Simulating soil organic matter with CQESTR (v. 2.0): Model description and validation against long-term experiments across North America

Soil carbon (C) models are important tools for examining complex interactions between climate, crop and soil management practices, and to evaluate the long-term effects of management practices on C-storage potential in soils. CQESTR is a process-based carbon balance model that relates crop residue additions and crop and soil management to soil organic matter (SOM) accretion or loss. This model was developed for national use in U.S and calibrated initially in the Pacific Northwest. Our objectives were: (i) to revise the model, making it more applicable for wider geographic areas including potential international application, by modifying the thermal effect and incorporating soil texture and drainage effects, and (ii) to recalibrate and validate it for an extended range of soil properties and climate conditions. The current version of CQESTR (v. 2.0) is presented with the algorithms necessary to simulate SOM at field scale. Input data for SOM calculation include crop rotation, aboveground and belowground biomass additions, tillage, weather, and the nitrogen content of crop residues and any organic amendments. The model was validated with long-term data from across North America. Regression analysis of 306 pairs of predicted and measured SOM data under diverse climate, soil texture and drainage classes, and agronomic practices at 13 agricultural sites having a range of SOM (7.3–57.9 g SOM kg⁻¹), resulted in a linear relationship with an r² of 0.95 (P < 0.0001) and a 95% confidence interval of 4.3 g SOM kg⁻¹. Using the same data the version 1.0 of CQESTR had an r² of 0.71 with a 95% confidence interval of 5.5 g SOM kg⁻¹. The model can be used as a tool to predict and evaluate SOM changes from various management practices and offers the potential to estimate C accretion required for C credits.     

Relative density of finds for assessing similarity-based maps of orchid occurrence

Similarity-based mapping of the expected distribution of 10 orchid species was conducted in a study area covering 300 km² in south-eastern Estonia. The observation track and species finds were recorded during fieldwork. Absence locations were generated on the line of observation track. Both presence and absence sites having an in-between distance of at least 100 m were used as training data. Expected presence/absence of a species was calculated according to similarity between the predictable location and selected observations (examples) of presence and absence sites. For each species, the machine learning system identified the best predictive sets by selecting the most useful variables out of 136 map and remote sensing features. Similarity-based estimations were evaluated both by training fit and by independent verification data. Reliability of the predictive maps was expressed also by usefulness ratios—the densities of validation find sites (1) in the predicted presence area relative to the density of those in the predicted absence area, and (2) relative to the share of the observation track in the predicted presence area and in the predicted absence area. The predictive mapping was most efficient for Dactylorhiza incarnata, D. russowii, Epipactis palustris, and Goodyera repens. We conclude that the profound coverage of observations on any larger area is unrealistic and the reliability of similarity-based predictive maps depends on the representativity of existing records relative to the diversity of the study area. The investigation showed that the studied species are much more common in nature than the records in the national database indicate.     

Modelling habitat overlap among sympatric mesocarnivores in southern Illinois,USA

Few researchers have developed large-scale habitat models for sympatric carnivore species. We created habitat models for red foxes (Vulpes vulpes), coyotes (Canis latrans) and bobcats (Lynx rufus) in southern Illinois, USA, using the Penrose distance statistic, remotely sensed landscape data, and sighting location data within a GIS. Our objectives were to quantify and spatially model potential habitat differences among species. Habitat variables were quantified for 1-km² buffered areas around mesocarnivore sighting locations. Following variable reduction procedures, five habitat variables (percentage of grassland patches, interspersion–juxtaposition of forest patches, mean fractal dimension of wetland patches and the landscape, and road density) were used for analysis. Only one variable differed (P < 0.05) between red fox and coyote sighting areas (road density) and bobcat and coyote sighting areas (mean fractal dimension of the landscape). However, all five variables differed between red fox and bobcat sighting areas, indicating considerable differences in habitat affiliation between this pair-group. Compared to bobcats, red fox sightings were affiliated with more grassland cover and larger grassland patches, higher road densities, lower interspersion and juxtaposition of forest patches, and lower mean fractal dimension of wetland patches. These differences can be explained by different life history requirements relative to specific cover types. We then used the Penrose distance statistic to create habitat models for red foxes and bobcats, respectively, based on the five-variable dataset. An independent set of sighting locations were used to validate these models; model fit was good with 65% of mesocarnivore locations within the top 50% of Penrose distance values. In general, red foxes were affiliated with mixtures of agricultural and grassland cover, whereas bobcats were associated with a combination of grassland, wetland, and forest cover. The greatest habitat overlap between red foxes and bobcats was found at the interface between forested areas and more open cover types. Our study provides insight into habitat overlap among sympatric mesocarnivores, and the distance-based modelling approach we used has numerous applications for modelling wildlife–habitat relationships over large scales.     

Fish assemblage compositions after implementation of the IndVal method on the Narew River system

Indicator species index (IndVal) was used as a new method for an already published study, and allowed of a more convincing way of fish assemblages characterization in a large river system. Three sites clusters (AB, CD, EF) were distinguish using the self-organizing map (SOM, Artificial neural network algorithm) in the lowland Narew River system, which comprised the most characteristic species of the total of 36 present. AB included Pungitius pungitius, Barbatula barbatula, Gasterosteus aculeatus and Gobio gobio (natural and slightly modified sites from small rivers), EF included Leuciscus idus, Perca fluviatilis, Rutilus rutilus, Blicca bjoerkna, Esox lucius, Lota lota and Alburnus alburnus (sites from the main channel and lower courses of biggest tributaries, and CD without characteristic species (containing sites from small and large river ditches impacted by pollution, engineering and both). The IndVal method applied here gives precise and accurate information on fish species habitat preferences.     

Modeling carbon sequestration under zero-tillage at the regional scale. II. The influence of crop rotation and soil type

For policy decisions with respect to CO₂-mitigation measures in the agricultural sector, national and regional estimations of the efficiency of such measures are required. The conversion of ploughed cropland to zero-tillage is discussed as an option to reduce CO₂ emissions and promises at the same time effective soil and water conservation. Based on the upscaling of simulation results with the soil and land resources information system SLISYS-BW, estimations of CO₂-mitigation rates in relation to crop rotations and soil type have been made for the state of Baden-Württemberg (Germany). The results indicate considerable differences in the CO₂-mitigation rates between crop rotations ranging from 0.48 to 0.03 Mg C ha⁻¹ a⁻¹ for winter cereals–spring cereals–rape rotations and winter cereals–spring cereals–corn silage rotations, respectively. The efficiency of the crop rotations is strongly related to the total carbon input and in particular the amount of crop residues. Among the considered soil types, highest CO₂-mitigation rates are associated with Cumulic Anthrosols (0.62 Mg C ha⁻¹ a⁻¹) and the lowest with Gleysols (−0.01 Mg C ha⁻¹ a⁻¹). An agricultural extensification scenario with conventional plowing but conversion of the presently applied intensive crop rotations to a clover–clover–winter cereals rotation indicated a CO₂-mitigation potential of 466 Gg C a⁻¹. However, the present high market prices for cereals and increasing demand for energy production from biomass encourages an intensification of the agricultural production and an excessive removal of biomass which in future will seriously reduce the potential for carbon sequestration on cropland.     

Mapping Soil Lead and Remediation Needs in Contaminated Soils

For the past two decades, the Taiwan Environmental Protection Administration has made a systematic investigation of As, Cd, Cr, Cu, Pb, Hg, Ni and Zn in agricultural soils to identify soil pollution from industrial production. The EPA has cooperated with local governmental agencies to establish a soil quality monitoring system that would upgrade the land recovery ability and prohibit polluted lands from being cultivated or turned over to other uses. Based on an island-wide soil survey, more than 1,000 hectares of arable soils in Taiwan were found to be considerably contaminated by heavy metals. One of the heavy metal contaminated sites, located near a ceramic product manufacturing factory in Nantou County, was identified as lead contaminated. According to the Nantou Environmental Protection Bureau, the lead content in contaminated sites showed a great variation of several mg Pbkg^–1 soil to several thousands mg Pbkg^–1 soil. Therefore, it is appropriate to estimate the lead spatial distribution through geostatistics such as Kriging. The soil lead concentration contour maps obtained by Kriging can help us to identify the pollution patterns and delineate the range of contaminated sites. The purpose of this study is to determine the Pb concentrations at each location by performing detailed soil sampling on those Pb contaminated sites and estimating the lead spatial distributions by Kriging. A total of 70 soils were sampled from different locations at two experiment sites. Lead contents were determined with 0.1M HCl extractable lead content of the soils. The results obtained by investigating the lead contents in each 15cm segment down to a 60cm depth, revealed that lead contents were greater in arable land near the ceramic products manufacturing factory, and lead concentrations decreased with depth. In addition, Pb concentrations in heavily contaminated soils showed heavy concentrations of Pb in specific locations. Results from Pb content spatial distributions indicated that the Kriging model is a useful tool and can provide decision-makers with critical information for delineating hazardous areas in heavy metal contaminated sites.     

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).     

A model of the emergence of infectious pancreatic necrosis virus in Scottish salmon farms 1996–2003

Infectious pancreatic necrosis virus (IPNV) is an increasingly common pathogen in farmed Scottish Atlantic salmon; over 80% of marine sites are now infected, although most do not suffer clinical disease. The increasing prevalence of this pathogen in farms over the period 1996–2003 is modelled using a simple susceptible–infected (SI) epidemic model. Because salmon production approximately doubled over this period, population-dependent and -independent transmission models are compared. The model generates mean R₀ (increase ratio) of 1.41 in fresh and 1.45 in marine water farms at the national level; higher values apply with time under population-dependent transmission (1.58, freshwater, 1.80 marine by 2003). Regional differences in R₀ are mostly moderate, indicating similar regional processes in spite of substantial difference in prevalence. Prevalence of IPNV for marine sites was further increased by the use of smolts (young salmon) from multiple freshwater sources. The model suggests that prevalence is entering dynamic equilibrium and will stabilise or only increase slowly as population increases. Cutting freshwater transmission is the most effective single strategy at reducing IPNV prevalence, but a combination of strategies (including reducing the number of sources of smolts) is better and indeed is required for eradication. Eradication would require cuts in transmission of at least 30–45% and this is unlikely to be practicable.     

A system-dynamic model on the competitive growth between Potamogeton malaianus Miq. and Spirogyra sp.

A system-dynamic model has been built to evaluate the competition between submerged macrophytes Potamogeton malaianus Miq. (PM) and filamentous green algae Spirogyra sp. (SP). The data background is based on a spring–summer and an autumn–winter experiment carried out in artificial field ponds. The experiments had the aim to acquire a knowledge base necessary to a successful restoration of submerged macrophyte vegetation in Lake Taihu, China by use of P. malaianus Miq. The model mainly focuses on variations in water volume; biomass dynamics of P. malaianus Miq., Spirogyra sp. and zoobenthos; nutrients cycling between water column, P. malaianus Miq., Spirogyra sp., zoobenthos, detritus and sediment. Sixteen state variables are included in the model: biomass of P. malaianus Miq., Spirogyra sp. and zoobenthos; nitrogen in sediments, detritus, in P. malaianus Miq., in Spirogyra sp. and zoobenthos; total dissolved nitrogen; phosphorus in sediments, detritus, in P. malaianus Miq., in Spirogyra sp. and in zoobenthos; total dissolved phosphorus, and water volume of the experiment pond. The calibration and validation of the model show a good accordance with the results of the spring–summer experiment and the autumn–winter experiment.     

Environmental Geochemistry of Soils and Waters of Susaki Area, Korinthos, Greece

Soil and water samples were collected from the Susaki area of Korinthos and analysed for heavy metals in order to evaluate their environmental impact. The geology of the studied area includes ultrabasic rocks and Neogene and Quaternary deposits whereas magnesite veins are found within the ultrabasic rocks. In the north part of the studied area post volcanic emissions of H₂S, CO₂ and H₂O vapor continue to the present day. All the samples were analysed for heavy metals by the ICP method. The element ranges (in g g^–1) for soil samples are: Cu 11–63, Pb 5–256, Zn 21–604, Ni 183–2665, Co 12–124, Mn 456–1434, As 5–104, Sr 44–730, V 21–84, Cr 163–2346, Ba 48–218, Zr 3–41, Y 3–13. The metals Pb, Zn, Ni, Co, Cr, Fe, Cu, Mn, As and Sr are enriched in the Susaki soils. The element ranges for water samples are: Cu 65–103ppb, Pb<10ppb, Zn<5ppb, Ni 21–163ppb, Co 2–12ppb, As<30ppb, Cr<20ppb, Ba 36–785ppb, Sb<10ppb, W<10ppb, Bi<30ppb, Mn 0.0–0.9 g g^–1, Fe 0.01–0.22 g g^–1, Na 843–3076 g g^–1, K 98–278 g g^–1, Si 39–65 g g^–1, P 0.1–0.2 g g^–1. There is a natural pollution of soils with elevated concentrations of Ni, Co, Mn, Fe and Cr due to the presence of ultrabasic rocks. Another natural case of As pollution of soils is due to the volcanic activity and the geothermal field in the area. The geochemical data of ground waters and also the ¹⁸, D data showed a mixing in different proportions between sea water and meteoric water.     

The development of a multi-species algal ecodynamic model for urban surface water systems and its application

An ecodynamic model that can simulate four phytoplankton species has been developed to deal with the unique characteristics of urban river systems which has manmade river profile, flow controlled by gates, severe eutrophication status, and fragile aquatic ecosystem. The ecodynamic model was developed referencing two typical models: the water quality simulation model WASP and ecological model CAEDYM. The model can simulate 11 state variables: dissolved oxygen, carbonaceous biochemical oxygen demand, ammonia nitrogen, nitrate nitrogen, organic nitrogen, inorganic phosphorus, organic phosphorus and four phytoplankton species with zooplankton as a boundary condition. The ecodynamic model was applied to Sihai section of the Beijing urban river system, where serious algal blooms broke out in recent years. The dominant phytoplankton species are Cyanophyta, Chlorophyta, Bacillariophyta, and Cryptophyta. Site-specific data on geometry, meteorology, pollution sources, and existing ecosystem parameters were collected and used for model calibration and verification The model results mimic observed trends of water quality and phytoplankton species succession and can be used for forecasting algal blooms as well as assessment of river management measures.     

Optimization of ecosystem model parameters using spatio-temporal soil moisture information

Parameters in process-based terrestrial ecosystem models are often nonlinearly related to the water flux to the atmosphere, and they also change temporally and spatially. Therefore, for estimating soil moisture, process-based terrestrial ecosystem models inevitably need to specify spatially and temporally variant model parameters. This study presents a two-stage data assimilation scheme (TSDA) to spatially and temporally optimize some key parameters of an ecosystem model which are closely related to soil moisture. At the first stage, a simplified ecosystem model, namely the Boreal Ecosystem Productivity Simulator (BEPS), is used to obtain the prior estimation of daily soil moisture. After the spatial distribution of 0–10 cm surface soil moisture is derived from remote sensing, an Ensemble Kalman Filter is used to minimize the difference between the remote sensing model results, through optimizing some model parameters spatially. At the second stage, BEPS is reinitialized using the optimized parameters to provide the updated model predictions of daily soil moisture. TSDA has been applied to an arid and semi-arid area of northwest China, and the performance of the model for estimating daily 0–10 cm soil moisture after parameter optimization was validated using field measurements. Results indicate that the TSDA developed in this study is robust and efficient in both temporal and spatial model parameter optimization. After performing the optimization, the correlation (r²) between model-predicted 0–10 cm soil moisture and field measurement increased from 0.66 to 0.75. It is demonstrated that spatial and temporal optimization of ecosystem model parameters can not only improve the model prediction of daily soil moisture but also help to understand the spatial and temporal variation of some key parameters in an ecosystem model and the corresponding ecological mechanisms controlling the variation.     

Examination of conflicts and improved strategies for the management of an endangered Eucalypt species using Bayesian networks

Bayesian decision support tools are becoming increasingly popular as a modelling framework that can analyse complex problems, resolve controversies, and support future decision-making in an adaptive management framework. This paper introduces a model designed to assist the management of an endangered Eucalypt species, the Swamp Gum (Eucalyptus camphora). This tree species is found in the Yellingbo Nature Conservation Reserve (YNCR), an isolated patch of forest in the Yarra Valley (Victoria, Australia), where E. camphora has become increasingly threatened by dieback. In order to maintain and rehabilitate existing trees and encourage regeneration, management strategies and action plans have concentrated on restoring the hydrological regime, which has been altered due to agricultural activities within the catchment. However, research suggests that nutrient enrichment from surrounding horticulture and livestock is having a greater impact on the health of the trees. A Bayesian network model has been developed for E. camphora and used to explore the differences between these two hypotheses. Model outputs suggest that the influencing factors of E. camphora condition are (a) spatially specific and (b) differ according to the group conducting the study in the YNCR. Given the poor quality of data and knowledge available, further research is required to identify the causal factors of dieback. The model offers a framework to guide future integrative and iterative monitoring and research in the YNCR.     

The effect of migration on the viability,dynamics and structure of two coexisting metapopulations

Two species of butterflies, Euphydryas aurinia and Melitaea phoebe, coexist as two metapopulations in a 38-patch network in Hebei Province, China. A Markovian model, whose transition matrix is the product of two matrices which represent the local extinction and recolonization process respectively, is used to describe the metapopulation dynamics. The application of this model to the metapopulation, consisting of 12 local populations in the northern subregion, shows that the expected life times of E. aurinia and M. phoebe are 160 and 121 years respectively and usually nearly half of the patches are occupied by E. aurinia, while only 1–3 patches are occupied by M. phoebe. We claim that E. aurinia can persist for a long time while M. phoebe faces relatively big extinction risk. By comparing the population dynamics with and without migration, we find M. phoebe benefits much more from migration than E. aurinia. Most patches are occupied mainly by local populations for E. aurinia, while by immigrants from the 8th patch for M. phoebe, meaning that E. aurinia has a classical metapopulation structure while M. phoebe has a source–sink metapopulation structure.     

Darstellung maskierter Nutzungseffekte auf naturraumspezifische Artengemeinschaften grasiger Feldraine mithilfe von Restvarianzmustern

Background and aim Grassy field margins have a high relevance in agricultural landscapes regarding the preservation of typical arthropod communities, their biodiversity and the ecological system functions linked with it. The structure of terrestrial communities is affected by anthropogenic impairment, which can lead to the replacement of sensitive by more tolerant species. The negative influence of pesticides on fauna and flora as well as the associated functional aspects (ecological system functions) and the reduction of biodiversity are undisputed since longer for agrarian systems and can also be assumed for grassy field margins due to spray-drift. The case study presented here examined the effect of influences related to utilization on the plant and arthropod communities of grassy field margins. Reference sites, on which due to missing farming in the direct surrounding countryside no utilization influences on the communities were present, were compared to non-target sites, on which these influences could not be excluded. Sites in three German macrochores were examined: in the Jülicher Börde, at the northeastern edge of the Leipziger low lands and in the area Mainfranken near Würzburg, all of them intensely used agricultural landscapes. Beside the vegetation, the epigeic arthropod communities of carabid beetles, spiders, springtails, hymenopterans, hover flies and ladybirds as well as abiotic parameters were included in the analysis. The aim of the study was the development of a statistical exclusion procedure which is capable to quantify the amount of variation in field community data which can be attributed to isolated factors. Special attention was paid to non-observable utilization impacts like undocumented pesticide application. The extraction of patterns of residual variance allowed for the uncovering of masked effects on a scale below the obvious abundance pattern. Materials and methods The variability in the species composition was visualized with the help of non-metric multi-dimensional scaling (NMDS). Indicator species analysis revealed those species which could be recognized as statistically significant indicators for local conditions. The relationship between the species composition and the environmental factors was statistically modeled by canonical correspondence analysis. By variance partitioning it was possible to extract the variance portion which could be bound to a set of covariables. For the remaining residual variance it could not be excluded that this resulted from a pesticide influence. Results The analyses based on the ecological distance (Bray-Curtis) showed that the communities in references sites and non-target sites could be clearly distinguished in all three landscapes. Based on the portions of variance which could be explained statistically by a utilization related influence, two different directions of reaction to the utilization related variables could be stated. On the one hand there were sensitive species, showing reduced abundances in the non-target sites, on the other hand there were species increasing in abundance in the non-target sites, recruiting from the group of strong competitors. Discussion By the use of residual variances a clear influence of utilization related parameters on the community of soil arthropods and vegetation could be shown. The observed abundances shifts between reference sites and non-target sites in the raw data were attributed to a multi-dimensional factor complex which could be split up by the use of partial ordination methods, quantifying the relationships to the utilization related parameters. It was demonstrated that special utilization correlated patterns could be found in the raw data after eliminating the influence of the covariables. Conclusions Utilization related influences in the non-target sites evened out the characteristic communities for the three landscapes towards a comprehensive, ubiquitous species composition. The hypothesis of decreasing abundance of sensitive species and the augmentation of tolerant species due to a potential pesticide influence could be underpinned and quantified. Sensitive species which showed a significant reduction in abundance between reference and non-target sites showed a much higher sensitivity to the influences and thus were assigned a higher indicator potential than tolerant species. From the group of the sensitive species Pardosa palustris and Poecilus cupreus could be isolated as two promising macrochore-specific indicator species for the masked effects. Recommendations and perspectives A macrochore-specific assessment of utilization effects was requested for future studies due to the different sensitivities of the species in the three landscapes. The elaboration and specifying of reference conditions for terrestrial agrarian systems is an important task for the future. The presented approach deduces a macrochore-specific, complex effect pattern of anthropogenic impairment on terrestrial species communities. It can be used to extract masked effects and by this facilitates a more sustainable use of e.g. plant protection products. Furthermore it provides an opportunity to validate evaluation systems for the effects of utilization impacts on terrestrial vegetation and arthropods. Additionally the species sensitivities with respect to the macrochores allow a regionalized assessment of ecotoxicological effects and the integration into spatially explicit effect assessment models.     

Environmental Impacts of a Secondary Lead Smelter in Landskrona, Southern Sweden

Scandinavia has one secondary lead smelter that recycles lead from approximately 85% of used car batteries in Scandinavia and which has been active since the 1940s. The smelter, situated in Landskrona, has undergone a comprehensive clean up programme during the last decade, during which time production has doubled, while at the same time discharges of dust and lead to the atmosphere have decreased.Top and depth soil samples were taken on a 0.5km×0.5Km grid throughout the city of Landskrona, which covers an area of approximately 15km². Samples were analysed by ICPAES for a number of elements including Pb, Zn, Cu, Cd, As, Sb and Hg. Road dust samples from selected sites were collected and similarly analysed. Blood samples were taken from 37 volunteer schoolchildren (aged 8–11) from two schools in Landskrona. House dust samples were taken from each child's home. Soil samples were taken from homes which had gardens, public and school play areas. Elevated heavy metal concentrations were found in close proximity to the secondary lead smelter, and this soil enrichment influences the whole of the town, modified to some extent by the prevailing wind. The smelter does not influence the soil lead concentration at distances greater than 3.5km, where the soil reflects the background value for the area.Road dust samples also show decreases in lead concentrations with distance from the smelter. The average level of lead in house dust was considerably lower than that found in Birmingham, UK. Blood lead levels in the child population ranged from 1.5–5.1gdl^–1, with a mean of 3.05gdl^–1, showing a distinct decrease from those measured in 1978–82. No significant difference in blood lead concentrations with distance of the home from the smelter, nor between attenders at the two schools was revealed in the limited number of children studied.     

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.     

Ants as a Measure of Effectiveness of Habitat Conservation Planning in Southern California

Abstract: In the United States multispecies habitat conservation plans were meant to be the solution to conflicts between economic development and protection of biological diversity. Although now widely applied, questions exist concerning the scientific credibility of the conservation planning process and effectiveness of the plans. We used ants to assess performance of one of the first regional conservation plans developed in the United States, the Orange County Central‐Coastal Natural Community Conservation Plan (NCCP), in meeting its broader conservation objectives of biodiversity and ecosystem‐level protection. We collected pitfall data on ants for over 3 years on 172 sites established across a network of conservation lands in coastal southern California. Although recovered native ant diversity for the study area was high, site‐occupancy models indicated the invasive and ecologically disruptive Argentine ant (Linepithema humile) was present at 29% of sites, and sites located within 200 m of urban and agricultural areas were more likely to have been invaded. Within invaded sites, native ants were largely displaced, and their median species richness declined by more than 60% compared with uninvaded sites. At the time of planning, 24% of the 15,133‐ha reserve system established by Orange County NCCP fell within 200 m of an urban or agricultural edge. With complete build out of lands surrounding the reserve, the proportion of the reserve system vulnerable to invasion will grow to 44%. Our data indicate that simply protecting designated areas from development is not enough. If habitat conservation plans are to fulfill their conservation promise of ecosystem‐level protection, a more‐integrated and systematic approach to the process of habitat conservation planning is needed.     

Epiphytische Flechten im Wandel von Immissionen und Klima • Ergebnisse einer Vergleichskartierung 1989/2007 in Nordwestdeutschland

Epiphytic lichens as indicators for changes in air pollution and climate. Results of a comparative survey 1989/2007 in north-west Germany Background, aim, and scope Lichens growing on tree bark (epiphytic lichens) respond very sensitively to environmental effects such as chemical substances and air temperature. Therefore, they are used as biomonitors for atmospheric pollution in environmental assessments. Based on a survey of epiphytic lichens in 1989, a repetition was performed in an intensively-used agricultural area of north-west Germany in 2007. The objective of this study was to assess possible changes in air pollution and climate. Materials and methods The study is based on a comparative inventory of epiphytic lichens, growing on 335 trees at 45 monitoring sites. A simplified half quantitative survey technique of the first survey was used. Results Indeed, major changes to the epiphytic lichen flora were found. Overall, nearly all monitoring points showed an increase in the level of lichen species. A sharp decrease in acidophileous species and a sharp increase in basidophileous and nitrophileous species were detected. In addition, an increase in thermophileous species which are mainly inhabitants of southern European countries was observed, combined with decreases in boreo-montanic species. Discussion These trends correspond with supra-regional observations. They are primarily attributed to changes in air pollution involving a decrease in SO₂ and an increase in NH₃ concentrations. Clear effects from climate change are evident as well. Conclusions Changes to epiphytic lichens over a 18-year period could be demonstrated using a relatively low-cost investigation. They are relevant for assessing the changing environmental situation, which is of great importance for other organism groups and ecosystems. Recommendations and perspectives Using standardized techniques epiphytic lichens are suitable bioindicators for obtaining different types of information about the air pollution in urban areas and in intensively-used agricultural regions. Furthermore they are obviously good indicators of temperature changes in their environment. More research is needed about the suitability of epiphytic lichens for a biomonitoring of climate changes.     

A process-based population dynamics model to explore target and non-target impacts of a biological control agent

The risks and benefits associated with efforts to control invasive alien species using classical biological control are being subjected to increasing scrutiny. A process-based population dynamics model was developed to explore the interactions between a folivorous biological control agent, Cleopus japonicus, and its plant host Buddleja davidii. The model revealed that climate could have a significant impact upon the interactions between B. davidii and C. japonicus. At the coolest sites, the impact of C. japonicus on B. davidii was slowed, but it was still eventually capable of controlling populations of B. davidii. At the warmer sites where both B. davidii and C. japonicus grew faster, B. davidii succumbed rapidly to weevil damage. We hypothesise that barring an encounter with a natural enemy, C. japonicus will eventually be able to provide sustained control B. davidii throughout the North Island of New Zealand. The model scenarios illustrate the potential for the C. japonicus population to attain high densities rapidly, and to defoliate patches of B. davidii, creating the potential for spill-over feeding on non-target plants. The potential magnitude of this threat will depend partly on the climate suitability for C. japonicus, the pattern by which it migrates in response to a reduction in the available leaf resource, and the suitability of non-target plants as hosts. In all migration scenarios considered, the pattern of population growth and resource consumption by C. japonicus was exponential, with a strong tendency toward complete utilisation of resource patches more quickly at the warmer compared to colder sites. In addition to providing some useful hypotheses about the effects of climate on the biological control system, and the non-target risks, it also provides some insight into the mechanisms by which climate affects the system.