Search

Aim: Species distribution information is essential under increasing global changes, and models can be used to acquire such information but they can be affected by different errors/bias. Here, we evaluated the degree to which errors in species data (false presences–absences) affect model predictions and how this is reflected in commonly used evaluation metrics. Location: Western Swiss Alps. Methods: Using 100 virtual species and different sampling methods, we created observation datasets of different sizes (100–400–1,600) and added increasing levels of errors (creating false positives or negatives; from 0% to 50%). These degraded datasets were used to fit models using generalized linear model, random forest and boosted regression trees. Model fit (ability to reproduce calibration data) and predictive success (ability to predict the true distribution) were measured on probabilistic/binary outcomes using Kappa, TSS, MaxKappa, MaxTSS and Somers'D (rescaled AUC). Results: The interpretation of models' performance depended on the data and metrics used to evaluate them, with conclusions differing whether model fit, or predictive success were measured. Added errors reduced model performance, with effects expectedly decreasing as sample size increased. Model performance was more affected by false positives than by false negatives. Models with different techniques were differently affected by errors: models with high fit presenting lower predictive success (RFs), and vice versa (GLMs). High evaluation metrics could still be obtained with 30% error added, indicating that some metrics (Somers'D) might not be sensitive enough to detect data degradation. Main conclusions: Our findings highlight the need to reconsider the interpretation scale of some commonly used evaluation metrics: Kappa seems more realistic than Somers'D/AUC or TSS. High fits were obtained with high levels of error added, showing that RF overfits the data. When collecting occurrence databases, it is advisory to reduce the rate of false positives (or increase sample sizes) rather than false negatives. [ABSTRACT FROM AUTHOR]

Tierberg-LTER is a research site established in 1987 in the semi-arid Succulent Karoo near Prince Albert in the Western Cape province, South Africa. The original purpose for its establishment was to study ecosystem dynamics and the drivers of vegetation in the context of historical land use. The large body of work that has materialised from Tierberg-LTER is grounded on extensive baseline data and has greatly influenced the broader Karoo literature. It stands as the only long-term ecological research facility for the semi-arid region of South Africa. The Karoo environment faces several new developments centred largely on the expanding energy sector. Under a changing climate, ecosystems will have to further adapt to the impacts of such developments. The future research programme for Tierberg-LTER will accordingly continue to focus on understanding Karoo ecosystem dynamics and drivers of climate and anthropogenic change at local scales, thereby informing management and mitigation of future development impacts. Among a growing network of Karoo research sites, Tierberg-LTER maintains a unique role for long-term and intensive research that will contribute significantly towards the South African Environmental Observation Network’s vision of furthering ecosystem integrity, societal prosperity and sustainable development. [ABSTRACT FROM AUTHOR]

Context: This paper presents a nitrogen flux model that applies previously developed denitrification process equations for an entire catchment. These denitrification equations were previously applied on single flowpaths; this paper implements a model to apply these equations to all possible flowpaths within the catchment.Objectives: The purpose of this paper is to describe a new modeling approach (GeoN) to represent and communicate the geospatial interaction between nitrogen sources and sinks within a catchment. This model is of use to local decision-makers because it identifies all areas that are prone to delivering large percentages of nitrogen to sensitive estuaries and those areas that are already providing natural denitrification of the system.Methods: The GeoN model utilizes a combination of ArcGIS hydrology tools and custom Python scripts to simulate the flow of nitrogen from a source to the catchment outlet. The model also simulates interactions with sinks that provide natural denitrification.Results: The model is validated using 11 USGS stream gauge locations. A two one-sided t test (TOST) is performed to evaluate the equivalence between the measured and simulated values. The test shows that the modeled and measured values are not statistically different. The model also simulates overall catchment retention of nitrogen within the range established in the literature for a coastal New England catchment.Conclusions: This research introduces a model that simulates geospatial interaction of all nitrogen sinks and sources within a catchment allowing the identification of key areas with regards to water quality. [ABSTRACT FROM AUTHOR]

Context: Biodiversity is modulated by the spatial structure of the landscape. Thus, landscape metrics can be useful indicators of biota integrity and vulnerability, helping in conservation and management decisions.Objective: We performed the first quantitative analysis of the spatial structure of the Caatinga drylands. We estimated the habitat amount and the fragmentation pattern of this region using a multi-scale perspective.Methods: Using the Brazilian official database of native remnants, we calculated the number and percentage of remaining fragments per size class and we describe how habitat amount changes along the landscape. By simulating different dispersal capacities, we estimated the functional connectivity among remnants. We also calculated the cumulative core area as a function of different edge effect widths.Results: Caatinga is subdivided into 47,100 fragments. Although 91% of them are smaller than 500 ha, 720 fragments are larger than 10,000 ha, corresponding to 78% of the remaining vegetation. Potentially, 95% of the vegetation is accessible to species that can cross 1000 m of matrix. With one kilometer of edge effect, the core area is reduced to a quarter of the remaining vegetation. The habitat amount analyzes reinforced the regional differences in the spatial distribution of the remnants.Conclusions: Caatinga remains well connected for species with moderate and high dispersal capacities. However much of its remaining area is vulnerable to anthropogenic disturbances. Expansion of the protected area network and effective natural resource management to avoid overexploitation of the remnants are key strategies for maintaining the Caatinga biodiversity and its services. [ABSTRACT FROM AUTHOR]

Context: To prevent the area of arable land from crossing the limit of 120 million ha arable land red line, China’s government proposed a linked urban-rural construction land policy. This policy helps to protect the arable land but will impact the rural landscape.Objective: The objective is to evaluate the effect of the linked urban-rural construction land policy on rural landscape in the future.Methods: We performed a simulation method to predict the rural landscape pattern changes in Tianjin during 2005-2020 using a cellular automata and multi-agent system model under the scenarios with or without implementing this policy. The landscape metrics were calculated for both scenarios to find the effects caused by this policy.Results: Following this policy, the Total Area and Large Patch Index of arable land decreased slowly. 65.50% of the occupied arable land can be compensated. For rural settlements, the Mean Patch Area increased to 2.87 times that in 2005. Number of Patches reduced greatly, and 1053 of the total rural settlements distributed along the periphery of Tianjin were reclaimed for arable land during 2005-2020. Aggregation Index increased greatly.Conclusions: According to the simulation model, the policy is effective on slowing down the loss of total arable land and the process of large arable land fragmentation. The increasing degree of aggregation of rural settlements is beneficial to the optimal allocation of resources and rural centralized management. However, as the rural settlements gather to urban construction land, they are more vulnerable to urban issues. [ABSTRACT FROM AUTHOR]

Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models’ accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For other phenophases, RMSE are higher and rise up to 9-10 days in the case of the earliest spring phenophases. [ABSTRACT FROM AUTHOR]

Ecological interactions are highly dynamic in time and space. Previous studies of plant-animal mutualistic networks have shown that the occurrence of interactions varies substantially across years. We analyzed interannual variation of a quantitative mutualistic network, in which links are weighted by interaction frequency. The network was sampled over six consecutive years, representing one of the longest time series for a community-wide mutualistic network. We estimated the interannual similarity in interactions and assessed the determinants of their persistence. The occurrence of interactions varied greatly among years, with most interactions seen in only one year (64%) and few (20%) in more than two years. This variation was associated with the frequency and position of interactions relative to the network core, so that the network consisted of a persistent core of frequent interactions and many peripheral, infrequent interactions. Null model analyses suggest that species abundances play a substantial role in generating these patterns. Our study represents an important step in the study of ecological networks, furthering our mechanistic understanding of the ecological processes driving the temporal persistence of interactions. [ABSTRACT FROM AUTHOR]

Comparing the structure of presence/absence (i.e., binary) matrices with those of randomized counterparts is a common practice in ecology. However, differences in the randomization procedures (null models) can affect the results of the comparisons, leading matrix structural patterns to appear either 'random' or not. Subjectivity in the choice of one particular null model over another makes it often advisable to compare the results obtained using several different approaches. Yet, available algorithms to randomize binary matrices differ substantially in respect to the constraints they impose on the discrepancy between observed and randomized row and column marginal totals, which complicates the interpretation of contrasting patterns. This calls for new strategies both to explore intermediate scenarios of restrictiveness in-between extreme constraint assumptions, and to properly synthesize the resulting information. Here we introduce a new modeling framework based on a flexible matrix randomization algorithm (named the 'Tuning Peg' algorithm) that addresses both issues. The algorithm consists of a modified swap procedure in which the discrepancy between the row and column marginal totals of the target matrix and those of its randomized counterpart can be 'tuned' in a continuous way by two parameters (controlling, respectively, row and column discrepancy). We show how combining the Tuning Peg with a wise random walk procedure makes it possible to explore the complete null space embraced by existing algorithms. This exploration allows researchers to visualize matrix structural patterns in an innovative bi-dimensional landscape of significance/effect size. We demonstrate the rational and potential of our approach with a set of simulated and real matrices, showing how the simultaneous investigation of a comprehensive and continuous portion of the null space can be extremely informative, and possibly key to resolving longstanding debates in the analysis of ecological matrices. [ABSTRACT FROM AUTHOR]

Dams located upstream only release water during the period of hydropower generation. This induces short-term fluctuations of water discharge in the downstream reach, which is called hydropeaking. As occurs quite often, if the temperature of the water released form the upstream dam is different from the water that is flowing in the downstream reach, the water temperature also tends to show short-term fluctuations, which is called thermopeaking. This study investigates the impacts of both hydropeaking and thermopeaking on the downstream habitat. The study area is a 2.3 km long reach located downstream from the Goesan Dam in the Dal River, Korea. To assess such impacts, this study conducted physical habitat simulations. The CMS-Flow model was used for the computation of the flow and water temperature, and the GEP model for the habitat simulation. Three physical habitat variables, flow depth, velocity, and water temperature, were used. The Zacco platypus was selected as the target fish in the study area. Simulation results indicated that the hydropeaking flows significantly reduced both the CSI and the WUA when compared with the natural flow regime. In addition, the use of the water temperature in the physical habitat simulations further decreased both CSI and WUA, indicating that thermopeaking is as important as hydropeaking in this type of assessment. [ABSTRACT FROM AUTHOR]

Sundarapandian Pattinam and Manamelkudi are two locations situated on the east coast of Tamil Nadu, India (9°40'N 69°20'E), along Palk Strait, the sea channel between India and Sri Lanka, in the Arabian Sea. These sites are located in one of the most productives zones of the world's oceans and they were sampled from 1 July 2005 to 30 June 2006. The present investigation has been made to study the distribution of planktonic copepods, in particular the occurrence of species in local assemblages, using null-model analysis. The results revealed that copepod assemblages can be considered random for Station I, whereas for Station II the species assemblages observed are not random. Hence, conservational measures are needed to protect the coastline of these two stations from too large an increase in aquacultural practice and an uncontrolled growth of fishery production, both intended for the economic upheaval of the local fishermen's communities. [ABSTRACT FROM AUTHOR]

In this paper, I adopt the view that if general forces or processes can be detected in ecology, then the principles or models that represent them should provide predictions that are approximately correct and, when not, should lead to the sorts of intervening factors that usually make trouble. I argue that Lotka-Volterra principles do not meet this standard; in both their simple 'strategic' and their complex 'tactical' forms they are not approximately correct of the findings of the laboratory experiments and historical studies most likely to confirm them; nor do they instruct ecologists where to look for likely intervening factors. Evidence drawn from long-term case studies and other available data sets suggests that the populations of predators and their prey are not regulated by an interaction between them but are controlled by transient, contingent, and accidental events that affect each animal and each population individualistically. This paper argues that the presence of general forces or processes in ecology should be determined by comparing competing models of these forces not just to each other or to a null model but also to case studies that may challenge theoretical approaches with convincing individualistic causal accounts of the phenomena. [ABSTRACT FROM AUTHOR]

The 'niche variation hypothesis' (NVH) predicts that populations with wider niches should display higher among-individual variability. This prediction originally stated at the intra-specific level may be extended to the inter-specific level: individuals of generalist species may differ to a greater extent than individuals of a specialist species. We tested the NVH at intra- and inter-specific levels based on a large diet database of three large herbivore feces collected in the field and analyzed using DNA metabarcoding. The three herbivores (roe deer Capreolus capreolus, chamois Rupicapra rupicapra and mouflon Ovis musimon) are highly contrasted in terms of sociality (solitary to highly gregarious) and diet. The NVH at the intraspecific level was tested by relating, for the same population, diet breadth and inter-individual variation across the four seasons. Compared to null models, our data supported the NVH both at the intra- and inter-specific levels. Inter-individual variation of the diet of solitary species was not larger than in social species, although social individuals feed together and could therefore have more similar diets. Hence, the NVH better explained diet breadth than other factors such as sociality. The expansion of the population niche of the three species was driven by resource availability, and achieved by an increase in inter-individual variation, and the level of inter-individual variability was larger in the generalist species (mouflon) than in the specialist one (roe deer). This mechanism at the base of the NVH appears at play at different levels of biological organization, from populations to communities. [ABSTRACT FROM AUTHOR]

Water sounds are believed to be important in triggering the upriver ascent behavior of migratory fish species. Modeling the effect of underwater sound on fish preference represents a promising technique to determine migratory paths for the comprehensive analysis of river habitat suitability. In this study, we aimed to determine the preference and weight of underwater sounds by laboratory experiments using adult and juvenile ayu (Plecoglossus altivelis). A watercourse with an underwater speaker installed at one end was used for the experiments. Sound was emitted from the speaker at different sound pressure levels. The sound sources included pure tones (100 Hz, 200 Hz, 400 Hz, and 800 Hz), white noise, recorded sound from a weir on the Fushino River, and recorded sound at a fish ladder on the Misumi River (Japan). The results showed that juvenile and adult ayu avoided the pure sound of 100 Hz and recorded sound of the Fushino River weir. In contrast, both adults and juveniles preferred the pure sound of 200 Hz and recorded sound of the fish ladder. Moreover, by comparing the obtained quantitative preference parameters for sounds, we found that adult ayu expressed higher preference for sound than juveniles. We designed a procedure to calculate sound preference and built it into our fish behavior simulation model on geographic information system (GIS) software. We believe that the model could successfully reproduce observed fish migration behavior in rivers. This technique could be used for designing an underwater soundscape to attract fish to the entrances of fish ladders or to keep fish away from hydropower plants. [ABSTRACT FROM AUTHOR]

Incidental mortality from commercial fishing operations can alter the demography and distribution of affected species. Population assessments for long-lived, wide-ranging species such as sea turtles may need to include a spatial component and a consideration of the affected life stages. We used a spatial matrix population projection model to examine the impact of federally authorized incidental fishing mortality on a simulated Northwest Atlantic loggerhead sea turtle population. We projected the population for 100 years, simulating fisheries bycatch mortality through removals from the population that were directed toward specific spatial units or life stages. We kept removals constant across years for most simulations. We incorporated demographic information in the removals by using reproductive values to estimate adult-equivalent turtles, which we compared with removing individual turtles. Removals made in terms of adult equivalents had identical population impacts for all removal schemes (80% population decline after 40 years). Removals made in terms of individuals had the greatest impact if weighted toward the adult life stage (89% population decline after 40 years) and the least impact if weighted toward the youngest life stage (78% population decline after 40 years). Differences in impact between spatially directed removals were attributed to unequal stage distributions between regions. Because the population impact of loggerhead mortality depends on the affected life stage, the monitoring of population-level impacts is more reliable if authorized incidental take is specified and monitored by life stage or by adult equivalents. [ABSTRACT FROM AUTHOR]

Population dynamics and in particular microbial population dynamics, though intrinsically discrete and random, are conventionally represented as deterministic differential equations systems. In these type of models, populations are represented by continuous population sizes or densities usually with deterministic dynamics. Over the last decades, alternate individual-based models have been proposed where population is explicitly represented as a set of individuals. These may include stochastic dynamics or stochastic rules. With reference to the last class of models we can also associate pure jump processes where the population is described as a discrete population size with stochastic discrete event evolutions. In the first class of models the population dynamics and its representation may be viewed respectively as deterministic and continuous, in the second class they may be viewed respectively as stochastic and discrete. In this present work, we present a modeling approach that bridges the two representations. This link can be mathematically described as a functional law of large numbers in high population size asymptotics. These results suggest new strategies of modeling and simulation. We illustrate this approach on the modeling of the chemostat. [ABSTRACT FROM AUTHOR]

Sampling bias contained in data of biological surveys is very common. Bias is clearly a function of roads, cities, rivers, or other physical features that determines accessibility of collectors, and many data sets of species are presence-only. We set out to estimate spatial sampling bias in a region, based on presence-only data, by explicitly incorporating information on these accessibility factors, and by considering a target group of species that may share a common search pattern. In order to indirectly estimate the number of individuals, we also resort to the concept of species richness. A probabilistic (multinomial) model is proposed, enabling standard likelihood inference procedures to be implemented. Simulation scenarios for exploration of the model and experimentation with the estimation procedure are included. Illustrative examples over a region of Mexico with mammals and butterflies are also reported with insightful results. Our model is able to estimate the sampling bias in a region and enhance the inferences regarding presence-only data. [ABSTRACT FROM AUTHOR]

Accurate simulation of terrestrial gross primary production (GPP), the largest global carbon flux, benefits our understanding of carbon cycle and its source of variation. This paper presents a novel light use efficiency-based GPP model called the terrestrial ecosystem carbon flux model (TEC) driven by MODIS FPAR and climate data coupled with a precipitation-driven evapotranspiration (E) model ( Yan et al., 2012 ). TEC incorporated a new water stress factor, defined as the ratio of actual E to Priestley and Taylor (1972) potential evaporation (EPT). A maximum light use efficiency (ϵ*) of 1.8 gC MJ−1 and 2.76 gC MJ−1 was applied to C3 and C4 ecosystems, respectively. An evaluation at 18 eddy covariance flux towers representing various ecosystem types under various climates indicates that the TEC model predicted monthly average GPP for all sites with overall statistics of r = 0.85, RMSE = 2.20 gC m−2 day−1, and bias = −0.05 gC m−2 day−1. For comparison the MODIS GPP products (MOD17A2) had overall statistics of r = 0.73, RMSE = 2.82 gC m−2 day−1, and bias = −0.31 gC m−2 day−1 for this same set of data. In this case, the TEC model performed better than MOD17A2 products, especially for C4 plants. We obtained an estimate of global mean annual GPP flux at 128.2 ± 1.5 Pg C yr −1 from monthly MODIS FPAR and European Centre for Medium-Range Weather Forecasts (ECMWF) ERA reanalysis data at a 1.0° spatial resolution over 11 year period from 2000 to 2010. This falls in the range of published land GPP estimates that consider the effect of C4 and C3 species. The TEC model with its new definition of water stress factor and its parameterization of C4 and C3 plants should help better understand the coupled climate-carbon cycle processes. [ABSTRACT FROM AUTHOR]

Begomovirus is a genus of highly destructive plant viruses that belongs to the family Geminiviriade and spreads through a single vector, the whitefly Bemisia tabaci . Although an old family of organisms, begomovirus has recently emerged as a potent threat to large-scale cultivation of crops. It is a threat with a very wide domain of influence and it can infect a very wide range of green plants cultivated for both sustenance and as cash crops. We introduce a mathematical model that simulates the complex dynamic interaction between begomovirus genetics, their adaptability to certain plants, and the availability of those plants to the virus under different cropping patterns. The model captures many empirically observed patterns of begomovirus epidemic outbursts, even if the equations do not directly depend on the genetics of begomovirus strains, and simply assume the vector to be ubiquitous. The model is formulated as a population dynamic system of differential equations, with nonlinear interactions between plant availability and begomovirus dynamic adaptability to different crop species. It also includes spatial diffusion allowing simulations over multiple neighboring regions. The ability of such a model to reproduce qualitatively correct epidemic structures indicates that the main reason for epidemic outbursts and the global spreading of the disease could be found in the patterns of inter-species interactions, many of which are human-induced. If this is the case, then the key to mitigating begomovirus epidemics would be the modification of agricultural practices. In particular, the use of intensive cropping patterns and resistant cultivars triggers aggressive virus adaptability through mutation speed-up. It seems that the only simple recourse would be to develop more diverse and less concentrated cropping patterns, both in cropland extent and in time. [ABSTRACT FROM AUTHOR]

Gastrointestinal nematodes are important parasites of livestock and wildlife worldwide, causing mortality and morbidity, regulating host populations and threatening food security through reduced productivity of ruminant livestock. A significant part of the life-cycle of most GINs is completed outside of the host. GINs are therefore susceptible to changes in climate, and evidence of climate-driven changes in the phenology of GINs and the seasonal incidence of disease already exists. A modelling framework, GLOWORM-FL was developed to predict changes in the seasonal dynamics of the free-living stages of trichostrongylid GINs on pasture as a first step towards evaluating potential mitigation strategies. The general model framework was parameterised and validated for three GIN species that infect a range of ruminants worldwide: Haemonchus contortus , Teladorsagia circumcincta and Ostertagia ostertagi . The model builds significantly on previous models of GIN population dynamics by incorporating the behaviour of nematodes in response to climate variability, facilitated by recent advances in our understanding of the ecology of GINs. Simulations using historical and predicted future climatic data for a temperate region reveal the potential for an increase in annual infection pressure of H. contortus and T. circumcincta in small ruminants as increasing temperatures accelerate development and remove constraints on the development of H. contortus during the winter months. In contrast, a significant decrease in annual infection pressure is predicted for O. ostertagi in cattle due to accelerated development being offset by rapid mortality at higher temperatures. A similar trade-off is predicted during the summer months for H. contortus and T. circumcincta resulting in complex seasonal dynamics of the availability of infective stages on pasture. These changes could have significant impacts on the seasonal incidence and pathology of infection by GINs. GLOWORM-FL therefore provides an important tool to predict the seasonal risk of transmission of GINs and will aid in the design of climate-driven, risk-based GIN control strategies. [ABSTRACT FROM AUTHOR]

Many organisms can alternatively expand their range through long- and short-distance movements. Understanding the relative importance of these two strategies in determining species range size is of great interest in ecology and conservation biology. The more distant species move, the lower their probability of finding suitable conditions for survival. Thus, a species has a lower probability to succeed in colonization through long-distance dispersal than through short-distance dispersal, i.e., a tradeoff exists between the two strategies. Here, I investigate this issue by using a spatially explicit model where species move from patch to patch across a fragmented landscape. By analyzing the outcomes of 10,000 simulations run on the model under a wide range of tradeoff scenarios, I identified colonization ability as the strongest predictor of species range, followed by short distance dispersal ability, short distance colonization ability and long distance dispersal ability. Thus, range size of species having two different movement strategies is mainly determined by how far the species can move in the short distance strategy, and by its likelihood to succeed in colonization of distant localities, even if the dispersal/colonization tradeoffs between the two strategies are very small. [ABSTRACT FROM AUTHOR]

Extended logistic and competitive Lotka–Volterra equations were developed by Eizi Kuno to understand the implications of population heterogeneity (especially spatial) for population growth. Population heterogeneity, defined as the presence of individuals in some patches of population and not others, is the resulting expression of a number of processes, including dispersal, habitat heterogeneity and searching behaviour. Kuno's models allow the effect of population heterogeneity (thus defined) on a population at equilibrium to be accounted for without using multi-patch models. This paper demonstrates this for the first time using numerical simulations and presents a more complete mathematical derivation of his models. An extension of Kuno's equations to model predator–prey scenarios with heterogeneity in the prey population is also developed. Analysis of this predator–prey case shows that a patchy distribution of prey facilitates their stable coexistence with predators. This paper has broad implications for ecological modelling because it shows how the effects of a number of population processes, including dispersal, are reflected in the density of populations at equilibrium. Therefore, by adjusting the equilibrium solutions of models, the effects of a number of processes are captured without representing the processes themselves in an explicit way. [ABSTRACT FROM AUTHOR]

Forest landscape models are effective tools for exploring the effects of long-term and large-scale landscape processes such as seed dispersal, fire, and timber harvest. These models have been widely used for about a decade, and although significant advances in theory and technology have been incorporated into their development, evaluating the veracity of simulated results from forest landscape models remains challenging. In this study, we evaluated simulated forest succession and the effects of simulated fire and harvest by a spatially explicit forest landscape model (LANDIS PRO), initialized using forest inventory data (second and third tier data from years 2000 and 2010). Our results suggested that the initialized forest landscape constructed from the year 2000 forest inventory data adequately represented the forest composition and structure from that year. The simulated density and basal area from year 2010 adequately represented the forest inventory data from that year at landscape scales. Our results indicated that the simulated fire and harvest effects were comparable to the field data (measured density and basal area). Results in this study quantified the near-term reliability and confidence of the model as well as prediction uncertainties. [ABSTRACT FROM AUTHOR]

Ecological models are powerful tools for generating predictions about the viability of populations of endangered species, especially in landscapes where they may be subject to complex, cross-scale disturbances. Spatially explicit, individual-based approaches are particularly promising due to their ability to simulate the effect of landscape level changes in habitat on individual-level behaviour, thus predicting possible emergent responses from the bottom up. We apply this approach to modelling the movement behaviour and the complex life cycles of two species of stream-dwelling salamanders (the Allegheny Mountain Dusky Salamander, Desmognathus ochrophaeus, and the Northern Spring Salamander, Gyrinophilus porphyriticus) in response to a spatially and temporally varying environment. Despite the poor state of ecological knowledge about these species, our model provides reasonable predictions about life cycle, as well as the density and distribution of salamanders. When tested with a dynamic, drought prone environment, the model predicts viability levels that are biologically plausible. By simulating the cross-scale interactions between organisms and their environment, individual-based models such as we have developed here provide a new tool for in silico investigations of the expected impacts of varying landscape scenarios and environmental changes. [ABSTRACT FROM AUTHOR]

In urban and other built environments, management decisions serve as a prominent feedback between biodiversity patterns and human-controlled environmental variables. In this study, we used the metacommunity concept to assess the mechanisms that link zooplankton biodiversity to different management regimes in urban water bodies associated with the Baltimore Ecosystem Study Long-Term Ecological Research site (USA). In the summer of 2011, we sampled zooplankton in 21 ponds built for stormwater management. Ponds were classified as either unmanaged ( n = 9) or actively managed ( n = 12) for recreation and aesthetic value, where managed ponds received multiple chemical and algaecide applications to improve water clarity. We found managed ponds had higher local (alpha) diversity and lower spatial turnover in community composition (beta-diversity), and thus greater biotic homogenization than ponds that were unmanaged. We developed a lottery-based metacommunity simulation (MCSim) to assess how niche and dispersal dynamics could create the observed biodiversity patterns, and to assess whether biotic homogenization was related to management. A comparison of empirical and simulated diversity patterns suggests the zooplankton pond metacommunity was influenced by both dispersal and niche-based community assembly dynamics. Simulations showed that the observed biotic homogenization effect was expected based on the spatially aggregated distribution of managed ponds, but pond management was not likely exacerbating biotic homogenization in this system. Such insight is essential to understand how environmental management can affect biodiversity at local and regional scales. [ABSTRACT FROM AUTHOR]

Multi-host pathogens can pose a serious conservation threat when free-ranging domestic animal populations occur alongside susceptible populations of wild species. An example is canine distemper virus (CDV), which can occur at high prevalence in domestic dog (Canis familiaris) populations from which it may be transmitted (spillover) into wild carnivore populations. Effective management of such disease threats is hindered by our limited understanding of the the dynamics of interspecific CDV transmission in natural settings. We used a modeling approach to better understand CDV spillover threats to wild Indian foxes (Vulpes bengalensis) occurring in a protected grassland habitat in central India. An agent-based stochastic simulation model was built, and parameterized with data from ecological and epidemiological studies. Based on the sensitivity analyses of the model, the CDV incidence rate in dogs was most influenced by the proportion of roamer dogs in the dog population. The CDV incidence rate in dogs was also sensitive to the CDV introduction frequency in the dog population. The proportion of roamer dogs in the dog population also influenced the number of CDV spillover events. The basic reproductive number (R0) for CDV in the model fox population was 0.85, indicating that CDV could not be independently sustained in the fox population. We used the model to explore potential management strategies to mitigate the risk of CDV spillover. Vaccination of local dog populations was an ineffective disease control strategy, while fox vaccination was highly effective. Interventions potentially resulting in lower contact rates between dogs and foxes, like reduction in village dog density and restricting dog movements in fox habitat, implemented in a sustained and integrated manner would be most effective in mitigating disease threats to foxes. Such modeling approaches can be used to better understand disease threats for other species of management concern, and to contrast potential management interventions. [ABSTRACT FROM AUTHOR]

Natural flow regimes can play a major role as an overarching ecosystem driver in reproduction and recruitment of riverine fishes. Human needs for freshwater however have altered hydrology of many riverine systems worldwide, threatening fish population sustainability. To understand and predict how spatiotemporal dynamics of flow regimes influence reproductive and recruitment variability, and ultimately population sustainability of shovelnose sturgeon (Scaphirhynchus platorynchus), we develop a spatially explicit (1D) individual-based population model that mechanistically (via energetics-based processes) simulates daily activities (dispersal, spawning, foraging, growth, and survival). With field observations of sturgeon and habitat conditions in a major tributary of the Missouri River system (USA), we calibrate and evaluate the model via pattern-oriented modeling. Model simulation experiments using 17-year environmental time series data showed that seasonal and interannual variation in hydrological conditions plays a major role in timing, location, and magnitude of spawning and recruitment success of sturgeon. During droughts, consecutive weak year-classes resulted in a steady population decline. While low flow and subsequent low prey production limited foraging opportunities and slowed gonad development, these conditions were not severe enough for adults to abort the reproductive cycle. Post-settlement larval sturgeon were however unable to feed efficiently to grow out of a size-dependent ‘predation window’, resulting in high mortality. Slow growth and low survival of larval sturgeon thus likely play a larger role in recruitment failures during droughts than low or lack of spawning events. [ABSTRACT FROM AUTHOR]

We use an agent-based model to analyze the effects of spatial heterogeneity and agents’ mobility on social–ecological outcomes. Our model is a stylized representation of a dynamic population of agents moving and harvesting a renewable resource. Cooperators (agents who harvest an amount close to the maximum sustainable yield) and selfish agents (those who harvest an amount greater than the sustainable yield) are simulated in the model. Three indicators of the outcomes of the system are analyzed: the number of settlements, the resource level, and the proportion of cooperators in the population. Our paper adds a more realistic approach to previous studies on the evolution of cooperation by considering a social–ecological system in which agents move in a landscape to harvest a renewable resource. Our results conclude that resource dynamics play an important role when studying levels of cooperation and resource use. Our simulations show that the agents’ mobility significantly affects the outcomes of the system. This response is nonlinear and very sensible to the type of spatial distribution of the resource richness. In our simulations, better outcomes of long-term sustainability of the resource are obtained with moderate agent mobility and cooperation is enhanced in harsh environments with low resource level in which cooperative groups have natural boundaries fostered by agents’ low mobility. [ABSTRACT FROM AUTHOR]

This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling of hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions. [ABSTRACT FROM AUTHOR]

Many large carnivore populations exist in human-influenced stochastic environments where availability of natural food sources vary annually and anthropogenic food sources can supplement energetic demands, but at a potential demographic cost due to human–wildlife conflict and subsequent conflict management. Understanding how these competing factors influence a population is complex and difficult to study, but here we demonstrate the utility of using a stochastic projection matrix model and perturbation analysis to gain insight into this problem. We modeled a black bear population subjected to stochastic failures of fruiting and masting species, but with access to garbage in urban environments. We parameratized our model with data from a 6-year study on black bears in Aspen, Colorado and data synthesized from other research studies. Using computer simulation, we investigated the effect that different levels of conflict-bear removal can have on a bear population by comparing a “reference” scenario where bears did not benefit from human food sources or experience conflict-bear removals with two urban scenarios where bears had varying access to human foods, but conflict bears were removed. We used perturbation analyses to evaluate consequences for changing population vital rates and to estimate the impact each vital rate change had on population growth. Simulations were used to identify how much variation in each vital rate influenced variation in the population growth rate. We identified the survival rate of breeding adult females during good natural food years as having the highest elasticity value. We found that the benefit of increased cub production from available human food sources during natural food failure years was quickly negated if management of conflict bears through removal reduced adult female survival. Increasing the frequency of years when natural food production fails resulted in disproportionate impacts from available urban food and conflict-bear removals, where population growth rates in a High Removal scenario declined 1.5 times faster than in the reference scenario. Our findings suggest that for regions where changing climates will increase the frequency of natural food failures, managers may need to utilize non-lethal practices in managing conflict bears and municipalities will need to secure human food sources to reduce the need for conflict-bear removals and potential population declines. [ABSTRACT FROM AUTHOR]

The tidal freshwater marshes dominated by Phragmites australis (common reed) in the Chongxi Wetland are important components of the Yangtze River estuary in China. The litter from P. australis is exported to the surrounding estuarine area and the sea with the tidal flushing in the form of plant residue, particulate organic matter, and dissolved organic matter and is an important organic carbon resource of the East China Sea. A model was constructed using STELLA ® software (version 9.1.3) to simulate the contribution of macrophyte-derived organic carbon to surrounding estuary and ocean ecosystems. The model is based on the monitoring and observational data from field surveys and published information on the Chongxi Wetland from 2008 to 2011, and the response of the total organic carbon flowing out of the wetland to global changes was also predicted in conditions of plant shoots that were annually harvested in winter. The results demonstrate the following: (1) the annual contributed organic carbon is 891 g C m −2 , of which 612 g C m −2 flows out of the wetland directly as plant residue; (2) total organic carbon continually increases after a short decrease at the start of April of 2010, retains a high value from mid-July to mid-November and rapidly decreases to approximately zero during the harvest of the aboveground plant organs; and (3) accumulated annual organic carbon contributions to the surrounding estuarine and oceanic ecosystems are predicted to increase as the global average temperature rises, and the sea level increases. [ABSTRACT FROM AUTHOR]

Testing ecological models involves using independent data on model performance, which can be difficult or practically impossible to obtain. Individual based models of forest dynamics, or gap models, simulate the change of forests by computing the annual growth, birth and death of each tree at a location in a forest. The models are relatively simple and simulate results that can be translated to multiple response scales: Individual plant growth, population birth-death processes, stand environmental dynamics ( e.g ., evapotranspiration, element cycling, heat flux, etc .), landscape processes, and regional and global change. This paper reviews some of the approaches applied to testing gap models. Then, it demonstrates the testing of the performance of an individual-based gap model of forest dynamics, FAREAST, through comparison against independent data from China and across Russia. As part of this model testing, biomass simulation output for 93 locations is compared to independent field-collected inventory-data from 44 Russian forests, which span a broad range of forest types across Russia. FAREAST captures biomass dynamics and stabilization at specific locations bracketing the measured values. At Changbai Mountain, the model accurately predicts the community dynamics of complex mixed forest types present along an elevational gradient, as well as the broad regional compositional patterns across China and Russia. Validation of regional detailed landscape dynamics shows the model performs with fidelity with an average R2 value of 0.74 for 87 comparisons and an average root mean square error of 10.8 tC ha −1. Performance of the model for historical conditions implies the model's applicability across a broad region and suggests the usefulness of a detailed model for evaluating forest change to management and changing climate. [ABSTRACT FROM AUTHOR]

Red spruce (Picea rubens Sargent) has exhibited widespread growth decline and high mortality for the last half century in the eastern United States. Good prediction of this species’ distribution in relation to environmental conditions is critical for effective management. This study projects red spruce distribution in response to multiple causal mechanisms in the Great Smoky Mountains National Park (GSMNP) of the Southern Appalachian Mountains by coupling a temporal simulation model of tree growth (ARIM.SIM) to a species distribution model (ARIM.HAB). ARIM.HAB computed habitat suitability, estimated from ARIM.SIM-generated red spruce growth, for every spatial 30 m grid cell in GSMNP. ARIM.SIM showed that different factors were responsible for habitat suitability and growth at higher vs. lower elevations. The air pollution variables (acid rain and cloud immersion frequency) caused low habitat suitability at higher elevations (1800–2028 m). Reduced air pollution but greater stress from climatic variables (high temperatures, reduced precipitation) caused medium suitability at lower elevations (1400–1600 m). And less stress from air pollution and climate variables combined with ample water to produce highest suitability at intermediate elevations (1600–1800 m). The projected range was verified with an existing geospatial database for red spruce and showed excellent correspondence with present-day distribution (AUC = 0.99, kappa = 0.87 and TSS = 0.88). This research shows that species distribution models coupled with a process-based temporal simulation models can improve the precision and accuracy of, respectively, habitat suitability and range projections for species at local scales. [ABSTRACT FROM AUTHOR]

Use of Z values to evaluate nestedness significance is a common procedure. An appealing alternative to the use of Z values is that of using a value of relative nestedness (RN). However, there is no agreement on the preferable procedures to generate the null matrices needed to compute both Z and RN. In general, it is recommended to use restrictive null models that take into account row and column totals. The two most widely used null models of this kind, namely, FF and CE [that generate matrices with row and column sums equal (FF) or proportional (CE) to the row and column totals of the original matrix, respectively], are very different in terms of restrictiveness. We performed a set of comparative analyses on both theoretical and real matrices to investigate the differences between the use of Z and RN values, and between the use of FF and CE null models, when NODF (Nestedness metric based on overlap and decreasing fill) or ρ(A) (i.e., the largest eigenvalue of the adjacency matrix) are used to measure nestedness. We found no difference in the use of Z or RN values. On the other hand, we found that different combinations of nestedness measures and null models may lead to inconsistent outcomes. Our results offer some clarity on a few issues that, despite playing a central role in the practical application of nestedness analysis, have been little explored, and highlight the need for the definition of some commonly accepted standards. [ABSTRACT FROM AUTHOR]

Models of gross primary production (GPP) based on remote sensing measurements are currently parameterized with vegetation-specific parameter sets and therefore require accurate information on the distribution of vegetation to drive them. Can this parameterization scheme be replaced with a vegetation-invariant set of parameters that can maintain or increase model applicability by reducing errors introduced from the uncertainty of land cover classification? Based on the measurements of ecosystem carbon fluxes from 168 globally distributed sites in a range of vegetation types, we examined the predictive capacity of seven light use efficiency (LUE) models. Two model experiments were conducted: (i) a constant set of parameters for various vegetation types and (ii) vegetation-specific parameters. The results showed no significant differences in model performance in simulating GPP while using both set of parameters. These results indicate that a universal of set of parameters, which is independent of vegetation cover type and characteristics can be adopted in prevalent LUE models. Availability of this well tested and universal set of parameters would help to improve the accuracy and applicability of LUE models in various biomes and geographic regions. [ABSTRACT FROM AUTHOR]

Understanding the relative contributions of various evolutionary processes—purifying selection, neutral drift, and adaptation—is fundamental to evolutionary biology. A common metric to distinguish these processes is the ratio of nonsynonymous to synonymous substitutions (i.e., dN/dS) interpreted from the neutral theory as a null model. However, from biophysical considerations, mutations have non-negligible effects on the biophysical properties of proteins such as folding stability. In this work, we investigated how stability affects the rate of protein evolution in phylogenetic trees by using simulations that combine explicit protein sequences with associated stability changes. We first simulated myoglobin evolution in phylogenetic trees with a biophysically realistic approach that accounts for 3D structural information and estimates of changes in stability upon mutation. We then compared evolutionary rates inferred directly from simulation to those estimated using maximum-likelihood (ML) methods. We found that the dN/dS estimated by ML methods (ωML) is highly predictive of the per gene dN/dS inferred from the simulated phylogenetic trees. This agreement is strong in the regime of high stability where protein evolution is neutral. At low folding stabilities and under mutation-selection balance, we observe deviations from neutrality (per gene dN/dS > 1 and dN/dS < 1). We showed that although per gene dN/dS is robust to these deviations, ML tests for positive selection detect statistically significant per site dN/dS > 1. Altogether, we show how protein biophysics affects the dN/dS estimations and its subsequent interpretation. These results are important for improving the current approaches for detecting positive selection. [ABSTRACT FROM AUTHOR]

Ecological models built on phenomenological relationships and behavior of the past may not be robust under novel conditions of the future because global changes are producing environmental conditions that forests have not experienced historically. We developed a new succession extension for the LANDIS-II forest landscape model, PnET-Succession, to simulate forest growth and succession using physiological first principles. PnET-Succession integrates the tree physiology model PnET-II with the existing LANDIS-II Biomass Succession extension. PnET-Succession simulates the competition of tree species cohorts for water and light as a function of photosynthetic processes driven by foliar nitrogen. Competition for water is simulated on each grid cell through a dynamic soil-water balance that receives precipitation and loses water through runoff, consumption in photosynthesis, and evapotranspiration. Competition for light is modeled by tracking solar radiation through canopy layers according to a standard Beer-Lambert formula. PnET-Succession requires average monthly photosynthetically active radiation, atmospheric CO2 concentration, temperature and precipitation as inputs. The new extension also dynamically calculates species establishment probabilities in each time step as a function of water and radiation stress. We calibrated PnET-Succession to biomass and LAI measurements from the Duke Experimental Forest in North Carolina (USA) and tested the calibrated model against data from the Green Ridge State Forest in Maryland. The new extension shows considerable promise for studying forest response to climate change, including changes in carbon stocks. [ABSTRACT FROM AUTHOR]

In the analysis of spatial point patterns, an important role is played by statistical tests based on simulation envelopes, such as the envelope of simulations of Ripley's K function. Recent ecological literature has correctly pointed out a common error in the interpretation of simulation envelopes. However, this has led to a widespread belief that the tests themselves are invalid. On the contrary, envelope-based statistical tests are correct statistical procedures, under appropriate conditions. In this paper, we explain the principles of Monte Carlo tests and their correct interpretation, canvas the benefits of graphical procedures, measure the statistical performance of several popular tests, and make practical recommendations. There are several caveats including the under-recognized problem that Monte Carlo tests of goodness of fit are probably conservative if the model parameters have to be estimated from data. Finally, we discuss whether graphs of simulation envelopes can be used to infer the scale of spatial interaction. [ABSTRACT FROM AUTHOR]

In the University we must the young people in the expansion of the awareness, which is recognized in the language of nature, developing the sensitivity in the sounds of the wind, the sea, the jungles and the woods. This expansive awareness faces the values of the power, the expansion, the control and the accumulation of capital, with its double reference: war, sacrifice, death and hopelessness. These values outlined the behavior of the mayan societies in the eclipse of its splendor. In recent times, we have built epistemological rationality concerning the phenomena and we organize the results of the scientific research in oral and written speeches, nevertheless, the threat of climatic change, the environmental crisis and the pollution of water, such as in the cenote, is not a tributary custom to the gods and their plans anymore, while it is a daily, purposeless practice, it becomes in the unconscious joy that other suffer, of those who are still part of the stones and the woods, the seas and the infinite. [ABSTRACT FROM AUTHOR]

Ecological sites are the basic entity used in rangeland health assessment. This study evaluates the synergistic use of multi- and hyper-spectral satellite imagery for sub-pixel classification of ecological sites in semiarid rangelands. Hyperion and Landsat enhanced thematic mapper (ETM) data are included in a two-step procedure to mapping ecological sites in Patagonian rangelands of Argentina. Firstly, mixture tuned matched filtering and logistic regression analyses are used for Hyperion data processing to obtain ecological site probability images in the area covered by hyperspectral imagery. Secondly, artificial neural networks are applied to model the relationships between the spectral response patterns of Landsat and the probability images from Hyperion, and used to map ecological sites over the entire study area. Overall classification accuracy was 81% (kappa = 0.77) with relatively high accuracies for all ecological sites demonstrating that their spectral signatures are sufficiently distinct to be detectable. Better accuracies were obtained for shrub steppes with desert pavement (producer's and user's accuracies of 89% and 84%, respectively), and shrub-grass steppes associated to tertiary calcareous outcrops (producer's and user's accuracies of 100% and 86%, respectively), while poorer accuracies resulted for shrub-grass steppes on old alluvial plains (producer's and user's accuracies of 75% and 56%, respectively). Fuzzy maps of ecological sites as presented in this research can provide rangeland managers with a tool to stratify the landscape and organize ecological information for rangeland health assessment and monitoring, prioritizing and selecting appropriate management actions, and promoting the recovery of areas degraded in these environments. [ABSTRACT FROM AUTHOR]

Available measures of nestedness consider descriptor variables (e.g. species) as equally associated, ignoring evolutionary or ecological dissimilarities. Here, we introduce tree NODF, a new class of nestedness that takes into account the resemblance of descriptor variables., The method is an extension of the NODF index and can be applied to systems in which the resemblance of descriptor variables is described by a tree-like object. Computation of tree NODF is similar to NODF, but uses branch lengths instead of the sum of species occurrences. In this way, we can calculate a phylo NODF for metacommunities if a phylogeny is used to account for differences in phylogenetic diversity ( PD) and trait NODF if a functional dendrogram constructed from species ecological traits is used to account for the functional diversity ( FD) of communities. Similar to NODF, tree NODF can also be used to assess nestedness among species. In this case, env NODF uses a dendrogram describing the resemblance among the environmental conditions of different sites, to test whether rare species occur in a subset of the environmental conditions in the habitats occupied by frequent species., tree NODF is a composite metric that can be additively partitioned into compositional (S.fraction) and tree-topology (topo NODF = tree NODF - S.fraction) components of the descriptor variables. Tests of tree NODF and its components can be carried out using null models and, if a hypothetical factor is used to order metacommunity data, permutation tests. We show that tree NODF is robust for matrix size and fill, as well as for tree topology., Finally, we illustrate the use of tree NODF by analysing data on Caribbean bats using phylo NODF, trait NODF and env NODF, as well as their composition and tree-topology components. [ABSTRACT FROM AUTHOR]

Highlights: [•] Explores individual behavioral differences in plant–pollinator interactions. [•] Reveals behavioral differences for real bees’ complex color decision-making. [•] Bee/flower model reveals conditions where specific decision strategies are superior. [•] Model reveals conditions that could have led to evolution of intra-colony variety. [Copyright &y& Elsevier]

While niche-based processes have been invoked extensively to explain the structure of interaction networks, recent studies propose that neutrality could also be of great importance. Under the neutral hypothesis, network structure would simply emerge from random encounters between individuals and thus would be directly linked to species abundance. We investigated the impact of species abundance distributions on qualitative and quantitative metrics of 113 host-parasite networks. We analyzed the concordance between neutral expectations and empirical observations at interaction, species, and network levels. We found that species abundance accurately predicts network metrics at all levels. Despite host-parasite systems being constrained by physiology and immunology, our results suggest that neutrality could also explain, at least partially, their structure. We hypothesize that trait matching would determine potential interactions between species, while abundance would determine their realization. [ABSTRACT FROM AUTHOR]

Many ecological systems can be represented as networks of interactions. A key feature in these networks is their organization into modules, which are subsets of tightly connected elements. We introduce MODULAR to perform rapid and autonomous calculation of modularity in network sets. MODULAR reads a set of files representing unipartite or bipartite networks, and identifies modules using two different modularity metrics widely used in the ecological networks literature. To estimate modularity, the software offers five optimization methods to the user. The software also includes two null models commonly used in studies of ecological networks to verify how the degree of modularity differs from two distinct theoretical benchmarks. [ABSTRACT FROM AUTHOR]

Pulsing is prevalent in nature. As resource pulse has been recognized as one of the major factors influencing ecosystem structures and processes, it is important to investigate why nature pulses and what benefits an ecosystem obtains from pulsed resources. The main question of this study was that if a system could be exposed to either constant external resources or pulsed external resources of the same temporal average intensity, which resources would maximize power acquisition of a system. To answer the question, this study tested how matching of pulsed resources affects total empower acquisition of a system using numerical simulation models and a refined dynamic emergy accounting method. A producer–consumer model system was built and simulated by varying phases and frequencies of pulsed energy sources. It was hypothesized that matching of frequency and phase among two or more pulsed energy sources increases the empower acquisition of a system, compared with a system under constant energy sources. The simulation results showed that in systems of two energy sources, matching phases and frequencies of the pulsed energy sources involved in primary production is critical to increase total empower acquisition and consumer energy storage. The primary mechanism was that the matching of pulsed resources in phase and frequency promotes energy acquisition of primary producers that is further efficiently transferred for the production of consumers. Energy acquisition of consumers was strongly correlated with total empower acquisition of the system presumably because the consumers are in the high energy hierarchical position controlling the producers thus contributing to the total empower acquisition through the system. [Copyright &y& Elsevier]

One of the main applications of balance indices is in tests of null models of evolutionary processes. The knowledge of an exact formula for a statistic of a balance index, holding for any number $$n$$ of leaves, is necessary in order to use this statistic in tests of this kind involving trees of any size. In this paper we obtain exact formulas for the variance under the Yule model of the Sackin, the Colless and the total cophenetic indices of binary rooted phylogenetic trees with $$n$$ leaves. [ABSTRACT FROM AUTHOR]

Highlights: [•] We run the Morris sensitivity-analysis method to the Pasture Simulation model. [•] Both uniform and normal distributions are employed to 28 vegetation parameters. [•] Sensitivity of nine outputs is examined at seven grassland sites in Europe. [•] Nine influential parameters are identified for model calibration. [•] We study the plasticity of the model with climate conditions. [Copyright &y& Elsevier]

Highlights: [•] An ecological model focusing on the dynamic of phosphorus cycling was developed for Lake Chaohu. [•] Six restoration strategies for Lake Chaohu were predicted by this model in long-term simulation. [•] Structural dynamic approach was introduced into the algae – submerged vegetation transition. [•] Response of SDMs to different intensity in changes of forcing function was tested. [•] SDMs with different parameter sets included were conducted and the results were compared. [Copyright &y& Elsevier]

Highlights: [•] Flexsem is a modular, fast and user friendly framework for 3D modelling in estuaries. [•] User defined equations and unstructured computational mesh make it very flexible. [•] Simplified hydrodynamics provides realistic solutions for estuarine systems. [•] Flexsem is highly suitable for important questions related to coastal management. [Copyright &y& Elsevier]

Question Is the strength of phylogenetic trait conservatism in the species pool reflected in the ability of α- and β-scale phylogenetic diversity indicators to detect niche-based assembly processes along stress gradients? Methods We used a simple community assembly model to explore the power of indicators of phylogenetic community structure to detect assembly processes. The model assumes that with declining stress the influence of niche complementarity on species fitness increases, while that of environmental filtering decreases. We separately incorporated two trait-independent stochastic processes - mass and priority effects - in simulating species occurrences and abundances along a hypothetical stress gradient. We measured power for α- and β-scale indices of phylogenetic diversity ( PD) as the proportion of simulations yielding a significant correlation between these indices and the community position along the stress gradient. For α-scale indices, we ran simulations where species richness was constant along the gradient, or either increased, decreased or varied randomly with declining stress. We used four models of trait evolution, differing in the degree of phylogenetic trait conservatism, to examine how variation in the influence of phylogeny on trait variation impacted the power of PD indices. Results None of the PD indices gave high power to detect assembly processes for either the mass effects or priority effects model, even when trait variation was strongly conserved. Those measures of α PD that gave moderate power in the priority-effects model with strong trait conservatism were greatly affected by variation in species richness. Consequently, none of the indices examined met the necessary selection criteria. Additional analyses revealed that trait conservatism at the species pool level was poorly maintained at the meta-community scale, with phylogenetically-determined species composition having only moderate power to detect functionally-determined species turnover. This lack of a strong phylogenetic signal in trait variation at the meta-community scale is the most likely explanation for the poor ability of PD indices to detect assembly processes in our study. Conclusion Phylogenetic diversity indices seem to have limited ability to detect trait-based assembly processes along ecological gradients, even when trait conservatism at the species pool level is strong. Consequently, PD is unlikely to provide a means of avoiding the tough decisions around which traits are most relevant for assembly processes. Rather, our findings emphasize the need to collect relevant functional trait data to understand the mechanisms controlling community assembly. [ABSTRACT FROM AUTHOR]