Influence of root structure on root survivorship: an analysis of 18 tree species using a minirhizotron method

Fine root survivorship is an important aspect of root ecology and is known to be influenced by a suite of covariates. However, the relative importance of each covariate on root survivorship is not clear. Here, we used minirhizotron-based data from 18 woody species to evaluate the relative strength of influence on root survivorship by root diameter, branch order, soil depth, and season of root birth, and to examine how the relationship between each covariate and root survivorship differed across species. We extracted hazard ratio estimates for 16 species from published studies that performed Cox proportional hazards regression analysis, and from our own unpublished data for two Chinese temperate tree species. The mean change in hazard ratio (CHR) and corresponding coefficient of variation for each factor were calculated across species. On average, root diameter and season of root birth had stronger effects on root survivorship than branch order and soil depth. However, the effects of season varied with species and were stronger in temperate forests, whereas the influence of diameter and order were relatively consistent across species. These results suggest that root structures such as diameter and branch order should be carefully considered in root classification and sampling, and adding season of birth (particularly in temperate forests) as a covariate in root survivorship analysis should further enhance our ability in achieving a better understanding of root demography and more accurate estimates of root turnover in forests of different climate zones.     

Improved retrieval of Secchi depth for optically-complex waters using remote sensing data

Water transparency is one of the ecological indicators for describing water quality and the underwater light field which determines its productivity. In the European Water Framework Directive (WFD) as well as in the European Marine Strategy Framework Directive (MSFD) water transparency is used for ecological status classification of inland, coastal and open sea waters and it is regarded as an indicator for eutrophication in Baltic Sea management (HELCOM, 2007). We developed and compared different empirical and semi-analytical algorithms for lakes and coastal Nordic waters to retrieve Secchi depth (Z_SD) from remote sensing data (MERIS, 300 m resolution). The algorithms were developed in water bodies with high coloured dissolved organic matter absorption (a_CDOM(442) ranging 1.7–4.0 m⁻¹), Chl a concentration (0.5–73 mg m⁻³) and total suspended matter (0.7–37.5 g m⁻³) and validated against an independent data set over inland and coastal waters (0.6 m < Z_SD < 14.8 m). The results indicate that for empirical algorithms, using longer wavelengths in the visible spectrum as a reference band decreases the RMSE and increases the coefficient of determination (R²). The accuracy increased (R² = 0.75, RMSE = 1.33 m, n = 134) when Z_SD was retrieved via an empirical relationship between Z_SD and K_d(490). The best agreement with in situ data was attained when Z_SD was calculated via both the diffuse and the beam attenuation coefficient (R² = 0.89, RMSE = 0.77 m, n = 89). The results demonstrate that transparency can be retrieved with high accuracy over various optical water types by the means of ocean color remote sensing, improving both the spatial and temporal coverage. The satellite derived Z_SD product could be therefore used as an additional source of information for WFD and MSFD reporting purposes.     

Soil core and minirhizotron comparison for the determination of root length density

Detailed knowledge of the distribution of roots in the soil is important in understanding the extraction of water and nutrients from soil. Various techniques have been developed to monitor root-length density under field conditions. Excavation techniques, including soil cores, have long been considered to give reliable estimates of root-length density, but these techniques are laborious in sample collection and tedious in determination of root lengths. An attractive alternative for monitoring root-length density has been the minirhizotron whereby a periscope is inserted into a clear tube permanently installed in the soil for repeated and rapid measures of root development. The objective of this study was to compare the ability of the minirhizotron technique to measure root-length density as compared to the root-core technique.As in previous studies, substantial disagreement existed between the two techniques in the top 30-cm of the soil. The results from the minirhizotron consistently indicated a much lower root population than the root-core technique in the surface layer of soil. This is especially worrisome because more than 45% of the root-length density was found in this layer with the root-core technique. At deeper soil layers, the minirhizotron data proved to be no less variable than the root-core technique making the determination of statistically significant results difficult. Finally, the relationship between the minirhizotron and soil-core results varied with time even when the observations from the soil surface layer were ignored. Attempts to directly translate minirhizotron observations into a root-length density using a correlation approach would be suspect based on the results of this experiment.Mention of company names or commercial products does not imply recommendation or endorsement by the United States Department of Agriculture over others not mentioned.     

Sex discriminatory effectiveness using combinations of root lengths and crown diameters

Using optical-scanner (OPTOCOM) and radiogrammetric measurements on mandibular permanent teeth, root length alone affords sex-discriminatory effectiveness equal to or exceeding conventional crown diameters. Combinations of root lengths and crown dimensions yield up to 80% accuracy in sexing with as few as two teeth, and discriminatory effectiveness of 87% with mandibular teeth alone.     

Parameterization of mechanistic models from qualitative data using an efficient optimal scaling approach

Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. These models usually comprise unknown parameters, which have to be inferred from experimental data. For quantitative experimental data, there are several methods and software tools available. However, for qualitative data the available approaches are limited and computationally demanding. Here, we consider the optimal scaling method which has been developed in statistics for categorical data and has been applied to dynamical systems. This approach turns qualitative variables into quantitative ones, accounting for constraints on their relation. We derive a reduced formulation for the optimization problem defining the optimal scaling. The reduced formulation possesses the same optimal points as the established formulation but requires less degrees of freedom. Parameter estimation for dynamical models of cellular pathways revealed that the reduced formulation improves the robustness and convergence of optimizers. This resulted in substantially reduced computation times. We implemented the proposed approach in the open-source Python Parameter EStimation TOolbox (pyPESTO) to facilitate reuse and extension. The proposed approach enables efficient parameterization of quantitative dynamical models using qualitative data.

     

Effect of correcting outcome data for case mix: an example from stroke medicine.

OBJECTIVE--To show the influence of variations in case mix on clinical outcome indicators for patients admitted to hospital with acute stroke. DESIGN--"Before and after" cohort study, with prospective, consecutive identification of patients and prospective follow up; multiple logistic regression analyses to correct for case mix variations. SETTING--University teaching hospital. SUBJECTS--216 patients with stroke identified before the introduction of an organised stroke service, and 252 patients with stroke identified after its introduction. MAIN OUTCOME MEASURES--Case fatality at 30 days and 12 months; for survivors at 12 months, proportions of patients who were independent (according to the Oxford handicap scale) and of those living at home. RESULTS--Crude outcome data suggested that patients in the cohort identified after the introduction of the stroke service were significantly more likely to be alive, independent, and living at home than patients managed before the stroke service. After adjustment for age and sex these "improvements" were less impressive but still significant. After adjustment for many other possible prognostic indicators, however, the differences between the two groups for all four outcomes were non-significant, suggesting that the "improvements" may have been entirely due to differences in case mix between the two cohorts, rather than the new stroke service. CONCLUSIONS--Variations in case mix have a crucial influence on the interpretation of outcome data, and this is particularly important in non-randomised comparative studies. Such studies, comparing performance within and between different provider units, are likely to become increasingly common in the new reformed NHS. To allow meaningful interpretation, these studies must try to correct for case mix.     

Evaluating minirhizotron estimates of fine root longevity and production in the forest floor of a temperate broadleaf forest

The minirhizotron technique (MR) for in situ measurement of fine root dynamics offers the opportunity to obtain accurate and unbiased estimates of root production in perennial vegetation only if MR tubes do not affect the longevity of fine roots. Assuming fine root biomass is near steady-state, fine root production (g m^–2 yr^–1) can be estimated as the ratio of fine root biomass (g m^–2) to median fine root longevity (yr). This study evaluates the critical question of whether MR access tubes affect the longevity of fine roots, by comparing fine root survivorship obtained using MR with those from a non-intrusive in situ screen method in the forest floor horizons of a northern hardwood forest in New Hampshire, USA. Fine root survivorship was measured in 380 root screens during 1993–1997 and in six horizontal minirhizotron tubes during 1996–1997. No statistically significant difference was found between estimates of survivorship of fine roots (<1 mm dia.) at this site from MR versus from in situ screens, suggesting that MR tubes do not substantially affect fine root longevity in the forest floor of this northern hardwood forest and providing greater confidence in measurements of fine root production using the MR technique. Furthermore, the methodology for estimating fine root production from MR longevity data was evaluated by comparison of fine root longevity and production estimates made using single vs. multiple root cohorts, and using root-number, root-length, and root-mass weighted methods. Our results indicate that fine root-length longevity estimates based on multiple root cohorts throughout the year can be used to approximate fine root biomass production. Using this method, we estimated fine root longevity and production in the forest floor at this site to be 314 days (or 0.86 yr) and 303 g m^–2 yr^–1, respectively. Fine root production in this northern hardwood forest is approximately equivalent to standing biomass and was previously underestimated by root in-growth cores. We conclude that the use of MR to estimate fine root longevity and production as outlined here may result in improved estimates of fine root production in perennial vegetation.     

Effects of root diameter,branch order,root depth,season and warming on root longevity in an alpine meadow

Fine root is of importance in biogeochemical cycles especially in terrestrial ecosystems. The lack of understanding of the factors controlling root lifespan has made accurate prediction of carbon flow and nutrient cycling difficult. A controlled warming experiment was performed in an alpine meadow on the northern Tibetan Plateau (near Nagchu Town). We used a minirhizotron technique to measure root dynamics in situ during the growing season of 2013 and 2014 and survival analyses to assess root lifespan and the effects of root diameter, branch order, birth season, root depth and warming on root lifespan. Root diameter, branch order and root depth were all positively correlated with root lifespan. With an increase in diameter of 0.1 mm, mortality hazard ratio of roots declined by 19.3 %. An increase in one level in branch order was associated with a decrease of 43.8 % in root death ratio. Compared with roots born in May–mid-July, the mortality hazard ratio of roots born in late July–August and September–October reduced by 26.8 and 56.5 %, respectively. In warming treatments, roots tended to be thinner, less branched and deeper, and there was a higher proportion of roots born in spring compared to ambient conditions. Warming shortened the median root lifespan 44 days. However, in single warming condition, root diameter had no significant influence on root lifespan. Root diameter, branch order, root depth and season of birth were all factors affecting root lifespan in the alpine meadow; however, root branch order was dominant.     

A comparison between minirhizotron and monolith sampling methods for measuring root growth of maize (Zea mays L.)

Transparent plastic minirhizotron tubes have been used to evaluate spatial and temporal growth activities of plant root systems. Root number was estimated from video recordings of roots intersecting minirhizotron tubes and of washed roots extracted from monoliths of the same soil profiles at the physiological maturity stage of a maize (Zea mays L.) crop. Root length was measured by the line intercept (LI) and computer image processing (CIP) methods from the monolith samples.There was a slight significant correlation (r=0.28, p<0.005) between the number of roots measured by minirhizotron and root lengths measured by the LI method, however, no correlation was found with the CIP method. Using a single regression line, root number was underestimated by the minirhizotron method at depths between 0–7.6 cm. A correlation was found between root length estimated by LI and CIP. The slope of estimated RLD was significant with depth for these two methods. Root length density (RLD) measured by CIP showed a more erratic decline with distance from the plant row and soil surface than the LI method.     

Improving the efficiency of multidimensional scaling in the analysis of high-dimensional data using singular value decomposition

MOTIVATION: Multidimensional scaling (MDS) is a well-known multivariate statistical analysis method used for dimensionality reduction and visualization of similarities and dissimilarities in multidimensional data. The advantage of MDS with respect to singular value decomposition (SVD) based methods such as principal component analysis is its superior fidelity in representing the distance between different instances specially for high-dimensional geometric objects. Here, we investigate the importance of the choice of initial conditions for MDS, and show that SVD is the best choice to initiate MDS. Furthermore, we demonstrate that the use of the first principal components of SVD to initiate the MDS algorithm is more efficient than an iteration through all the principal components. Adding stochasticity to the molecular dynamics simulations typically used for MDS of large datasets, contrary to previous suggestions, likewise does not increase accuracy. Finally, we introduce a k nearest neighbor method to analyze the local structure of the geometric objects and use it to control the quality of the dimensionality reduction. RESULTS: We demonstrate here the, to our knowledge, most efficient and accurate initialization strategy for MDS algorithms, reducing considerably computational load. SVD-based initialization renders MDS methodology much more useful in the analysis of high-dimensional data such as functional genomics datasets.     

Endocranial volumes of primate species: scaling analyses using a comprehensive and reliable data set

We present a compilation of endocranial volumes (ECV) for 176 non-human primate species based on individual data collected from 3813 museum specimens, at least 88% being wild-caught. In combination with body mass data from wild individuals, strong correlations between endocranial volume and body mass within taxonomic groups were found. Errors attributable to different techniques for measuring cranial capacity were negligible and unbiased. The overall slopes for regressions of log ECV on log body mass in primates are 0.773 for least-squares regression and 0.793 for reduced major axis regression. The least-squares slope is reduced to 0.565 when independent contrasts are substituted for species means (branch lengths from molecular studies). A common slope of 0.646 is obtained with logged species means when grade shifts between major groups are taken into account using ANCOVA. In addition to providing a comprehensive and reliable database for comparative analyses of primate brain size, we show that the scaling relationship between brain mass and ECV does not differ significantly from isometry in primates. We also demonstrate that ECV does not differ substantially between captive and wild samples of the same species. ECV may be a more reliable indicator of brain size than brain mass, because considerably larger samples can be collected to better represent the full range of intraspecific variation. We also provide support for the maternal energy hypothesis by showing that basal metabolic rate (BMR) and gestation period are both positively correlated with brain size in primates, after controlling for the influence of body mass and potential effects of phylogenetic relatedness.     

The scaling and selection of sexually dimorphic characters: an example using the Marbled Teal

Current theory and empirical evidence suggests that, if a character is sexually dimorphic as a result of sexual selection, it should be positively allometric (i.e. relatively larger in larger individuals), whereas if the dimorphism is the result of natural selection (e.g. niche divergence), it should be isometric. I show how this can be used to study the selective forces responsible for dimorphic morphological characters, using the monochromatic Marbled Teal Marmaronetta angustirostris as an example. In absolute terms, first-year male teals have a higher body mass, wing length, head length and bill length than females. In relative terms (controlling for body size), males still have longer wings, heads and bills. The scaling in Marbled Teal suggests that bill and head dimorphisms are due to sexual selection, whereas wing dimorphism is due to natural selection. Tail length is sexually monomorphic but positively allometric, possibly because of a display function. Such scaling studies are easy to carry out, and provide a useful complement to direct investigation of the influence of variation in the size of dimorphic characters on mating success, foraging efficiency etc.     

Inter-specific scaling of phytoplankton production and cell size in the field

This study tests the hypothesis that the interspecific scalingof phytoplankton production and cell size in the field followsthe -power scaling law. Published data of cell size and in situ,cell-specific carbon production rates by single phytoplanktonspecies, collected in surface waters of lakes, rivers, estuariesand oceans, are reviewed. Across more than nine orders of magnitudein cell volume, 98% of the variability in carbon productionrates was explained by cell size. The slope (b) in the log–logrelationship between carbon production rate and cell volumedid not differ significantly from 1, either for diatoms (b =1.01) or for dinoflagellates (b = 0.89). For all phytoplanktonspecies considered together, which included also cyanobacteriaand haptophytes, b took a value of 0.91, which is significantlyhigher than . The observed nearly isometric scaling relationshipsbetween production rate and cell volume suggest that there isno relationship between phytoplankton growth rate and cell size.The present analysis confirms recent evidence showing that phytoplanktonmetabolism in natural conditions does not follow the -powerscaling rule. It is argued that allometric models of planktongrowth and metabolism should incorporate scaling parametersmeasured in situ on natural phytoplankton assemblages, ratherthan those obtained in the laboratory with monospecific cultures.     

Assessing the efficiency of clustering algorithms and goodness-of-fit measures using phytoplankton field data

Investigation of patterns in beta diversity has received increased attention over the last years particularly in light of new ecological theories such as the metapopulation paradigm and metacommunity theory. Traditionally, beta diversity patterns can be described by cluster analysis (i.e. dendrograms) that enables the classification of samples. Clustering algorithms define the structure of dendrograms, consequently assessing their performance is crucial. A common, although not always appropriate approach for assessing algorithm suitability is the cophenetic correlation coefficient c. Alternatively the 2-norm has been recently proposed as an increasingly informative method for evaluating the distortion engendered by clustering algorithms. In the present work, the 2-norm is applied for the first time on field data and is compared with the cophenetic correlation coefficient using a set of 105 pairwise combinations of 7 clustering methods (e.g. UPGMA) and 15 (dis)similarity/distance indices (e.g. Jaccard index). In contrast to the 2-norm, cophenetic correlation coefficient does not provide a clear indication on the efficiency of the clustering algorithms for all combinations. The two approaches were not always in agreement in the choice of the most faithful algorithm. Additionally, the 2-norm revealed that UPGMA is the most efficient clustering algorithm and Ward's the least. The present results suggest that goodness-of-fit measures such as the 2-norm should be applied prior to clustering analyses for reliable beta diversity measures.     

Significance of temperature and precipitation for maize root distribution in the field

Measurements of maize (Zea mays L.) root distribution with depth in the soil for nine years in a 11-year period revealed significantly different distribution patterns. Weather variations were expected to be related to the amount of roots found in each of the five 15-cm soil layers. The objective of this study was to attempt to explain root distribution in the field on the basis of precipitation and temperature data for the nine growing seasons. Growing degree days (GDD), accumulated in daily increments from planting to silking, were used to describe temperature effects. Correlations were calculated for weekly time increments of GDD versus root length densities at silking in all soil layers. Root length density below 30 cm was correlated (P=0.05) with GDD for two weeks following planting, whereas no relation was found between GDD and root length density in the topsoil. Amount of precipitation was accumulated in weekly increments from silking to planting and correlated with root length density in the soil layers at silking. This procedure evaluated the relation between precipitation and root growth during the vegetative growth period. Root length density in the 0 to 15 cm layer was found to be related significantly (P=0.05) to precipitation. The period 3 weeks prior silking gave the highest correlation coefficient (r=0.79). Journal Paper no. 10,629. Purdue Univ. Agric. Exp. Stn., W. Lafayette, IN 47907. Contribution from the Dep. of Agronomy. The research was supported in part by BARD, United States-Israel Binational Agricultural Research and Development Fund, and Deutsche Forschungsgemeinschaft.