Ecological Quantity Research Articles

Analytical Solutions of Microplastic Particles Dispersion Using a Lotka–Volterra Predator–Prey Model with Time-Varying Intraspecies Coefficients

Discarded plastic is subjected to weather effects from different ecosystems and becomes microplastic particles. Due to their small size, they have spread across the planet. Their presence in living organisms can have several harmful consequences, such as altering the interaction between prey and predator. Huang et al. successfully modeled this system presenting numerical results of ecological relevance. Here, we have rewritten their equations and solved a set of them analytically, confirming that microplastic particles accumulate faster in predators than in prey and calculating the time values from which it happens. Using these analytical solutions, we have retrieved the Lotka–Volterra predator–prey model with time-varying intraspecific coefficients, allowing us to interpret ecological quantities referring to microplastics dispersion. After validating our equations, we solved analytically particular situations of ecological interest, characterized by extreme effects on predatory performance, and proposed a second-order differential equation as a possible next step to address this model. Our results open space for further refinement in the study of predator–prey models under the effects of microplastic particles, either exploring the second-order equation that we propose or modify the Huang et al. model to reduce the number of parameters, embedding in the time-varying intraspecies coefficients all the adverse effects caused by microplastic particles.

Multiplicative Shot-Noise: A New Route to Stability of Plastic Networks.

Fluctuations of synaptic weights, among many other physical, biological, and ecological quantities, are driven by coincident events of two "parent" processes. We propose a multiplicative shot-noise model that can capture the behaviors of a broad range of such natural phenomena, and analytically derive an approximation that accurately predicts its statistics. We apply our results to study the effects of a multiplicative synaptic plasticity rule that was recently extracted from measurements in physiological conditions. Using mean-field theory analysis and network simulations, we investigate how this rule shapes the connectivity and dynamics of recurrent spiking neural networks. The multiplicative plasticity rule is shown to support efficient learning of input stimuli, and it gives a stable, unimodal synaptic-weight distribution with a large fraction of strong synapses. The strong synapses remain stable over long times but do not "run away." Our results suggest that the multiplicative shot-noise offers a new route to understand the tradeoff between flexibility and stability in neural circuits and other dynamic networks.

A guide to state–space modeling of ecological time series

AbstractState–space models (SSMs) are an important modeling framework for analyzing ecological time series. These hierarchical models are commonly used to model population dynamics, animal movement, and capture–recapture data, and are now increasingly being used to model other ecological processes. SSMs are popular because they are flexible and they model the natural variation in ecological processes separately from observation error. Their flexibility allows ecologists to model continuous, count, binary, and categorical data with linear or nonlinear processes that evolve in discrete or continuous time. Modeling the two sources of stochasticity separately allows researchers to differentiate between biological variation and imprecision in the sampling methodology, and generally provides better estimates of the ecological quantities of interest than if only one source of stochasticity is directly modeled. Since the introduction of SSMs, a broad range of fitting procedures have been proposed. However, the variety and complexity of these procedures can limit the ability of ecologists to formulate and fit their own SSMs. We provide the knowledge for ecologists to create SSMs that are robust to common, and often hidden, estimation problems, and the model selection and validation tools that can help them assess how well their models fit their data. We present a review of SSMs that will provide a strong foundation to ecologists interested in learning about SSMs, introduce new tools to veteran SSM users, and highlight promising research directions for statisticians interested in ecological applications. The review is accompanied by an in‐depth tutorial that demonstrates how SSMs can be fitted and validated in R. Together, the review and tutorial present an introduction to SSMs that will help ecologists to formulate, fit, and validate their models.

Interactions between Air Pollution and Terrestrial Ecosystems: Perspectives on Challenges and Future Directions

AbstractInteractions between air pollution and terrestrial ecosystems play an important role in the Earth system. However, process-based knowledge of air pollution–terrestrial ecosystem interactions is limited, hindering accurate quantification of how changes in tropospheric chemistry, biogeochemical cycling, and climate affect air quality and its impact on humans and ecosystems. Here we summarize current challenges and future directions for advancing the understanding of air pollution–ecosystem interactions by synthesizing discussions from a multidisciplinary group of scientists at a recent Integrated Land Ecosystem–Atmosphere Processes Study (iLEAPS) early-career workshop. Specifically, we discuss the important elements of air pollution–terrestrial ecosystem interactions, including vegetation and soil uptake and emissions of air pollutants and precursors, in-canopy chemistry, and the roles of human activities, fires, and meteorology. We highlight the need for a coordinated network of measurements of long-term chemical fluxes and related meteorological and ecological quantities with expanded geographic and ecosystem representation, data standardization and curation to reduce uncertainty and enhance observational syntheses, integrated multiscale observational and modeling capabilities, collaboration across scientific disciplines and geographic regions, and active involvement by stakeholders and policymakers. Such an enhanced network will continue to facilitate the process-level understanding and thus predictive ability of interactions between air pollution and terrestrial ecosystems and impacts on local-to-global climate and human health.

Making quantitative predictions on the yield of a species immersed in a multispecies community: The focal species method

• Predicting the species yields of a community is central for its management. • Estimating all the required parameters to attain such goal may be unfeasible. • The focal species approximation requires only a fraction of these parameters. • Predictions are compared against experiments covering a wide variety of taxa. • Predictions using only a fraction of the set of model parameters are quite accurate. The abundance or yield of a species is an ecological quantity of paramount importance when making management and conservation decisions. The linear generalized Lotka–Volterra equations (LGLVE) constitute the simplest theoretical framework for predicting such yields. However, in many ecological communities ( e.g. tropical forests), the number of coexisting species S can be very large and estimating the entire interaction matrix A from experiments is practically unfeasible. Here, I introduce a method for predicting the yield of a particular species of interest, or focal species. The method proposed here only requires data on the interaction coefficients of the focal species k , referring to the elements of row and column k of the approximate focal interaction matrix A ( k ) . These interaction coefficients can be obtained from measuring the yields of species in monoculture ( S experimental treatments) and in biculture experiments involving the focal species ( S − 1 treatments). The remaining elements of A ( k ) are considered equal to − 1. I compare the species yields predicted by the focal species method against a data set of experimental studies I compiled from the literature across several taxa −plants, algae, protozoa and crustacean. The accuracy of this method is slightly lower than that attained when using the entire Lotka-Volterra interaction matrix. The advantage of this method is that it requires a much smaller number of experimental treatments to estimate parameters (of the order of S rather than of S 2 ). Therefore, it can be a useful quantitative tool for applied sciences like agriculture or fisheries.

Z‐scores unite pairwise indices of ecological similarity and association for binary data

AbstractPairwise ecological resemblance, which includes compositional similarity between sites (beta diversity), or associations between species (co‐occurrence), can be measured by >70 indices. Classical examples for presence–absence data are Jaccard index or C‐score. These can be expressed using contingency table matching components a, b, c, and d—the joint presences, presences at only one site/species, and joint absences. Using simulations of point patterns for two species with known magnitude of association, I demonstrate that most of the indices converge to a similar value and they describe the simulated association almost identically, as long as they are calculated as a Z‐score, that is, as deviation of the index from a null expectation. Further, I show that Z‐scores estimate resemblance on average better than raw forms of the indices, particularly in the face of confounding effects of spatial scale and conspecific aggregation. Finally, I show that any single of the matching components, when expressed as Z‐score, can be used as an index that performs as good as the classical indices; this also includes joint absences. All this simplifies selection of the right resemblance index, it underscores the advantage of expressing resemblance as deviation from a null expectation, and it revives the potential of joint absences as a meaningful ecological quantity.

Response of Landscape and Ecological Characteristics to the Optimal Rainwater Harvesting Dual-Element Mulch Covered Soil Model in Beijing

The implementation of energy conservation and emissions reduction in Beijing prompted yearly increases in the area of urban green space, leading to direct increases in urban water consumption. This aggravated an already tense situation of water shortage. Considering the low irrigation water utilization effectives of the urban green space system, the typical urban greening shrub (Ligustrum vicaryi) was selected as the research object of this study. In a pot experiment, three mulch materials were selected: gravel (CH1), pine needles + gravel (CH2), and bark + gravel (CH3). These materials were set to a uniform thickness of 3 cm, and soil water was maintained between 75% and 85% of the field capacity. Using the analytic hierarchy process and fuzzy mathematics model, the physiological and ecological response characteristics of Ligustrum vicaryi were investigated under different combinations of mulch material. The results for various processing, regarding plant growth, showed CH3 > CH2 > CH1 > CK (Control Check). The leaf area, total leaf area, and leaf area index of CH3 were, respectively, 21.4%, 21.9%, and 62.5% larger than those of the control check (CK). Regarding physiological characteristics, photosynthetic rate, evaporation rate, stomatal conductance, and water use efficiency of CH3 were better than for the other treatments. Regarding ecological services, carbon fixation, oxygen release, cooling, and quantity of humidification of CH3 were optimal. Considered comprehensively for the landscape function, physical characteristics, and ecological services of Ligustrum vicaryi, the preliminary thought is that bark and gravel dual-element mulch, with a layer thickness of 3 cm, was the optimal soil cover treatment for the typical city greening shrub Ligustrum vicaryi. Using the analytic hierarchy process (AHP) and the fuzzy mathematical model for the evaluation of the effects of different soil cover treatments on the landscape function, ecological service function, and physiological characteristics of Ligustrum vicaryi was reliable and feasible. The model evaluation results match the actual ones.

Identifying drivers of spatial variation in occupancy with limited replication camera trap data

Occupancy models are widely used in camera trap studies to analyze species presence, abundance, and geographic distribution, among other important ecological quantities. These models account for imperfect detection using a latent variable to distinguish between true presence/absence and observed detection of a species. Under certain experimental setups, parameter estimation in a latent variable framework can be challenging. Several studies have issued guidelines on the number of independent replicated observations (surveys) needed for each unchanging occupancy field (season) to ensure reliable estimation. In this paper, we present a spatio-temporal occupancy model, and show through a simulation study that it can be fit to data obtained from a single survey per season, so long as the number of seasons is sufficiently large. We include an application using camera-trap data on the Thomson's gazelle in the Serengeti in Tanzania.

An Eco-Compensation Strategy in the Water Source Area: A Case for Southern Shaanxi in China

The South-to-North Water Transfer Project (SNWTP) in China which is the world’s largest water transfer project completed in 2014 is promoted as a strategy to mitigate water stresses in the northern China by the Chinese government and engineers. However, the ecological compensation of SNWTP in China has been slow and less for the people living in the water source area which was lost their opportunities to earn money; some had even lost their farmland. A key issue for SNWTP is to establish an eco-compensation system, define the compensation scheme, and make an effective economic compensation to the people living in the water source area. In this paper, we take the water source area of the Middle-Route project of SNWTP located in Southern Shaanxi including three cities called Hanzhong, Ankang and Shangluo as the research regions. Six factors are taken into consideration: (1) ecological losses, (2) economic losses and (3) ecological bonus in our eco-compensation strategy, as well as join two dynamic factors accounting in the calculation of ecological damage, (4) water quantity and (5) water quality. Besides, the total amount of compensation is changing over time. (6) Time scale factor is also used to simulate. In the article, we set three-time periods to calculate the different amount of compensation for the water source area. Finally, the Southern Shaanxi, supplied 70% water to Danjiangkou Reservoir, were analyzed by this model. We make full use of the reasonable eco-compensation strategy and try to solve actual problems of water source area and even provide a basis conception for the watershed protection and management.

Rivers and streams in the media: a content analysis of ecosystem services.

Although ecosystem services research has become common, few efforts are directed toward in-depth understanding of the specific ecological quantities people value. The theoretical framework of final ecosystem services focuses attention on such measurable attributes, as a common currency for social-ecological systems research. Environmental communications as well as ecological monitoring and analysis efforts could be enhanced through increased documentation of final ecosystem services. For example, small changes in the way ecosystems are described could strongly influence relevance to the public and improve the foundation for environmental decision making. Focusing on rivers and streams, we conducted a content analysis of existing publications to document the breadth and frequency with which various measurable attributes, such as flooding, water quality characteristics, and wildlife appeared in different news sources over a multiyear timeline. In addition to attributes, motivations for human interest in river-related resources were also coded, such as recreation or preservation for future generations. To allow testing of differences between materials written for different audiences, three sources were sampled: a blog hosted by National Geographic, New York Times articles, and Wall Street Journal articles. The coding approach was rigorously tested in a pilot phase, with measures developed to ensure high data quality, including use of two independent coders. Results show numerous similarities across sources with some notable differences in emphasis. Significant relationships between groups of attribute and motivation codes were also found, one outcome of which is further support for the importance of nonuse values for fish and wildlife. Besides offering insight on ecosystem services, the project demonstrates an in-depth quantitative approach to analyzing preexisting qualitative data.

Scale criticality in estimating ecosystem carbon dynamics

Scaling is central to ecology and Earth system sciences. However, the importance of scale (i.e. resolution and extent) for understanding carbon dynamics across scales is poorly understood and quantified. We simulated carbon dynamics under a wide range of combinations of resolution (nine spatial resolutions of 250 m, 500 m, 1 km, 2 km, 5 km, 10 km, 20 km, 50 km, and 100 km) and extent (57 geospatial extents ranging from 108 to 1 247 034 km(2) ) in the southeastern United States to explore the existence of scale dependence of the simulated regional carbon balance. Results clearly show the existence of a critical threshold resolution for estimating carbon sequestration within a given extent and an error limit. Furthermore, an invariant power law scaling relationship was found between the critical resolution and the spatial extent as the critical resolution is proportional to A(n) (n is a constant, and A is the extent). Scale criticality and the power law relationship might be driven by the power law probability distributions of land surface and ecological quantities including disturbances at landscape to regional scales. The current overwhelming practices without considering scale criticality might have largely contributed to difficulties in balancing carbon budgets at regional and global scales.

How Individual Movement Response to Habitat Edges Affects Population Persistence and Spatial Spread

How individual-level movement decisions in response to habitat edges influence population-level patterns of persistence and spread of a species is a major challenge in spatial ecology and conservation biology. Here, we integrate novel insights into edge behavior, based on habitat preference and movement rates, into spatially explicit growth-dispersal models. We demonstrate how crucial ecological quantities (e.g., minimal patch size, spread rate) depend critically on these individual-level decisions. In particular, we find that including edge behavior properly in these models gives qualitatively different and intuitively more reasonable results than those of some previous studies that did not consider this level of detail. Our results highlight the importance of new empirical work on individual movement response to habitat edges.

Land use and land cover change and driving mechanism in the arid inland river basin: a case study of Tarim River, Xinjiang, China

Identifying the primary causes and examining the processes and trends of land use change are crucial for land use planning, utilization of regional resources and environment management. Combining the ecological quantity analysis with GIS technology, based on the land use data and remote sense images, the changes of land use and land cover and the driving force were analyzed in the mainstream of the Tarim River from 1973 to 2005. The results showed that the areas of cropland and built-up land increased obviously, grassland, forest and wetland decreased and unused land increased first and then decreased. The major patterns of land use change were from grassland (major source), woodland, unused land and wetland to cropland, from a great lot of cropland to built-up land, as well as from grassland (occupying 30 %), woodland and wetland to unused land. Land use change underwent a process of obvious change–slow change–obvious change–tremendous change in the period of 1973–2005. The influence of natural factors including elevation, slope, soil types, distance from river course and climate change on land use and land cover change was limited. Population growth, economic development and industry policy were the dominant driving force for land use and land cover change in the mainstream of the Tarim River. The sustainable use of land resources is significant to keep economic development and environmental protection in arid inland river basin.

Likelihood analysis of species occurrence probability from presence‐only data for modelling species distributions

Summary1. Understanding the factors affecting species occurrence is a pre‐eminent focus of applied ecological research. However, direct information about species occurrence is lacking for many species. Instead, researchers sometimes have to rely on so‐called presence‐only data (i.e. when no direct information about absences is available), which often results from opportunistic, unstructured sampling. maxent is a widely used software program designed to model and map species distribution using presence‐only data.2. We provide a critical review of maxent as applied to species distribution modelling and discuss how it can lead to inferential errors. A chief concern is that maxent produces a number of poorly defined indices that are not directly related to the actual parameter of interest – the probability of occurrence (ψ). This focus on an index was motivated by the belief that it is not possible to estimate ψ from presence‐only data; however, we demonstrate that ψ is identifiable using conventional likelihood methods under the assumptions of random sampling and constant probability of species detection.3. The model is implemented in a convenient r package which we use to apply the model to simulated data and data from the North American Breeding Bird Survey. We demonstrate that maxent produces extreme under‐predictions when compared to estimates produced by logistic regression which uses the full (presence/absence) data set. We note that maxent predictions are extremely sensitive to specification of the background prevalence, which is not objectively estimated using the maxent method.4. As with maxent, formal model‐based inference requires a random sample of presence locations. Many presence‐only data sets, such as those based on museum records and herbarium collections, may not satisfy this assumption. However, when sampling is random, we believe that inference should be based on formal methods that facilitate inference about interpretable ecological quantities instead of vaguely defined indices.

The change of land use/cover and characteristics of landscape pattern in arid areas oasis: An application in Jinghe, Xinjiang

This paper uses 3S technology in macroscopic. Combining the integrated technology of ecological quantity analytical method with GIS technology through ArcGIS and Fragstats, the authors study the images of 1972, 1990, 2001, and 2005 and obtained land use data in Jinghe County. Then, the change of land use/cover and landscape pattern had been analyzed in the Jinghe County of Xinjiang. The conclusions were as follows: (1) The trend of LUCC is that the area of oasis expands slowly in nearly 33 years between 1972 to 2005 in Jinghe County. (2) The water area is mainly influenced by Ebinur Lake, so the area expands a little in this period. (3) The area of salinization-land expands at first and reduces later. The area of sand land decreases and the other land class increases, while the probability of transfer is always high. (4) Landscape change is also obvious throughout the decades. Overall, landscape density increases, the largest path index decreases at first and expends later, the weight area index decreases, and the shape of landscape becomes regulated. The nearest distances, the degrees of reunite, and outspread decreases. It shows that the connection of the main path in 1972 is better than 2005, wherein the patch becomes more complex. From the changes of Shannon’s Diversity Index and Shannon’s Evenness Index, we know that the diversity of landscape and the Interspersion Juxtaposition Index increase. The degree of diversity landscape and fragmentation increase also shows that the land uses become more complex. All in all, it is essential to intensify the spatial relationships among landscape elements and to maintain the continuity of landscape ecological process and pattern in the course of area expansion.

Eco-environmental water demands for the Baiyangdian Wetland

In recent years, the hydrological characters of Baiyangdian Wetland have changed greatly, which, in turn, influence the biotic component, the structure and function of the wetland ecosystem. In order to determine the demands for water resources of ecological wetland system, a method of ecological water level coefficient was suggested to calculate the water resources demands for wetland environment use. This research showed that the minimum coefficient is 0.94 and the optimal coefficient is more than 1.10. According to these two coefficients, the ecological water level and water quantity can be estimated. The results indicate that the amount of the minimal and optimal eco-environmental water requirements are 0.87 × 108 and 2.78 × 108 m3 in average monthly, respectively, with the maximum eco-environmental water requirement in summer and the minimum in winter. The annual change of eco-environment water demand is in according with the climate change and hydrological characters. The method of ecological water level emphasizes that wetland ecosystem adapts to the hydrological conditions, so it can be used in practice well.

Scaling of offspring number and mass to plant and animal size: model and meta-analysis

The scaling of reproductive parameters to body size is important for understanding ecological and evolutionary patterns. Here, we derived allometric relationships for the number and mass of seeds, eggs and neonates from an existing model on population production. In a separate meta-analysis, we collected 79 empirical regressions on offspring mass and number covering different taxa and various habitats. The literature review served as a validation of the model, whereas, vice versa, consistency of isolated regressions with each other and related ecological quantities was checked with the model. The total offspring mass delivered in a reproductive event scaled to adult size with slopes in the range of about 3/4 to 1. Exponents for individual seed, egg and neonate mass varied around 1/2 for most heterotherms and between 3/4 and 1 for most homeotherms. The scaling of the progeny number released in a sowing, clutch or litter was opposite to that of their size. The linear regressions fitted into a triangular envelope where maximum offspring mass is limited by the size of the adult. Minimum seed and egg size scaled with weight exponents of approximately 0 up to 1/4. These patterns can be explained by the influence of parents on the fate of their offspring, covering the continuum of r-strategists (pelagic–aquatic, arial, most invertebrates, heterotherms) and K-strategists (littoral–terrestrial, some invertebrates, homeotherms).

Bayesian change‐point analyses in ecology

Ecological and biological processes can change from one state to another once a threshold has been crossed in space or time. Threshold responses to incremental changes in underlying variables can characterize diverse processes from climate change to the desertification of arid lands from overgrazing. Simultaneously estimating the location of thresholds and associated ecological parameters can be difficult: ecological data are often 'noisy', which can make the identification of the locations of ecological thresholds challenging. We illustrate this problem using two ecological examples and apply a class of statistical models well-suited to addressing this problem. We first consider the case of estimating allometric relationships between tree diameter and height when the trees have distinctly different growth modes across life-history stages. We next estimate the effects of canopy gaps and dense understory vegetation on tree recruitment in transects that transverse both canopy and gap conditions. The Bayesian change-point models that we present estimate both threshold locations and the slope or level of ecological quantities of interest, while incorporating uncertainty in the change-point location into these estimates. This class of models is suitable for problems with multiple thresholds and can account for spatial or temporal autocorrelation.

Ecolingua: a formal ontology for data in ecology

Ecolingua is an ontology for ecological quantitative data, which has been designed through reuse of a conceptualisation of quantities and their physical dimensions provided by the EngMath family of ontologies. A hierarchy of ecological quantity classes is presented together with their definition axioms in first-order logic. An implementation-level application of the ontology is discussed, by way of which conceptual ecological models are synthesised from data annotations in Ecolingua through reuse of existing model structures.

Ecolingua: a Formal ontology for data in ecology

Abstract Ecolingua is an ontology for ecological quantitative data, which has been designed through reuse of a conceptualisation of quantities and their physical dimensions provided by theEngMath family of ontologies. A hierarchy of ecological quantity classes is presented together with their definition axioms in first-order logic. An implementation-level application of the ontology is discussed, by way of which conceptual ecological models are synthesised from data annotations inEcolingua through reuse of existing model structures.