Integration of local and regional species-area relationships from space-time species accumulation

A long-standing observation in community ecology is that the scaling of species richness, as exemplified by species-area curves, differs on local and regional scales. This decoupling of scales may be largely due to sampling processes (the increasing constraint imposed by sampling fewer individuals at fine scales), as distinct from ecological processes, such as environmental heterogeneity, that operate across scales. Removal of the sampling constraint from fine-scale richness estimates should yield species-area curves that behave like those of the regions in which they are embedded, but an effective method for this removal has not been available. We suggest an approach that incorporates the manner in which small areas accumulate species over time as a way to remove the signature of sampling processes from fine-scale species-area curves. We report for three species-rich grasslands from two continents how local plant species richness is distributed through time at multiple, nested spatial scales, and we ask whether sampling-corrected curves reflect the spatial scaling of richness of each larger floristic province. Our analysis suggests that fine-scale values of richness are highly constrained by sampling processes, but once these constraints are removed, the spatial scaling of species richness is consistent from the scale of individuals to that of an entire province.     

Sampling in ecology and evolution – bridging the gap between theory and practice

Sampling is a key issue for answering most ecological and evolutionary questions. The importance of developing a rigorous sampling design tailored to specific questions has already been discussed in the ecological and sampling literature and has provided useful tools and recommendations to sample and analyse ecological data. However, sampling issues are often difficult to overcome in ecological studies due to apparent inconsistencies between theory and practice, often leading to the implementation of simplified sampling designs that suffer from unknown biases. Moreover, we believe that classical sampling principles which are based on estimation of means and variances are insufficient to fully address many ecological questions that rely on estimating relationships between a response and a set of predictor variables over time and space. Our objective is thus to highlight the importance of selecting an appropriate sampling space and an appropriate sampling design. We also emphasize the importance of using prior knowledge of the study system to estimate models or complex parameters and thus better understand ecological patterns and processes generating these patterns. Using a semi‐virtual simulation study as an illustration we reveal how the selection of the space (e.g. geographic, climatic), in which the sampling is designed, influences the patterns that can be ultimately detected. We also demonstrate the inefficiency of common sampling designs to reveal response curves between ecological variables and climatic gradients. Further, we show that response‐surface methodology, which has rarely been used in ecology, is much more efficient than more traditional methods. Finally, we discuss the use of prior knowledge, simulation studies and model‐based designs in defining appropriate sampling designs. We conclude by a call for development of methods to unbiasedly estimate nonlinear ecologically relevant parameters, in order to make inferences while fulfilling requirements of both sampling theory and field work logistics.     

Estimating species – area relationships by modeling abundance and frequency subject to incomplete sampling

Models and data used to describe species–area relationships confound sampling with ecological process as they fail to acknowledge that estimates of species richness arise due to sampling. This compromises our ability to make ecological inferences from and about species–area relationships. We develop and illustrate hierarchical community models of abundance and frequency to estimate species richness. The models we propose separate sampling from ecological processes by explicitly accounting for the fact that sampled patches are seldom completely covered by sampling plots and that individuals present in the sampling plots are imperfectly detected. We propose a multispecies abundance model in which community assembly is treated as the summation of an ensemble of species‐level Poisson processes and estimate patch‐level species richness as a derived parameter. We use sampling process models appropriate for specific survey methods. We propose a multispecies frequency model that treats the number of plots in which a species occurs as a binomial process. We illustrate these models using data collected in surveys of early‐successional bird species and plants in young forest plantation patches. Results indicate that only mature forest plant species deviated from the constant density hypothesis, but the null model suggested that the deviations were too small to alter the form of species–area relationships. Nevertheless, results from simulations clearly show that the aggregate pattern of individual species density–area relationships and occurrence probability–area relationships can alter the form of species–area relationships. The plant community model estimated that only half of the species present in the regional species pool were encountered during the survey. The modeling framework we propose explicitly accounts for sampling processes so that ecological processes can be examined free of sampling artefacts. Our modeling approach is extensible and could be applied to a variety of study designs and allows the inclusion of additional environmental covariates.     

Future trends in nitrogen research

N research effort has undergone major changes over recent decades with changing emphasis because of environmental problems and issues. This driving force, coupled with a universal desire to improve N-use efficiency, appreciation of the importance of maintaining soil resource quality and a need to provide integrated landscape managements, will continue to prompt new research areas and issues for study. Already, much information has been provided and new approaches and needs defined. It will be essential in future research to take full note of the many interactions that occur and to provide a mechanistic basis so that scaling of effects can be undertaken with the appropriate simplification without being superficial. Examples of interactions, as well as fundamental gaps in the basic processes are discussed and needs for future research identified.     

Transport of bacteria in porous media: II. A model for convective Transport and growth

A model is presented for the coupled processes of bacterial growth and convective transport of bacteria has been modeled using a fractional flow approach. The various mechanisms of bacteria retention can be incorporated into the model through selection of an appropriate shape of the fractional flow curve. Permeability reduction due to pore plugging by bacteria was simulated using the effective medium theory. In porous media, the rates of transport and growth of bacteria, the generation of metabolic products, and the consumption of nutrients are strongly coupled processes. Consequently, the set of governing conservation equations form a set of coupled, nonlinear partial differential equations that were solved numerically. Reasonably good agreement between the model and experimental data has been obtained indicating that the physical processes incorporated in the model are adequate. The model has been used to predict the in situ transport and growth of bacteria, nutrient consumption, and metabolite production. It can be particularly useful in simulating laboratory experiments and in scaling microbial-enhanced oil recovery or bioremediation processes to the field. (c) 1994 John Wiley & Sons, Inc.     

Fish distribution predictions from different points of view: comparing associative neural networks,geostatistics and regression models

Accurate prediction of species distributions based on sampling and environmental data is essential for further scientific analysis, such as stock assessment, detection of abundance fluctuation due to climate change or overexploitation, and to underpin management and legislation processes. The evolution of computer science and statistics has allowed the development of sophisticated and well-established modelling techniques as well as a variety of promising innovative approaches for modelling species distribution. The appropriate selection of modelling approach is crucial to the quality of predictions about species distribution. In this study, modelling techniques based on different approaches are compared and evaluated in relation to their predictive performance, utilizing fish density acoustic data. Generalized additive models and mixed models amongst the regression models, associative neural networks (ANNs) and artificial neural networks ensemble amongst the artificial neural networks and ordinary kriging amongst the geostatistical techniques are applied and evaluated. A verification dataset is used for estimating the predictive performance of these models. A combination of outputs from the different models is applied for prediction optimization to exploit the ability of each model to explain certain aspects of variation in species acoustic density. Neural networks and especially ANNs appear to provide more accurate results in fitting the training dataset while generalized additive models appear more flexible in predicting the verification dataset. The efficiency of each technique in relation to certain sampling and output strategies is also discussed.     

Spatial pattern of diversity in a tropical rain forest in Malaysia

The diversity of trees (species richness, abundance and Shannon diversity) in a tropical rain forest of Malaysia has been studied from the point of view of its spatial organization in order to formulate hypotheses about the origin of the observed spatial patterns. The question that motivated this study is whether tropical forests communities are in a state of equilibrium or non-equilibrium. Three aspects have been examined: (1) changes in diversity were studied with respect to sampling area and sampling designs. A minimum area of 5–10 ha is recommended by the species–area curves, while 2–5 ha seem appropriate based on the Shannon diversity–area curves. Different sampling designs significantly affect the species–area curves. The power function, which can be derived under the equilibrium assumption, is not appropriate to fit the observed diversity–area curves. (2) The spatial features of diversity variables were then studied. Variograms showed that there are dominant short-range effects (around 150 m), obvious anisotropic distribution, and high random variation in the diversity data. (3) Partitioning the variation of the diversity measures into environmental (topographic) and spatial components indicated that the spatial organisation of that community was mostly unpredictable. There may be many processes controlling the formation of the spatial patterns in the tropical rain forest. Unidentified causes, affecting mainly the small-scale processes (<20 m), seem responsible for the large amount of undetermined variation in the diversity data sets. The study suggests that the Pasoh forest of Malaysia may not be in a state of equilibrium.     

Correlation of space-time ranges in ecological hierarchies of various nature

Relations between characteristic scales of time and space are analyzed for the hierarchical systems of a various nature. The available data fit well to the power relation: [T] = a[L]b, where [T] and [L] are characteristic ranges of time and space, b--scaling exponent, a--conversion coefficient. The spatio-temporal scales of ocean physical and biological (pelagic) processes are closely overlapped. Contrastingly, the scale for terrestrial and benthic ecosystems and their environments differ noticeably. For terrestrial and benthic ecological systems, and also for atmospheric phenomena, the b values significantly less than 1, that indicates a significant coherence of structure-generating processes integrating lower-level hierarchical units to a higher-level entity. For geomorphological structures, both terrestrial and oceanic, the scaling parameters has appeared close to 1 (a "direct transfer" type of generating processes). For plankton systems, which are related with water masses, the b values vary from 1 (processes of direct transfer) up to 2 (random dispersal or diffusion processes). The author attributes this difference to the principle distinctions in dynamic properties of the physical environments for terrestrial (and probably, benthic) and plankton organisms. Finally, for the units (structures or processes) of one and the same organization level, scaling exponents are significantly higher and close to 2 (diffusive dynamics) or more (rigid spatial limitation). Thus, the development of many ecological structures looks dynamically like diffusion or gradual growth, but their putting in the higher-level order (integrity) is a qualitative leap forward and demands appropriate cooperative organizational processes.     

Low-cost image processing system for analyzing molecular RNA fingerprints.

A complete image digitizing and processing system is described for capturing, enhancing and analyzing molecular fingerprints. The low-cost, high-resolution system features a Motorola 68000 processor, multi-tasking, a separate video coprocessor, and color or gray scale processing. Thousands of manipulations are possible using functions which include histographic equalization, edge detection, filtering, overlays, false coloring, zoom, pan and print. All operations are initiated and controlled with a mouse. Techniques for enhancing, scaling and comparing molecular fingerprints are described. The techniques all involve using a graphical interface to select and manipulate the various processes. The system has been used successfully for about 1.5 years, and it has been ideal for our application which requires human judgment at many steps between processing and which probably would not lend itself to a completely automated analysis. Similar techniques could probably be used with this system on many other applications.     

Life‐cycle and cost of goods assessment of fed‐batch and perfusion‐based manufacturing processes for mAbs

Life‐cycle assessment (LCA) is an environmental assessment tool that quantifies the environmental impact associated with a product or a process (e.g., water consumption, energy requirements, and solid waste generation). While LCA is a standard approach in many commercial industries, its application has not been exploited widely in the bioprocessing sector. To contribute toward the design of more cost‐efficient, robust and environmentally‐friendly manufacturing process for monoclonal antibodies (mAbs), a framework consisting of an LCA and economic analysis combined with a sensitivity analysis of manufacturing process parameters and a production scale‐up study is presented. The efficiency of the framework is demonstrated using a comparative study of the two most commonly used upstream configurations for mAb manufacture, namely fed‐batch (FB) and perfusion‐based processes. Results obtained by the framework are presented using a range of visualization tools, and indicate that a standard perfusion process (with a pooling duration of 4 days) has similar cost of goods than a FB process but a larger environmental footprint because it consumed 35% more water, demanded 17% more energy, and emitted 17% more CO₂ than the FB process. Water consumption was the most important impact category, especially when scaling‐up the processes, as energy was required to produce process water and water‐for‐injection, while CO₂ was emitted from energy generation. The sensitivity analysis revealed that the perfusion process can be made more environmentally‐friendly than the FB process if the pooling duration is extended to 8 days. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1324–1335, 2016     

Early tetrapodomorph biogeography: Controlling for fossil record bias in macroevolutionary analyses

The fossil record provides direct empirical data for understanding macroevolutionary patterns and processes. Inherent biases in the fossil record are well known to confound analyses of this data. Sampling bias proxies have been used as covariates in regression models to test for such biases. Proxies, such as formation count, are associated with paleobiodiversity, but are insufficient for explaining species dispersal owing to a lack of geographic context. Here, we develop a sampling bias proxy that incorporates geographic information and test it with a case study on early tetrapodomorph biogeography. We use recently-developed Bayesian phylogeographic models and a new supertree of early tetrapodomorphs to estimate dispersal rates and ancestral habitat locations. We find strong evidence that geographic sampling bias explains supposed radiations in dispersal rate (potential adaptive radiations). Our study highlights the necessity of accounting for geographic sampling bias in macroevolutionary and phylogenetic analyses and provides an approach to test for its effect.     

A Scaling Rule for Landscape Patches and How It Applies to Conserving Soil Resources in Savannas

Scaling issues are complex, yet understanding issues such as scale dependencies in ecological patterns and processes is usually critical if we are to make sense of ecological data and if we want to predict how land management options, for example, are constrained by scale. In this article, we develop the beginnings of a way to approach the complexity of scaling issues. Our approach is rooted in scaling functions, which integrate the scale dependency of patterns and processes in landscapes with the ways that organisms scale their responses to these patterns and processes. We propose that such functions may have sufficient generality that we can develop scaling rules—statements that link scale with consequences for certain phenomena in certain systems. As an example, we propose that in savanna ecosystems, there is a consistent relationship between the size of vegetation patches in the landscape and the degree to which critical resources, such as soil nutrients or water, become concentrated in these patches. In this case, the features of the scaling functions that underlie this rule have to do with physical processes, such as surface water flow and material redistribution, and the ways that patches of plants physically “capture” such runoff and convert it into plant biomass, thereby concentrating resources and increasing patch size. To be operationally useful, such scaling rules must be expressed in ways that can generate predictions. We developed a scaling equation that can be used to evaluate the potential impacts of different disturbances on vegetation patches and on how soils and their nutrients are conserved within Australian savanna landscapes. We illustrate that for a 10-km² paddock, given an equivalent area of impact, the thinning of large tree islands potentially can cause a far greater loss of soil nitrogen (21 metric tons) than grazing out small grass clumps (2 metric tons). Although our example is hypothetical, we believe that addressing scaling problems by first conceptualizing scaling functions, then proposing scaling rules, and then deriving scaling equations is a useful approach. Scaling equations can be used in simulation models, or (as we have done) in simple hypothetical scenarios, to collapse the complexity of scaling issues into a manageable framework. Received 8 December 1998; accepted 17 August 1999.     

Method for Collecting Air-Water Interface Microbes Suitable for Subsequent Microscopy and Molecular Analysis in both Research and Teaching Laboratories

A method has been developed for collecting air-water interface (AWI) microbes and biofilms that enables analysis of the same sample with various combinations of bright-field and fluorescence light microscopy optics, scanning and transmission electron microscopy (TEM), and atomic force microscopy. The identical sample is then subjected to molecular analysis. The sampling tool consists of a microscope slide supporting appropriate substrates, TEM grids, for example, that are removable for the desired protocols. The slide with its substrates is then coated with a collodion polymer membrane to which in situ AWI organisms adhere upon contact. This sampling device effectively separates the captured AWI bacterial community from the bulk water community immediately subtending. Preliminary data indicate that the AWI community differs significantly from the water column community from the same sample site when both are evaluated with microscopy and with 16S ribosomal DNA sequence-based culture-independent comparisons. This microbe collection method can be used at many levels in research and teaching.     

Error propagation methods for LCA—a comparison

Purpose

The analysis of uncertainty in life cycle assessment (LCA) studies has been a topic for more than 10 years, and many commercial LCA programs now feature a sampling approach called Monte Carlo analysis. Yet, a full Monte Carlo analysis of a large LCA system, for instance containing the 4,000 unit processes of ecoinvent v2.2, is rarely carried out by LCA practitioners. One reason for this is computation time. An alternative faster than Monte Carlo method is analytical error propagation by means of a Taylor series expansion; however, this approach suffers from being explained in the literature in conflicting ways, hampering implementation in most software packages for LCA. The purpose of this paper is to compare the two different approaches from a theoretical and practical perspective.

Methods

In this paper, we compare the analytical and sampling approaches in terms of their theoretical background and their mathematical formulation. Using three case studies—one stylized, one real-sized, and one input–output (IO)-based—we approach these techniques from a practical perspective and compare them in terms of speed and results.

Results

Depending on the precise question, a sampling or an analytical approach provides more useful information. Whenever they provide the same indicators, an analytical approach is much faster but less reliable when the uncertainties are large.

Conclusions

For a good analysis, analytical and sampling approaches are equally important, and we recommend practitioners to use both whenever available, and we recommend software suppliers to implement both.     

Method for collecting air-water interface microbes suitable for subsequent microscopy and molecular analysis in both research and teaching laboratories

A method has been developed for collecting air-water interface (AWI) microbes and biofilms that enables analysis of the same sample with various combinations of bright-field and fluorescence light microscopy optics, scanning and transmission electron microscopy (TEM), and atomic force microscopy. The identical sample is then subjected to molecular analysis. The sampling tool consists of a microscope slide supporting appropriate substrates, TEM grids, for example, that are removable for the desired protocols. The slide with its substrates is then coated with a collodion polymer membrane to which in situ AWI organisms adhere upon contact. This sampling device effectively separates the captured AWI bacterial community from the bulk water community immediately subtending. Preliminary data indicate that the AWI community differs significantly from the water column community from the same sample site when both are evaluated with microscopy and with 16S ribosomal DNA sequence-based culture-independent comparisons. This microbe collection method can be used at many levels in research and teaching.     

Novel approaches to the calculation and comparison of thermoregulatory parameters: Non-linear regression of metabolic rate and evaporative water loss in Australian rodents

The calculation and comparison of physiological characteristics of thermoregulation has provided insight into patterns of ecology and evolution for over half a century. Thermoregulation has typically been explored using linear techniques; I explore the application of non-linear scaling to more accurately calculate and compare characteristics and thresholds of thermoregulation, including the basal metabolic rate (BMR), peak metabolic rate (PMR) and the lower (T_lc) and upper (T_uc) critical limits to the thermo-neutral zone (TNZ) for Australian rodents. An exponentially-modified logistic function accurately characterised the response of metabolic rate to ambient temperature, while evaporative water loss was accurately characterised by a Michaelis-Menten function. When these functions were used to resolve unique parameters for the nine species studied here, the estimates of BMR and TNZ were consistent with the previously published estimates. The approach resolved differences in rates of metabolism and water loss between subfamilies of Australian rodents that haven’t been quantified before. I suggest that non-linear scaling is not only more effective than the established segmented linear techniques, but also is more objective. This approach may allow broader and more flexible comparison of characteristics of thermoregulation, but it needs testing with a broader array of taxa than those used here.     

Applying non-metric multidimensional scaling analysis for measuring the assemblage change of Chu-Lan Creek dike in Taiwan

Ensuring that water resources development in harmony with aquatic environment is the major water policy of Taiwan in the 21st century, Taiwan's water authority has adopted several methodologies, such as utilizing ecological engineering techniques, establishing integrated water resources management configuration, involving the public in decision-making processes, etc., and applying them in the field. Significant consequences in ecological engineering were obtained in several cases, such as for Ta-Chia Creek, where wire cages, tires, and boulders were installed to improve the stream habitat, and for Wu-Lao Creek, where natural water purification facilities were constructed to reduce river pollution. Although the sustainable methodologies have been widely accepted by hydraulic engineers in Taiwan, lack of engineer-friendly evaluation indices or methods hindered the further progress of river ecological engineering projects. This research applied a non-metric multidimensional–scaling (MDS) analysis to measure the assemblage change of river aquatic habitat. A dike construction project at Chu-Lan Creek was selected for verification in this study. The analyzed results showed that the dike construction project did affect the aquatic habitat in Chu-Lan Creek. The proposed MDS analysis successfully captured the effect of the construction. The MDS method could be used to evaluate the improvement or damage of aquatic habitat by a traditional hydraulic approach or a new ecological hydraulic developed technique in Taiwan.     

Inferential biases linked to unobservable states in complex occupancy models

Modeling of species distributions has undergone a shift from relying on equilibrium assumptions to recognizing transient system dynamics explicitly. This shift has necessitated more complex modeling techniques, but the performance of these dynamic models has not yet been assessed for systems where unobservable states exist. Our work is motivated by the impacts of the emerging infectious disease chytridiomycosis, a disease of amphibians that is associated with declines of many species worldwide. Using this host‐pathogen system as a general example, we first illustrate how misleading inferences can result from failing to incorporate pathogen dynamics into the modeling process, especially when the pathogen is difficult or impossible to survey in the absence of a host species. We found that traditional modeling techniques can underestimate the effect of a pathogen on host species occurrence and dynamics when the pathogen can only be detected in the host, and pathogen information is treated as a covariate. We propose a dynamic multistate modeling approach that is flexible enough to account for the detection structures that may be present in complex multistate systems, especially when the sampling design is limited by a species’ natural history or sampling technology. When multistate occupancy models are used and an unobservable state is present, parameter estimation can be influenced by model complexity, data sparseness, and the underlying dynamics of the system. We show that, even with large sample sizes, many models incorporating seasonal variation in vital rates may not generate reasonable estimates, indicating parameter redundancy. We found that certain types of missing data can greatly hinder inference, and we make study design recommendations to avoid these issues. Additionally, we advocate the use of time‐varying covariates to explain temporal trends in the data, and the development of sampling techniques that match the biology of the system to eliminate unobservable states when possible.     

Use of randomized sampling for analysis of metabolic networks

Genome-scale metabolic network reconstructions in microorganisms have been formulated and studied for about 8 years. The constraint-based approach has shown great promise in analyzing the systemic properties of these network reconstructions. Notably, constraint-based models have been used successfully to predict the phenotypic effects of knock-outs and for metabolic engineering. The inherent uncertainty in both parameters and variables of large-scale models is significant and is well suited to study by Monte Carlo sampling of the solution space. These techniques have been applied extensively to the reaction rate (flux) space of networks, with more recent work focusing on dynamic/kinetic properties. Monte Carlo sampling as an analysis tool has many advantages, including the ability to work with missing data, the ability to apply post-processing techniques, and the ability to quantify uncertainty and to optimize experiments to reduce uncertainty. We present an overview of this emerging area of research in systems biology.     

Temporal scale, phytoplankton ecology and palaeolimnology

1. Scales of temporal analysis in limnology generally cover dial through to interannual changes, with occasional longer studies with up to 50 years continuous sampling data. Lakes, however, have been changing over much longer time periods than this, as is apparent from palaeolimnological studies. Temporal scales are, however, largely relative, with an individual's perspective controlling what is deemed short or long term. 2. Phytoplankton populations are variable over a variety of timescales, and the sediment record can readily record these changes from interannual through to 10³-year timescales. Because of anthropogenic influences, such as acidification and eutrophication, phytoplankton communities probably have been altered dramatically in many lakes, often before routine sampling began. Records of changing phytoplankton populations at timescales relevant to limnologists can be derived from, for example, varved sediments and used to address specific problems, such as the degree of long-term interannual variability and timescales of sexual reproduction. 3. Palaeolimnologists tend to interpret changes in sediment assemblages in terms of ecological and physiological processes which are relevant at scales that may not be resolvable in lake sediments. There is a clear need for sediment records to be interpreted in terms of the processes which operate at timescales that match the resolution of that sediment sequence. 4. Increasingly fine sampling resolutions are being attempted by palaeolimnologists, often without consideration of the reasons for such an approach or to the repeatability of the results. The increased variability associated with high-resolution sampling can make it difficult to separate noise from the ecological signal. There is a clear need for replication. 5. The necessary temporal resolution is defined by the aim of any given palaeolimnological study. If the main emphasis of a study is, for example, establishing background phosphorus concentrations, a coarser sampling resolution is probably acceptable than that required for many ‘ecological’studies.