The derivation of species response curves with Gaussian logistic regression is sensitive to sampling intensity and curve characteristics

We investigated quantitatively the sensitivity of plant species response curves to sampling characteristics (number of plots, occurrence and frequency of species), along a simulated pH gradient. We defined 54 theoretical unimodal response curves, issued from combinations of six values for optimum (opt = 3, 4, …, 8), three values for tolerance (tol = 0.5, 1.0, and 1.5, sensu ter Braak and Looman [ter Braak, C.J.F., Looman, C.W.N., 1986. Weighted averaging, logistic regression and the Gaussian response model. Vegetatio 65, 3–11]), and three values for maximum probability of presence (p_max = 0.05, 0.20, and 0.50). For each of these 54 theoretical response curves, we built artificial binary data sets (presence/absence) to test the influence of species occurrence, frequency, or number of available plots. With real data extracted from EcoPlant, a phytoecological database for French forests [Gégout, J.-C., Coudun, Ch., Bailly, G., Jabiol, B., 2005. EcoPlant: a forest sites database linking floristic data with soil characteristics and climatic conditions. J. Veg. Sci. 16, 257–260], we compared the ecological response of 50 plant species to soil pH, based first on a small data set (100 randomly sampled plots), and then based on the whole data set available (3810 plots).     

Comments on optimizing the selection of the number of groups in a classification tree

In a recent issue of this journal Guidi et al. (2009) proposed a Random Simulation Test (RST) to assist with the determination of the optimal number of clusters to be extracted from a hierarchical classification tree. This short note illustrates the potential influence that the richness of a simulated new site has on the determination of the optimal level to cut the dendrogram. This is discussed in the context of the need for clear objectives and criteria against which a classification tree can be evaluated. A simple modification of the RST is proposed that the simulated new site of the matrix has an appropriate number of positive entries that lies within the range of the observed matrix. The impact of this modification is then evaluated using an ecological community site-by-species matrix.     

Are savannas patch-dynamic systems? A landscape model

Savannas are ecosystems characterized by the coexistence of woody species (trees and bushes) and grasses. Given that savanna characteristics are mainly formed from competition, herbivory, fire, woodcutting, and patchy soil and precipitation characteristics, we propose a spatially explicit model to examine the effects of the above-mentioned parameters on savanna vegetation dynamics in space and time. Furthermore, we investigate the effects of the above-mentioned parameters on tree–bush–grass ratios, as well as the degrees of aggregation of tree–bush–grass biomass. We parameterized our model for an arid savanna with shallow soil depth as well as a mesic one with generally deeper and more variable soil depths. Our model was able to reproduce savanna vegetation characteristics for periods of time over 2000 years with daily updated time steps. According to our results, tree biomass was higher than bush biomass in the arid savanna but bush biomass exceeded tree and grass biomass in the simulated mesic savanna. Woody biomass increased in our simulations when the soil's porosity values were increased (mesic savanna), in combination with higher precipitation. Savanna vegetation varied from open savanna to woodland and back to open savanna again. Vegetation cycles varied over ∼300-year cycles in the arid and ∼220-year cycles in the mesic-simulated savanna. Autocorrelation values indicated that there are both temporal and spatial vegetation cycles. Our model indicated cycling savanna vegetation at the landscape scale, cycles in cells, and patchiness, i.e. patch dynamics.     

Traditional occupancy–abundance models are inadequate for zero-inflated ecological count data

Traditional occupancy–abundance and abundance–variance–occupancy models do not take into account zero-inflation, which occurs when sampling rare species or in correlated counts arising from repeated measures. In this paper we propose a novel approach extending occupancy–abundance relationships to zero-inflated count data. This approach involves three steps: (1) selecting distributional assumptions and parsimonious models for the count data, (2) estimating abundance, occupancy and variance parameters as functions of site- and/or time-specific covariates, and (3) modelling the occupancy–abundance relationship using the parameters estimated in step 2. Five count datasets were used for comparing standard Poisson and negative binomial distribution (NBD) occupancy–abundance models. Zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) occupancy–abundance models were introduced for the first time, and these were compared with the Poisson, NBD, He and Gaston's and Wilson and Room's abundance–variance–occupancy models. The percentage of zero counts ranged from 45 to 80% in the datasets analysed. For most of the datasets, the ZINB occupancy–abundance model performed better than the traditional Poisson, NBD and Wilson and Room's model. He and Gaston's model performed better than the ZINB in two out of the five datasets. However, the occupancy predicted by all models increased faster than the observed as density increased resulting in significant mismatch at the highest densities. Limitations of the various models are discussed, and the need for careful choice of count distributions and predictors in estimating abundance and occupancy parameter are indicated.     

The dynamics of shifting cultivation captured in an extended Constrained Cellular Automata land use model

This paper presents an extension to the Constrained Cellular Automata (CCA) land use model of White et al. [White, R., Engelen, G., Uljee, I., 1997. The use of constrained cellular automata for high-resolution modelling of urban land-use dynamics. Environment and Planning B: Planning and Design 24(3), 323–343] to make it better suited for modelling the dynamics of shifting cultivation. In the extended model the time passed since the last land use transition of a location is a factor of its land use potential. The model can now account for the gradual decrease in soil fertility after an area of forest has been cleared for cultivation and also capture the process of regeneration once the plot is fallowed. The model is applied for the Ruhunupura area of Sri Lanka where chena, a particular practice of shifting cultivation, is a common land use that dominates the landscape dynamics. The model is calibrated for the period 1985–2001 and the results are assessed in terms of location to location overlap as well as structural similarity at multiple scales. These results give confidence in the representation of land use dynamics for the main land use classes. On the basis of a long term scenario run for the period 2001–2030, it is verified that the model captures stylized facts related to chena dynamics, in particular shortening fallow periods and increasingly long cultivation periods of chena, as a result of increasing land use pressure.     

Comparison of exergy found by a classical thermodynamic approach and by the use of the information stored in the genome

It is possible to calculate the exergy for organisms based on classic thermodynamics as already demonstrated by Mejer and Jorgensen [Mejer, H., Jorgensen, S.E., 1979. Exergy and ecological buffer capacity. State-of-the-art in Ecol. Model. 7, 829–846]. The calculation of exergy as eco-exergy, which is based on the information stored in the genome, has lately been proposed by Jørgensen and co-workers. Recently, Ludovisi [Ludovisi, A., 2009. Exergy vs information in ecological successions: interpreting community changes by a classical thermodynamic approach. Ecol. Model. 220, 1566–1577] has put forward a method based on classical thermodynamics, which leads to the calculation of “virtual” values of concentration at equilibrium for a number of organic compounds (VEC) and freshwater organisms (VECE). This paper compares the two approaches by analysing the correlation existing between the VECE- and the β-values derived by Jørgensen et al. [Jørgensen, S.E., Ladegaard, N., Debeljak, M., Marques, J.C., 2005. Calculations of exergy for organisms. Ecol. Model. 185, 165–175]. It was found that there was a good correlation, which can be useful for estimating β-values for organisms whose genome is not known in a sufficient detail. The relationship between VECE- and β-values suggests that two proposed thermodynamic orientors based on these quantities – the eco-exergy index and the structural information – should lead to coherent results when applied to the evaluation of the development state of ecosystems. A numerical simulation shows that this expectation is verified in a major case, but also that different, even opposite, responses can arise, depending on the biological composition of the biocoenosis investigated.     

Impact of climate change on soil moisture dynamics in Brandenburg with a focus on nature conservation areas

Global warming impacts the water cycle not only by changing regional precipitation levels and temporal variability, but also by affecting water flows and soil moisture dynamics. In Brandenburg, increasing average annual temperature and decreasing precipitation in summer have already been observed. For this study, past trends and future effects of climate change on soil moisture dynamics in Brandenburg were investigated, considering regional and specific spatial impacts. Special Areas of Conservation (SACs) were focused on in particular. A decreasing trend in soil water content was shown for the past by analyzing simulation results from 1951 to 2003 using the integrated ecohydrological model SWIM [Krysanova, V., Müller-Wohlfeil, D.-I., Becker, A., 1998. Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds. Ecol. Model. 106, 261–289]. The trend was statistically significant for some areas, but not for the entire region. Simulated soil water content was particularly low in the extremely dry year 2003. Comparisons of simulated trends in soil moisture dynamics with trends in the average annual Palmer Drought Severity Index for the region showed largely congruent patterns, though the modeled soil moisture trends are characterized by a much higher spatial resolution. Regionally downscaled climate change projections representing the range between wetter and drier realizations were used to evaluate future trends of available soil water. A further decrease of average available soil water ranging from −4% to −15% was projected for all climate realizations up to the middle of the 21st century. An average decrease of more than 25 mm was simulated for 34% of the total area in the dry realization. Available soil water contents in SACs were generally higher and trends in soil moisture dynamics were lower mainly due to their favorable edaphic conditions. Stronger absolute and relative changes in the simulated trends for the past and future were shown for SACs within Brandenburg than for the state as a whole, indicating a high level of risk for many wetland areas. Nonetheless, soil water content in SACs is expected to remain higher than average under climate change conditions as well, and SACs therefore have an important buffer function under the projected climate change. They are thus essential for local climate and water regulation and their status as protected areas in Brandenburg should be preserved.     

Modification of an ecosystem model for filling medium-sized gaps in tower-based estimates of net ecosystem productivity

Gap filling of flux data is necessary to assist with periodic interruptions in the measurement data stream. The gap-filling model (GFM), first described in Xing et al. [Xing, Z., Bourque, C.P.-A., Meng, F.-R., Zha, T.-S., Cox, R.M., Swift, E., 2007. A simple net ecosystem productivity model for gap filling of tower-based fluxes: an extension of Landsberg's equation with modifications to the light interception term. Ecol. Model. 206, 250–262], was modified to account for the day-to-day control of net ecosystem productivity (NEP) by incorporating air and soil temperature as new controlling variables in the calculation of NEP. To account for the multiple-phase influences of air and soil temperature on plant growth we model ecosystem respiration as a function of soil and canopy respiration. The paper presents model development in an incremental fashion in order to quantify the contribution of individual model enhancements to the prediction of NEP during periods when air and soil temperature variations are important.     

Local likelihood disease clustering: development and evaluation

This paper illustrates a method based on local likelihood (LL) for detecting disease clusters. The approach is based on estimating a lasso distance for each region: within which regions are considered to be clustered. An important advantage in implementing this approach is that it does not require any special Monte Carlo Markov Chain (MCMC) algorithm, e.g., reversible jump MCMC, which is essential in hidden Markov model approach. Another advantage is that extending the model to incorporate covariates is straightforward. We illustrate three ways of doing this by using Eastern Germany lip cancer data. By using simulated data, we have made a comparison with the BYM model [Besag et al. (1991) Annals of the Institute of Statistical Mathematics, 43, 1–59] and the mixture model [Lawson and Clark (2002) Disease Mapping and Risk Assessment for Public Health, Chapman and Hall]. We also did a limited examination of the ability of the LL model to recover true relative risk under different priors for lasso parameter. In order to check the edge effects, which has been overlooked in many spatial clustering models for disease mapping but deserves special attention as it lacks observable neighbors, we have adapted here a simple approach to observe the changes in relative risks when the edge regions are omitted. An erratum to this article is available at .     

The growth response of a model Gymnodinium splendens in stationary and wavy water columns

A computer model is used to investigate the simulated growth of a theoretical dinoflagellate resembling Gymnodinium splendens in response to a variety of field conditions. Literature data on G. splendens are combined with probable estimates of organism response (where direct data are lacking) to yield light-and temperature-dependent production curves. These production curves are superimposed on a physical model characterized by a diurnally variable light cycle, by a two-layered water column (16°C water overlaying 12°C water) of variable layer thicknesses, and by variable extinction coefficients in the upper layer. The water column is either stationary or perturbed by a semidiurnal (12.4 h) internal wave. Organism behavior ranges from the continuous occupation of selected strata (stationary or wavy) to diurnal vertical migrations within the upper layer or across the thermocline. In stationary water columns, species patchiness depends on spatial differences in the depth preferences of nonmigrating organisms or in the details of the behavior of migrating organisms. In water columns perturbed by a semidiurnal internal wave, spatial differences in the phase relationship between the wave form and daylight supplement organism behavior as a source of patchiness. The models result in their most complex spatial patterns when a population migrates through a thermocline perturbed by a semidiurnal internal wave.University of Texas Marine Science Institute Contribution No. 280.     

Structural changes in lake functioning induced from nutrient loading and climate variability

Climate variability is increasingly recognized as an important regulatory factor, capable of influencing the structural properties of aquatic ecosystems. Lakes appear to be particularly sensitive to the ecological impacts of climate variability, and several long time series have shown a close coupling between climate, lake thermal properties and individual organism physiology, population abundance, community structure, and food web dynamics. Thus, understanding the complex interplay among meteorological forcing, hydrological variability, and ecosystem functioning is essential for improving the credibility of model-based water resources/fisheries management. Our objective herein is to examine the relative importance of the ecological mechanisms underlying plankton seasonal variability in Lake Washington, Washington State (USA), over a 35-year period (1964–1998). Our analysis is founded upon an intermediate complexity plankton model that is used to reproduce the limiting nutrient (phosphate)–phytoplankton–zooplankton–detritus (particulate phosphorus) dynamics in the lake. Model parameterization is based on a Bayesian calibration scheme that offers insights into the degree of information the data contain about model inputs and allows obtaining predictions along with uncertainty bounds for modeled output variables. The model accurately reproduces the key seasonal planktonic patterns in Lake Washington and provides realistic estimates of predictive uncertainty for water quality variables of environmental management interest. A principal component analysis of the annual estimates of the underlying ecological processes highlighted the significant role of the phosphorus recycling stemming from the zooplankton excretion on the planktonic food web variability. We also identified a moderately significant signature of the local climatic conditions (air temperature) on phytoplankton growth (r = 0.41), herbivorous grazing (r = 0.38), and detritus mineralization (r = 0.39). Our study seeks linkages with the conceptual food web model proposed by Hampton et al. [Hampton, S.E., Scheuerell, M.D., Schindler, D.E., 2006b. Coalescence in the Lake Washington story: interaction strengths in a planktonic food web. Limnol. Oceanogr. 51, 2042–2051.] to emphasize the “bottom-up” control of the Lake Washington plankton phenology. The posterior predictive distributions of the plankton model are also used to assess the exceedance frequency and confidence of compliance with total phosphorus (15 μg L⁻¹) and chlorophyll a (4 μg L⁻¹) threshold levels during the summer-stratified period in Lake Washington. Finally, we conclude by underscoring the importance of explicitly acknowledging the uncertainty in ecological forecasts to the management of freshwater ecosystems under a changing global environment.     

Urban expansion and its contribution to the regional carbon emissions: Using the model based on the population density distribution

The method is used for calculating regional urban area dynamics and the resulting carbon emissions (from the land-conversion) for the period of 1980 till 2050 for the eight world regions. This approach is based on the fact that the spatial distribution of population density is close to the two-parametric Γ-distribution [Kendall, M.G., Stuart, A., 1958. The Advanced Theory of Statistics, vol. 1.2. Academic Press, New York; Vaughn, R., 1987. Urban Spatial Traffic Patterns, Pion, London]. The developed model provides us with the scenario of urbanisation, based on which the regional and world dynamics of carbon emissions and export from cities, and the annual total urban carbon balance are estimated. According to our estimations, world annual emissions of carbon as a result of urbanisation increase up to 1.25 GtC in 2005 and begin to decrease afterwards. If we compare the emission maximum with the annual emission caused by deforestation, 1.36 GtC per year, then we can say that the role of urbanised territories (UT) in the global carbon balance is of a comparable magnitude. Regarding the world annual export of carbon from UT, we observe its monotonous growth by three times, reaching 505 MtC. The latter, is comparable to the amount of carbon transported by rivers into the ocean (196–537 MtC). The current model shows that urbanisation is inhibited in the interval 2020–2030, and by 2050 the growth of urbanised areas would almost stop. Hence, the total balance, being almost constant until 2000, then starts to decrease at an almost constant rate. By the end of the XXI century, the total carbon balance will be equal to zero, with the exchange flows fully balanced, and may even be negative, with the system beginning to take up carbon from the atmosphere, i.e., becomes a “sink”. The regional dynamics is somewhat more complex, i.e., some regions, like China, Asia and Pacific are being active sources of Carbon through the studied period, while others are changing from source to sink or continue to be neutral in respect the GCC.     

Role of standard incidence in an eco-epidemiological system: A mathematical study

Ecology and epidemiology are two major fields of study in their own right, but they have some common features. [Chattopadhyay, J., Pal, S., El Abdllaoui, A., 2003. Classical predator–prey system with infection of prey population—a mathematical model. Math. Meth. Appl. Sci. 26, 1211–1222] considered a predator–prey model with disease in the prey population. They analyzed the system based on the assumption that horizontal incidence follows simple mass action incidence. Mass action incidence is appropriate for a constant population, but for a large population, standard incidence is more appropriate. The complicated dynamics around (0, 0, 0) arise because of standard incidence. The conditions under which the population reaches the origin either by following the axis or in a spiral pattern were determined. Numerical experiments were performed to observe the dynamics of the system with mass action incidence and standard incidence. This investigation showed that the infection rate plays a crucial role for predicting the behavior of the dynamics in the long run.     

Space-time Bayesian small area disease risk models: development and evaluation with a focus on cluster detection

This paper extends the spatial local-likelihood model and the spatial mixture model to the space-time (ST) domain. For comparison, a standard random effect space-time (SREST) model is examined to allow evaluation of each model’s ability in relation to cluster detection. To pursue this evaluation, we use the ST counterparts of spatial cluster detection diagnostics. The proposed criteria are based on posterior estimates (e.g., misclassification rate) and some are based on post-hoc analysis of posterior samples (e.g., exceedance probability). In addition, we examine more conventional model fit criteria including mean square error (MSE). We illustrate the methodology with a real ST dataset, Georgia throat cancer mortality data for the years 1994–2005, and a simulated dataset where different levels and shapes of clusters are embedded. Overall, it is found that conventional SREST models fair well in ST cluster detection and in goodness-of-fit, while for extreme risk detection the local likelihood ST model does best.     

Role of competition in phytoplankton population for the occurrence and control of plankton bloom in the presence of environmental fluctuations

Termination of harmful algal blooms (HABs) and coexistence of phytoplankton–zooplankton populations are of great importance to human health, ecosystem, environment, tourism and fisheries. In this paper, we propose a three component model consisting of non-toxic phytoplankton (NTP), toxin producing phytoplankton (TPP) and zooplankton (Z). The growth of zooplankton species is assume to reduce due to toxic chemicals released by TPP population. We have extended the model proposed by Chattopadhyay et al. [Chattopadhyay, J., Sarkar, R.R., Pal, S., 2004. Mathematical modelling of harmful algal blooms supported by experimental findings. Ecol. Comp. 1, 225–235] by including competition terms between TPP and NTP. We observe the effect of competition factors both in the presence and absence of the environmental fluctuation. From our field as well as model analysis we observe that competition helps in the coexistence of the species, but if the effect of competition is very high on the TPP population, it results in planktonic bloom. It is shown that the coexistence equilibrium loses its stability when the competition coefficient crosses a critical value and resulting Hopf-bifurcation around the positive equilibrium depicting oscillations phenomena of the populations.     

A resource-based approach to modelling the dynamics of interacting populations

The procedure for modelling the growth of single-species populations [Sakanoue, S., 2007. Extended logistic model for growth of single-species populations. Ecol. Model. 205, 159–168] is improved to be applicable to the study of the dynamics of interacting populations. The improved procedure is based on three assumptions: resource availability changes with population size as a variable, resource supply to populations and population demand for resources are defined as functions of resource availability and population size, and the variables of resource availability and population size shift in the supply function attracted to the demand function. These assumptions are organized into three equations. The equations can generate the dynamics models of plant, herbivore, and detritivore populations, and their own resources. The models can be used to describe prey–predator dynamics. They naturally contain nonlinear terms for the predator’s numerical and functional responses. Depending on the terms, the fluctuations in resource availability and population size stabilize. The three equations can also generate the dynamics models of different populations consuming the same resources. The analysis of zero isoclines of the models shows that a superior population can be simply defined as one with a higher intrinsic rate of natural increase, that a stable coexistence may be realized with the intraspecific interference or the interspecific facilitation of superiors, and that the interspecific interference or the intraspecific facilitation of inferiors may make the coexistence unstable and the inferiors winners depending on their initial population size.     

Zooplankton population model coupled to a biogeochemical model of the North Western Mediterranean Sea ecosystem

A stage structured population (SSP) model based on Fennel's [Fennel, W., 2001. Modelling copepods with links to circulation models. Journal of Plankton Research, 23, 1217–1232] equations is applied to Centropages typicus (Kröyer), a dominant copepod species of the North Western Mediterranean Sea (NWMS) and a prey of small pelagic fish. The model considers five groups of stages and development rates are represented by a mechanistic formulation depending on individual specific growth in each stage. Individual growth is calculated from the individual energy budget depending on food availability and temperature.     

Divergence in sink contributions to population persistence

Population sinks present unique conservation challenges. The loss of individuals in sinks can compromise persistence; but conversely, sinks can improve viability by improving connectivity and facilitating the recolonization of vacant sources. To assess the contribution of sinks to regional population persistence of declining populations, we simulated source–sink dynamics for 3 very different endangered species: Black‐capped Vireos (Vireo atricapilla) at Fort Hood, Texas, Ord's kangaroo rats (Dipodomys ordii) in Alberta, and Northern Spotted Owls (Strix occidentalis caurina) in the northwestern United States. We used empirical data from these case studies to parameterize spatially explicit individual‐based models. We then used the models to quantify population abundance and persistence with and without long‐term sinks. The contributions of sink habitats varied widely. Sinks were detrimental, particularly when they functioned as strong sinks with few emigrants in declining populations (e.g., Alberta's Ord's kangaroo rat) and benign in robust populations (e.g., Black‐capped Vireos) when Brown‐headed Cowbird (Molothrus ater) parasitism was controlled. Sinks, including ecological traps, were also crucial in delaying declines when there were few sources (e.g., in Black‐capped Vireo populations with no Cowbird control). Sink contributions were also nuanced. For example, sinks that supported large, variable populations were subject to greater extinction risk (e.g., Northern Spotted Owls). In each of our case studies, new context‐dependent sinks emerged, underscoring the dynamic nature of sources and sinks and the need for frequent re‐assessment. Our results imply that management actions based on assumptions that sink habitats are generally harmful or helpful risk undermining conservation efforts for declining populations.