland covers most areas of the northern Tibetan Plateau along with important global terrestrial carbon (C) and nitrogen (N) pools, so there is a need to better understand the different alpine grassland growth associated with ecosystem C, N storage and water use efficiency (WUE). (2) Methods: The plant biomass and C, N concentrations, stocks and vegetation WUE of five kinds of alpine grassland types were investigated in northern Tibetan Plateau. (3) Results: The results showed that there were significant differences among five types of alpine grasslands in aboveground biomass (AGB), belowground biomass (BGB), total biomass (TB) and root:shoot (R/S) ratio while the highest value of different indices was shown in alpine meadow type (AM). The AGB and BGB partitioning results significantly satisfied the allometric biomass partitioning theory. The C, N concentrations and C/N of the vegetation in AGB and BGB showed significant grassland type differences. The highest C, N stocks of BGB were in AM which was almost six or seven times more than the C, N stocks of AGB in alpine desert type (AD). There were significant differences in δ13C and intrinsic water use efficiency (WUEi) under five alpine grassland types while the highest mean values of foliar δ13C and WUEi were in AD. Significant negative correlations were found between WUEi and C, N concentrations, C/N of AGB and soil water content (SWC) while the correlation with BGB C/N was not significant. For AGB, BGB, TB and R/S, there were positive correlations with C, N concentrations of AGB, BGB and SWC while it had significant negative correlations with C/N of BGB. (4) Conclusions: With regard to its types, it is suggested that the AM or AS may be an actively growing grassland type in the northern Tibetan Plateau.

The Protective Role of Non-Photochemical Quenching in PSII Photo-Susceptibility: A Case Study in the Field.

Non-photochemical quenching (NPQ) has been regarded as a safety valve to dissipate excess absorbed light energy not used for photochemistry. However, there exists no general consensus on the photoprotective role of NPQ. In the present study, we quantified the Photosystem II (PSII) photo-susceptibilities (mpi) in the presence of lincomycin, under red light given to five shade-acclimated tree species grown in the field. Photosynthetic energy partitioning theory was applied to investigate the relationships between mpi and each of the regulatory light-induced NPQ [Y(NPQ)], the quantum yield of the constitutive nonregulatory NPQ [Y(NO)] and the PSII photochemical yield in the light-adapted state [Y(PSII)] under different red irradiances. It was found that in the low to moderate irradiance range (50-800 μmol m-2 s-1) when the fraction of open reaction centers (qP) exceeded 0.4, mpi exhibited no association with Y(NPQ), Y(NO) and Y(PSII) across species. However, when qP < 0.4 (1,500 μmol m-2 s-1), there existed positive relationships between mpi and Y(NPQ) or Y(NO) but a negative relationship between mpi and Y(PSII). It is postulated that both Y(NPQ) and Y(NO) contain protective and damage components and that using only Y(NPQ) or Y(NO) metrics to identify the photo-susceptibility of a species is a risk. It seems that qP regulates the balance of the two components for each of Y(NPQ) and Y(NO). Under strong irradiance, when both protective Y(NPQ) and Y(NO) are saturated/depressed, the forward electron flow [i.e. Y(PSII)] acts as the last defense to resist photoinhibition.

A consensus-reaching method for large-scale group decision-making based on integrated trust–opinion similarity relationships

Recently, the consensus-reaching process (CRP) of large-scale group decision-making (LSGDM) has attracted much attention. Trusting relationships and similar opinions among decision makers have been proven to exert important but different impacts on large-scale group consensus. We propose a large-scale group consensus-reaching method based on integrated relationships between trust and the similarity of opinions (“opinion similarity”). First, we propose a directed tuple of trust and opinion similarity to blend the information about trust and opinion similarity among decision makers, and construct an integrated relationship network among decision makers based on trust and opinion similarity. Second, leadership-based network partitioning theory is used to divide the integrated relationship network, and the decision maker with the highest degree of recommendation is selected as the representative of each subnetwork. Considering the strength of the integrated relationships and the similarity of opinions of the subnetworks, we add directed edges between the representative of each subnetwork and the rest of the subnetworks, to ensure that leaders exist between all subnetworks, which is effective for reaching group consensus. In an integrated relationship network, decision makers’ opinions are evolved using opinion dynamics theory to obtain group consensus results. Finally, a numerical experiment is used to illustrate the feasibility of the proposed method, and comparative analysis demonstrates its advantages. The proposed large-scale group consensus-reaching method based on integrated trust–opinion similarity relationships can significantly reduce the initial changes in the opinions of decision makers and is applicable to solving a variety of practical problems related to large-scale group decision-making.

Tutorial: Dynamic organic growth modeling with a volatility basis set

Organic aerosols are ubiquitous in the atmosphere and oxygenated organics are a major driver of aerosol growth. The volatility basis set (VBS) as introduced by Donahue et al. (2006, 2011) is often used to simplify the partitioning behavior of the huge variety of atmospheric organics. Recently, the VBS was used to dynamically model aerosol growth from the smallest sizes onwards. This tutorial is intended to equip the reader with the necessary tools to facilitate organic growth modelling based on gas-phase measurements of oxygenated organics using a 2-dimensional VBS. We start with a contextualization of the VBS in partitioning theory and point out the need for dynamic modeling. We provide an overview on the most common methods to estimate the volatility of oxygenated organics and give detailed instruction on how to construct the binned VBS. We then explain the dynamic condensation model including solution and curvature effects. Furthermore, we provide a python package for VBS growth calculations and show with two examples from ambient and chamber measurements how growth rates can be calculated. Last, we summarize the limitation of this approach and outline necessary future developments.

Modelling polycyclic aromatic hydrocarbon bioavailability in historically contaminated soils with six in-vitro chemical extractions and three earthworm ecotypes

Accurate prediction of organic contaminant bioavailability for risk assessment in ecological applications is hindered by limited validation on relevant bioassay species. Here, six in-vitro chemical extraction methods (butanol, non-buffered and buffered hydroxypropyl-β-cyclodextrin (HPCD, Buf-HPCD), Tenax, potassium persulfate oxidation, polyoxymethylene solid phase extraction (POM)) were tested for PAH bioaccumulation prediction in three earthworm ecotypes with dissimilar exposures, Amynthas sp., Eisenia fetida, and Lumbricus terrestris, in historically contaminated soils from manufactured gas plant (MGP) sites. Extractions were compared directly and modelled in a calculation approach using equilibrium partitioning theory (EqPT) with a novel combination of different organic carbon/octanol-water partitioning parameters (KOC and KOW). In the direct comparison approach Buf-HPCD showed the closest prediction of accumulation for burrowing Amynthas sp. and L. terrestris (within 1.5 and 3.1, respectively), but Tenax and POM showed the closest approximation for E. fetida (within 1.1 and 0.9, respectively). The optimum method for predicting PAH bioaccumulation in the calculation approach depended on earthworm species and the partitioning parameters used in equations of the four models, but overall POM, which was independent of KOC, showed the closest approximation of accumulation, within a factor of 2.5 across all species. This work effectively identifies the optimum in-vitro based approaches for PAH bioavailability prediction in earthworms as a model soil health indicator for ecological risk assessment within regulatory and remediation decision frameworks.

Cost Partitioning Heuristics for Stochastic Shortest Path Problems

In classical planning, cost partitioning is a powerful method which allows to combine multiple admissible heuristics while retaining an admissible bound. In this paper, we extend the theory of cost partitioning to probabilistic planning by generalizing from deterministic transition systems to stochastic shortest path problems (SSPs). We show that fundamental results related to cost partitioning still hold in our extended theory. We also investigate how to optimally partition costs for a large class of abstraction heuristics for SSPs. Lastly, we analyze occupation measure heuristics for SSPs as well as the theory of approximate linear programming for reward-oriented Markov decision processes. All of these fit our framework and can be seen as cost-partitioned heuristics.

Theory, method and application advance of isotopic flux partitioning of ecosystem photosynthesis and respiration

Photosynthesis and respiration are two important components of net ecosystem exchange (NEE). NEE can be directly observed by eddy covariance (EC) technique, and statistically separated into ecosystem assimilation and respiration based on the statistical flux partitioning of temperature response function or light-response curves. However, these methods would result in auto-correlation between assimilation and respiration, and overestimate daytime respiration. Recently-developed isotope ratio infrared spectroscopy permits high-resolution measurement of atmospheric CO2 and its stable carbon isotope composition (δ13C) under field conditions, and achieves diurnal and seasonal partitioning of ecosystem photosynthesis and respiration by matching with NEE measurements from EC. We expounded the fundamental theories and assumptions of isotopic flux partitioning of ecosystem photosynthesis and respiration, elaborated the development and application advance of techniques in isotopic flux measurement, summarized the advance of isotopic flux partitioning to provide new insight into the assimilation and respiration processes, and prospected the uncertainty of isotopic flux partitioning theory and the necessity of comparative researches of various methods.

Inter-cluster competition and resource partitioning may govern the ecology of Frankia.

Microbes live in a complex communal ecosystem. The structural complexity of microbial community reflects diversity, functionality, as well as habitat type. Delineation of ecologically important microbial populations along with exploration of their roles in environmental adaptation or host-microbe interaction has a crucial role in modern microbiology. In this scenario, reverse ecology (the use of genomics to study ecology) plays a pivotal role. Since the co-existence of two different genera in one small niche should maintain a strict direct interaction, it will be interesting to utilize the concept of reverse ecology in this scenario. Here, we exploited an 'R' package, the RevEcoR, to resolve the issue of co-existing microbes which are proven to be a crucial tool for identifying the nature of their relationship (competition or complementation) persisting among them. Our target organism here is Frankia, a nitrogen-fixing actinobacterium popular for its genetic and host-specific nature. According to their plant host, Frankia has already been sub-divided into four clusters C-I, C-II, C-III, and C-IV. Our results revealed a strong competing nature of CI Frankia. Among the clusters of Frankia studied, the competition index between C-I and C-III was the largest. The other interesting result was the co-occurrence of C-II and C-IV groups. It was revealed that these two groups follow the theory of resource partitioning in their lifestyle. Metabolic analysis along with their differential transporter machinery validated our hypothesis of resource partitioning among C-II and C-IV groups.

CO2 exchange of the ecosystem–atmosphere in a mountain forest ecosystem: Combining stable carbon isotope (δ13C) and soil respiration measurements

Stable carbon isotopes (δ13C) are a useful technique to partition the net ecosystem–atmosphere exchange (NEE) of carbon dioxide (CO2) into gross primary productivity (GPP) and respiratory (R) components. The acquisition of ecosystem flux is usually performed using the eddy covariance (EC) technique, but this method is limited under complex terrain conditions and stable atmospheric conditions. Here, we try to develop the flux partitioning theory of mountain forest ecosystem by combining isotope technology and soil respiration. We used a full growing season of isotopic profile data and soil respiration data from a temperate deciduous forest on Jiufeng Mountain to demonstrate the method and quantify its uncertainties. We found that the assessable systematic uncertainty was ± 29.97% for NEE, ±24.87% for GPP, and ± 36.82% for R. The factors that most strongly affected the uncertainties of GPP and R were canopy CO2 stomatal conductance (gco2), calculated by the Köstner model, and the carbon isotope value of the total respiration in the ecosystem at night (δ13Cn-eco), calculated by the Keeling plot method. The advantage of isotopic methods is not only the relief of terrain restrictions but also the stable atmospheric conditions. The method provides an innovative vision for the partitioning of flux in forest ecosystems, especially for mountain forests.

Biomass partitioning of plants under soil pollution stress

Polluted sites are ubiquitous worldwide but how plant partition their biomass between different organs in this context is unclear. Here, we identified three possible drivers of biomass partitioning in our controlled study along pollution gradients: plant size reduction (pollution effect) combined with allometric scaling between organs; early deficit in root surfaces (pollution effect) inducing a decreased water uptake; increased biomass allocation to roots to compensate for lower soil resource acquisition consistent with the optimal partitioning theory (plant response). A complementary meta-analysis showed variation in biomass partitioning across published studies, with grass and woody species having distinct modifications of their root: shoot ratio. However, the modelling of biomass partitioning drivers showed that single harvest experiments performed in previous studies prevent identifying the main drivers at stake. The proposed distinction between pollution effects and plant response will help to improve our knowledge of plant allocation strategies in the context of pollution.

Understanding Effects of Competition and Shade Tolerance on Carbon Allocation with a Carbon Balance Model

A carbon-balance model based on mechanistic and allometric relationships (CroBas) was used to assess the effects of competition in C allocation in jack pine (Pinus banksiana Lamb.), a shade-intolerant species, and black spruce (Picea mariana (Mill.) B.S.P.), a moderately shade-tolerant species. For both species, model efficiencies ranged from 36 to 99%. The average model bias was lower than 11% and 18% for jack pine and black spruce, respectively. For both jack pine and black spruce, the total tree C increased over the years, with greater increases noted for decreasing competition. When considering a C compartment as a ratio of the total tree C, decreasing competition resulted for both species in decreasing stem C and increasing C in branches and foliage. When considering the amount of C in a given compartment, for jack pine, decreasing competition led to greater C stem, branches, foliage, and roots, whereas, for black spruce, it also increased its stem C but lately shifted at about 20 years, following thinning; thus, the changing C allocation over time results from both “passive plasticity”, reflecting environmentally induced variations in growth, and “ontogenetic plasticity”, referring to variations in the ontogenetic trajectory of a trait. Overall, the C allocation to stem and foliage relative to the total tree C generally decreased as competition decreased, supporting the optimal partitioning theory. These C-allocation patterns were related to the species’ shade tolerance and illustrated how jack pine and black spruce maximize their competitive fitness.

Soil N enrichment mediates carbon allocation through respiration in a dominant grass during drought

Abstract Carbon (C) allocation strategy plays a critical role in plant adaptability, which are also important to assess the productivity stability under environmental change. Based on optimal partitioning theory, we asked two questions: (1) How is plant C allocation within tissues affected by nutrient enrichment (N addition)? And (2) does long‐term N addition alter how plants allocate C under drought? To address these questions, we conducted a greenhouse experiment using the widespread perennial C3 grass, Leymus chinensis, under four treatments: ‘Watered’, ‘Dry’, ‘Watered + N’ and ‘Dry + N’. 13CO2 pulse labelling was used to trace C transport through the plant–soil system. We found that drought and N addition resulted in additive effects on C allocation. Greater above‐ground biomass under N addition resulted in higher C loss via above‐ground plant respiration, even under drought, which plays a more important role in the adjustment of root:shoot ratio than does the trade‐off between above‐ and below‐ground organs. Compared to the concept of active phenotype adjustment for maximized growth rate in traditional optimal partitioning theory, our results imply that pre‐drought allometry, which changes under long‐term resource addition, also determines how plants respond to drought and their adaptability to changing environmental conditions. Read the free Plain Language Summary for this article on the Journal blog.

Refining our understanding of metal bioavailability in sediments using information from porewater: Application of a multimetal biotic ligand model as an extension of the equilibrium partitioning sediment benchmarks.

The equilibrium partitioning sediment benchmarks (ESBs) derived by the US Environmental Protection Agency (USEPA) in 2005 provide a mechanistic framework for understanding metal bioavailability in sediments by considering equilibrium partitioning (EqP) theory, which predicts that metal bioavailability in sediments is determined largely by partitioning to sediment particles. Factors that favor the partitioning of metals to sediment particles, such as the presence of acid volatile sulfide (AVS) and sediment organic matter, reduce metal bioavailability to benthic organisms. Because ESBs link metal bioavailability to partitioning to particles, they also predict that measuring metals in porewater can lead to a more accurate assessment of bioavailability and toxicity to benthic organisms. At the time of their development, sediment ESBs based on the analysis of porewater metal concentrations were limited to comparison with hardness-dependent metals criteria for the calculation of interstitial water benchmark units (IWBUs). However, the multimetal biotic ligand model (mBLM) provides a more comprehensive assessment of porewater metal concentrations, because it considers factors in addition to hardness, such as pH and dissolved organic carbon, and allows for interactions between metals. To evaluate the utility of the various sediment and porewater ESBs, four Hyalella azteca bioassay studies were identified that included sediment and porewater measurements of metals and porewater bioavailability parameters. Evaluations of excess simultaneously extracted metals, IWBUs, and mBLM toxic units (TUs) were compared among the bioassay studies. For porewater, IWBUs and mBLM TUs were calculated using porewater metal concentrations from samples collected using centrifugation and peepers. The percentage of correct predictions of toxicity was calculated for each benchmark comparison. The mBLM-based assessment using peeper data provided the most accurate predictions for the greatest number of samples among the evaluation methods considered. This evaluation demonstrates the value of porewater-based evaluations in conjunction with sediment chemistry in understanding toxicity observed in bioassay studies. Integr Environ Assess Manag 2022;18:1335-1347. © 2021 SETAC.

Comparison of Species Sensitivity Distributions for Sediment-Associated Nonionic Organic Chemicals Through Equilibrium Partitioning Theory and Spiked-Sediment Toxicity Tests with Invertebrates.

Equilibrium partitioning (EqP) theory and spiked‐sediment toxicity tests are useful methods to develop sediment quality benchmarks. However, neither approach has been directly compared based on species sensitivity distributions (SSDs) to date. In the present study, we compared SSDs for 10 nonionic hydrophobic chemicals (e.g., pyrethroid insecticides, other insecticides, and polycyclic aromatic hydrocarbons) based on 10–14‐day spiked‐sediment toxicity test data with those based on EqP theory using acute water‐only tests. Because the exposure periods were different between the two tests, effective concentrations (i.e., median effective/lethal concentration) were corrected to compare SSDs. Accordingly, we found that hazardous concentrations for 50% and 5% of species (HC50 and HC5, respectively) differed by up to a factor of 100 and 129 between the two approaches, respectively. However, when five or more species were used for SSD estimation, their differences were reduced to a factor of 1.7 and 5.1 for HC50 and HC5, respectively, and the 95% confidence intervals of HC50 values overlapped considerably between the two approaches. These results suggest that when the number of test species is adequate, SSDs based on EqP theory and spiked‐sediment tests are comparable in sediment risk assessments. Environ Toxicol Chem 2022;41:462–473. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Differential accumulation of polycyclic aromatic hydrocarbons (PAHs) in three earthworm ecotypes: Implications for exposure assessment on historically contaminated soils

This study compared accumulation of the 16 US-EPA priority polycyclic aromatic hydrocarbons (PAHs) in three different earthworm ecotypes, Amynthas sp., Eisenia fetida, and Lumbricus terrestris, in four historically (> 50 years) contaminated manufactured gas plant (MGP) soils using bioassays. Epi-endogeic deep burrowing and soil ingesting Amynthas sp. accumulated significantly more ∑16 PAHs than any other species (upto 8.7 times more), and epigeic surface dwelling E. fetida showed the lowest ∑16 PAH accumulation. Results indicated the importance of earthworm habit and physiology on PAH partitioning into earthworm lipids. Exposure to soil borne PAHs via the gut, as compared with passive diffusion from pore water, was important in species tested, being most evident in burrowing species Amynthas sp. and L. terrestris and for the desorption-resistant higher molecular weight (HMW) PAHs. Biota-soil accumulation factors (BSAF) were low, as influenced by aging, sequestration and strong PAH sorption to secondary sorptive phases in the historically contaminated soils. Bioconcentration factors (BCFs) calculated from freely dissolved pore water PAH concentrations derived from polyoxymethylene solid-phase extractions (POM) were species specific, indicating stronger relationships with octanol-water partition coefficient (KOW) for Amynthas sp. and L. terrestris than for E. fetida. Modelling demonstrated that KOW values were not a reliable proxy for BCF in equilibrium partitioning theory (EqPT) to predict bioavailability for the range of earthworms tested, being less accurate for E. fetida compared to the burrowing species. The study showed that including burrowing and soil feeding earthworm species, such as Amynthas sp. and L. terrestris, in standard testing would benefit regulatory decisions for more accurate quantification of PAH bioavailability in ecological risk assessment on historically contaminated soils.

Application of optimal set partitioning theory to solving problems of artificial intelligence and pattern recognition

The paper substantiates the possibility of applying the mathematical theory of continuous problems of optimal partitioning of sets of n-dimensional Euclidean space, which belong to the non-classical problems of infinite-dimensional mathematical programming, to the solution of problems of artificial intelligence and pattern recognition. The problems of pattern recognition both in conditions of certainty and in conditions of uncertainty are formulated. A particular attention is paid to the application of methods of the theory of optimal partitioning for the construction of fuzzy Voronoi diagrams. Examples of constructing fuzzy Voronoi diagrams with the optimal placement of generating points are given.

Interpreting spatial layouts of nursing homes based on partitioning theory

ABSTRACT With the aging world and the improvement of people’s living standards, the quality of elderly life is gaining more attention. The nursing home is an important carrier for the life of the elderly, the reasonable layout of its spaces can provide a better wayfinding experience for residents. Based on the survey of 168 Japanese nursing homes, we found that some spatial layouts are more widely used in the design of nursing homes than others. The intention of this paper is to attempt to explore the characteristics of these spatial layouts within the theoretical framework of space syntax. The expectation is to discover certain design principles that are followed when the spaces in the nursing home are arranged, seeking to contribute to a better understanding of nursing home morphology. Setting out from the spatial models established by partitioning theory research, the paper examines the impacts of the different numbers of corridors, different corridor combinations, and different spatial distribution on their subjects. The result shows that designers will consider a combination of influencing factors when designing the spatial layout of the nursing home. In terms of the number of corridor and corridor combinations, the spatial layout which facilitates the residents’ wayfinding is adopt in more nursing home plans, but in terms of spatial distribution, the plan layout of nursing homes is more focused on a balanced design. Finally, this paper analyses the design principles of spatial layout for nursing homes by using spatial syntax theory and method based on experience. It suggests that the theory and method can provide designers with a new way of thinking about understanding architectural space.

Changes in Root-Shoot Allometric Relations in Alpine Norway Spruce Trees After Strip Cutting.

Silvicultural interventions such as strip cuttings can change the resource availability of the edge trees. This may alter tree allometry, as light regime, water, and nutrient availability can change at the forest edge. Increased root growth may optimize resource uptake and/or enhance tree anchorage to withstand the altered wind regime. However, little is known about the patterns of the root–shoot allometric responses to strip cuttings. In three alpine stands differing in climate, site productivity, and stand characteristics, we selected 71 Norway spruce trees and took increment cores from stems, root collars, and main roots. This enabled us to study changes in the long-term root-stem allometry for 46 years and short-term allometric responses to intervention. The effects of cutting were compared between edge trees and trees from the stand interior in 10 years before and after the intervention. The long-term allocation to roots increased with stem diameter, with the strongest effects on the regularly managed stand with the tallest and largest trees. These results support the allometric biomass partitioning theory, which postulates resource allocation patterns between different plant organs to depend on plant size. Strip cutting on north-facing slopes boosted edge-tree growth in all plant compartments and enhanced allocation to roots. This change in allometry started 2 years after cutting but disappeared 7–8 years later. In the post-cutting period, the highest root–shoot increase was observed in the small trees independent of the site. This indicates the change in growing conditions to have the strongest effects in formerly suppressed trees. Thus, the effect of such acclimation on the wind firmness of subdominant spruce trees is a question with high importance for optimizing cutting layouts in lowering post-cutting vulnerability to disturbance. The results from this case study contribute to a better understanding of the structural acclimation of spruce trees from high-elevation forests to new forest edges. However, for a more mechanistic understanding of environmental drivers, further analyses of tree-ring stable isotopes are recommended.

Using GECKO-A to derive mechanistic understanding of secondary organic aerosol formation from the ubiquitous but understudied camphene

Abstract. Camphene, a dominant monoterpene emitted from both biogenic and pyrogenic sources, has been significantly understudied, particularly in regard to secondary organic aerosol (SOA) formation. When camphene represents a significant fraction of emissions, the lack of model parameterizations for camphene can result in inadequate representation of gas-phase chemistry and underprediction of SOA formation. In this work, the first mechanistic study of SOA formation from camphene was performed using the Generator for Explicit Chemistry and Kinetics of Organics in the Atmosphere (GECKO-A). GECKO-A was used to generate gas-phase chemical mechanisms for camphene and two well-studied monoterpenes, α-pinene and limonene, as well as to predict SOA mass formation and composition based on gas/particle partitioning theory. The model simulations represented observed trends in published gas-phase reaction pathways and SOA yields well under chamber-relevant photooxidation and dark ozonolysis conditions. For photooxidation conditions, 70 % of the simulated α-pinene oxidation products remained in the gas phase compared to 50 % for limonene, supporting model predictions and observations of limonene having higher SOA yields than α-pinene under equivalent conditions. The top 10 simulated particle-phase products in the α-pinene and limonene simulations represented 37 %–50 % of the SOA mass formed and 6 %–27 % of the hydrocarbon mass reacted. To facilitate comparison of camphene with α-pinene and limonene, model simulations were run under idealized atmospheric conditions, wherein the gas-phase oxidant levels were controlled, and peroxy radicals reacted equally with HO2 and NO. Metrics for comparison included gas-phase reactivity profiles, time-evolution of SOA mass and yields, and physicochemical property distributions of gas- and particle-phase products. The controlled-reactivity simulations demonstrated that (1) in the early stages of oxidation, camphene is predicted to form very low-volatility products, lower than α-pinene and limonene, which condense at low mass loadings; and (2) the final simulated SOA yield for camphene (46 %) was relatively high, in between α-pinene (25 %) and limonene (74 %). A 50 % α-pinene + 50 % limonene mixture was then used as a surrogate to represent SOA formation from camphene; while simulated SOA mass and yield were well represented, the volatility distribution of the particle-phase products was not. To demonstrate the potential importance of including a parameterized representation of SOA formation by camphene in air quality models, SOA mass and yield were predicted for three wildland fire fuels based on measured monoterpene distributions and published SOA parameterizations for α-pinene and limonene. Using the 50/50 surrogate mixture to represent camphene increased predicted SOA mass by 43 %–50 % for black spruce and by 56 %–108 % for Douglas fir. This first detailed modeling study of the gas-phase oxidation of camphene and subsequent SOA formation highlights opportunities for future measurement–model comparisons and lays a foundation for developing chemical mechanisms and SOA parameterizations for camphene that are suitable for air quality modeling.

Beyond the limit: carrying capacity (K) and the holism/reductionism debate.

As the debate about holism and reductionism in ecology has ebbed in the last twentyyears, this article aims to reassess the traditional opposition between holistic and reductionist epistemologies during the development of population biology. The history of the notion of carrying capacity, the upper demographic limit of a viable population, will be analyzed as a paradigmatic case of the progressive imposition of reductionist strategies, from both an epistemological and a semantic point of view, since the middle of the twentieth century. Then, Richard Looijen's reduction of the carrying capacity concept to the niche partitioning theory will be assessed and rebuked for both empirical and logical reasons. Eventually, some recent "weak" and "hard" emergent conceptualizations of the notion of carrying capacity, in logistic map models or in coupled niche-population systems, will be presented in order to show how they call into question the nature and the use of the notion of carrying capacity as a predefined ecological limit.