Search

This paper refers to a subjective approach to Ecosystems, referred to as Impure Systems to capture a set of fundamental properties. There are four main phenomenological components: directionality, intensity, connection energy and volume. A fundamental question in this approach to Impure Systems is the intensity or forces of a relation. Concepts as the system volume, and propose a system thermodynamic theory based in the Law of Zipf and the temperature of information are introduced. It hints at the possibility of adapting the fractal theory by introducing the fractal dimension of the system., Author(s): Josué-Antonio Nescolarde-Selva [sup.1] , José-Luis Usó-Doménech [sup.1] , Miguel Lloret-Climent [sup.1] Author Affiliations: (Aff1) 0000 0001 2168 1800, grid.5268.9, Department of Applied Mathematics, University of Alicante, , Alicante, Spain [...]

The ascidian Styela clava, native to the north-west Pacific, is an invasive species affecting New Zealand's marine ecosystems, biodiversity and aquaculture operations. To provide detailed information on the reproductive biology of S. clava in New Zealand for post-border biosecurity management, long-term seasonal patterns of gametogenesis were determined from May 2006 to May 2008 in Auckland's Waitemata Harbour (36°49'20'S, 174°45'85'E). Of particular interest was whether the critical 15°C threshold spawning temperature for reproduction observed in the Northern Hemisphere applied here to the first Southern Hemisphere study. S. clava gametogenesis followed a regular seasonal cycle with ripe gametes appearing as early as September and persisting to June; this time frame corresponds to the period when sea surface temperatures in the region first reach 15°C and with spawning occurring mainly during late summer to early autumn. From photoperiod manipulation, it was determined that spawning occurred at approximately 18:20. The extended reproductive period and a short generation time in the Waitemata Harbour provides a lengthy opportunity for S. clava to spread. Findings are discussed in relation to S. clava's post-border management., Author(s): Nicholas A. Wong [sup.1] , Dan McClary [sup.2] [sup.3] , Mary A. Sewell [sup.1] Author Affiliations: (1) grid.9654.e, 0000000403723343, School of Biological Sciences, University of Auckland, , Private Bag [...]

The metabolic theory of ecology (MTE) is based on models derived from the first principles of thermodynamics and biochemical kinetics. The MTE predicts that the relationship between temperature and species richness of ectotherms should show a specific slope. Testing the validity of this model, however, depends on whether empirical data do not violate assumptions and are obtained within contour conditions. When dealing with richness gradients, the MTE must be empirically tested only for ectothermic organisms at high organization levels and when their body size as well as abundance does not vary with temperature gradients. Here we evaluate whether the magnitude of the deviations in slope expected from the MTE to empirical data for New World amphibians is due to the violations of model assumptions and to lack of generality due to restricting contour conditions. We found that the MTE correctly predicted biodiversity patterns only at higher levels of organization and when assumptions of the basic model were not violated. Approximately 60% of the deviations from the MTE-predicted slope across amphibian families were due to violations of the model assumptions. The hypothesis that richness patterns are a function of environmental temperature is too restrictive and does not take complex environmental and ecological processes into account. However, our results suggest that it may be possible to obtain multiple derivations of the MTE equation if idiosyncrasies in spatial and biological/ ecological issues that are essential to understanding biodiversity patterns are considered. Key words: body size; diversity gradients; ectotherms; macroecology; spatial autocorrelation; species richness; stationarity; temperature gradients.

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1365-2745.2009.01635.x Byline: Roberto Salguero-Gomez (1), Hans de Kroon (2) Keywords: demographic buffering; integral projection model; plant demography; population dynamics; projection matrix; stochastic elasticity; stochastic life table response experiment (SLTRE); transient dynamics Abstract: Summary 1. Projection matrices have become the dominant modelling approach in plant demography because they (i) are relatively easy to formulate, (ii) compile complex data in a structured and analytically tractable manner, (iii) provide numerous parameters with direct biological meaning, (iv) allow the investigator to address broad or specific, experimental and/or theoretical, ecological and evolutionary questions, and (v) produce uniform outputs, enabling direct comparisons between the results of different studies. 2. The last decade has witnessed major advancements in this field that have brought demographic models much closer to the real world, in particular in the analysis of effects of spatial and temporal environmental variation on populations. The present Special Feature contributes to that progress with novel methodologies and applications on Integral Projection Models, stochastic Life Table Response Experiment analyses, stochastic elasticities, transient dynamics and phylogenetic analyses. 3.Synthesis. Environmental stochasticity is an integral part of ecosystems, and plant populations exhibit a tremendous array of demographic strategies to deal with its effects. The analytical challenge of understanding how populations avoid, tolerate or depend on stochasticity is finally overcome with the new matrix approaches. The tools are now available to interpret the effects of changes in temporal and spatial variation on plant populations. Author Affiliation: (1)Department of Biology, University of Pennsylvania, 215 South University Avenue, 321 Leidy Laboratories, Philadelphia, PA 19104, USA (2)Department of Experimental Plant Ecology, Radboud University Nijmegen, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands Article History: Received 3 December 2009; accepted 9 December 2009 Handling Editor: Michael Hutchings Article note: (*) Correspondence author. E-mail: salguero@sas.upenn.edu

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.anbehav.2009.06.025 Byline: Ferenc Szalai (a), Szabolcs Szamado (b) Abstract: The honesty of communication in competitive situations has long been debated. We investigated the coexistence of a diverse set of strategies in a simple model of aggressive communication by means of individual-based computer simulations. The game is an extended Hawk-Dove game in which there are two types of individual, weak and strong, and in which individual can communicate by means of cost-free signals before deciding whether to attack. The available strategies can be classified into three categories: honest, cheaters and those that ignore the signalling system. We found a diverse set of equilibria, most of them consisting of a mixture of honest and cheating individuals. We found that when starting populations consist of all strategies (1) the honest equilibrium can evolve, (2) communication is almost always present when signals are informative, and (3) strategies that ignore signalling are generally rare. Honest individuals need not be the majority in these populations yet communication will be present and stable in the long run. In contrast, the pure honest equilibrium is unlikely to evolve when the starting populations consist of strategies that ignore signals. Strategies that ignore signals are more frequent in these types of run however, signalling strategies are still present in the most frequently evolved equilibria. Even in this simple system two different kinds of use of signals can evolve: the first when signals refer to resource-holding potential and a second where signals are used to create a payoff-irrelevant asymmetry. In general, regardless of the starting conditions, a low resource value favours weak individuals, both honest and cheaters, and cowards, medium values favour strong individuals that use and listen to signals, and a high resource value favours strong individuals that ignore the signalling system and attack under all conditions. Although it is possible to find parameter combinations with a negative value of information, the value of information is positive in the overwhelming majority of equilibria. Thus one can conclude that for the majority of parameter combinations an equilibrium evolved that might not be honest, not even on average, but communication is present and signals are worth listening to. Author Affiliation: (a) Research Institute for Solid State Physics and Optics, Hungarian Academy of Sciences, Hungary (b) Department of Plant Taxonomy and Ecology, HAS Research Group of Ecology and Theoretical Biology, Eotvos Lorand University, Hungary Article History: Received 3 August 2007; Revised 12 November 2007; Accepted 22 June 2009 Article Note: (miscellaneous) MS. number: 9479R

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1523-1739.2009.01209.x Byline: HAKAN BERGLUND (*), ROBERT B. O'HARA ([dagger]), BENGT GUNNAR JONSSON ([double dagger]) Keywords: conservation planning; hierarchical model; logistic regression; random effect; predictability Abstract: Abstract: Quantitative conservation objectives require detailed consideration of the habitat requirements of target species. Tree-living bryophytes, lichens, and fungi are a critical and declining biodiversity component of boreal forests. To understand their requirements, Bayesian methods were used to analyze the relationships between the occurrence of individual species and habitat factors at the tree and the stand scale in a naturally fragmented boreal forest landscape. The importance of unexplained between-stand variation in occurrence of species was estimated, and the ability of derived models to predict species' occurrence was tested. The occurrence of species was affected by quality of individual trees. Furthermore, the relationships between occurrence of species at the tree level and size and shape of stands indicated edge effects, implying that some species were restricted to interior habitats of large, regular stands. Yet for the habitat factors studied, requirements of many species appeared similar. Species occurrence also varied between stands; most of the seemingly suitable trees in some stands were unoccupied. The models captured most variation in species occurrence at tree level. They also successfully accounted for between-stand variation in species occurrence, thus providing realistic simulations of stand-level occupancy of species. Important unexplained between-stand variation in species occurrence warns against a simplified view that only local habitat factors influence species' occurrence. Apparently, similar stands will host populations of different sizes due to historical, spatial, and stochastic factors. Thus, habitat suitability cannot be assessed simply by population sizes, and stands lacking a species may still provide suitable habitat and merit protection. Abstract (Spanish): Cuantificacion de los Requerimientos de Habitat de Especies Arboricolas en Bosques Boreales Fragmentados Mediante Metodos Bayesianos Resumen: Los objetivos de la conservacion cuantitativa requieren consideracion detallada de los requerimientos de habitat de las especies de interes. Las briofitas, liquenes y hongos arboricolas son un componente, critico y en declinacion, de la biodiversidad de los bosques boreales. Para comprender sus requerimientos, utilizamos metodos Bayesianos para analizar las relaciones entre la ocurrencia de especies individuales y factores del habitat en el arbol y a escala de parche en un paisaje de bosque boreal fragmentado naturalmente. Se estimo la importancia de la variacion no explicada en la ocurrencia de especies entre parches, y se probo la habilidad de los modelos derivados para predecir la ocurrencia de especies. La ocurrencia de especies fue afectada por la calidad de los arboles individuales. Mas aun, las relaciones entre la ocurrencia de especies a nivel de arbol y la forma y tamano de los parches indicaron efectos de borde, lo que implica que algunas especies estaban restringidas a los habitats interiores de parches extensos y regulares. No obstante, para los factores estudiados, los requerimientos de muchas especies fueron similares. La ocurrencia de especies tambien vario entre parches; la mayoria de los arboles aparentemente adecuados en algunos parches estaban desocupados. Los modelos capturaron la mayor parte de la variacion en la ocurrencia de especies a nivel de arbol. Tambien explicaron exitosamente la variacion en la ocurrencia de especies entre parches, por lo tanto proporcionaron simulaciones realistas de la ocupacion de especies a nivel de parche. La variacion no explicada entre parches es una advertencia contra la vision simplificada que solo los factores locales del habitat influyen en la ocurrencia de las especies. Aparentemente, parches similares hospedaran poblaciones de diferentes tamanos debido a factores historicos, espaciales y estocasticos. Por lo tanto, la aptitud del habitat no puede ser evaluada simplemente por el tamano de las poblaciones, y los parches que carecen de especies aun pueden proporcionar habitat adecuado y merecer proteccion. Author Affiliation: (*)Department of Ecology, Swedish University of Agricultural Sciences, P.O. Box 7044, SE-750 07 Uppsala, Sweden, emailhakan.berglund@ekol.slu.se ([dagger])Department of Mathematics and Statistics, P.O. Box 68 (Gustaf Hallstromin katu 2b), FIN-00014, University of Helsinki, Finland ([double dagger])Department of Natural Sciences, Engineering and Mathematics, Mid Sweden University, SE-851 70 Sundsvall, Sweden Article History: Paper submitted June 19, 2008; revised manuscript accepted December 26, 2008.

There is still much uncertainty about ecological controls on the rate and direction of net C[O.sub.2] exchange by tropical rain forests, in spite of their importance to global C cycling. These controls are thought to arise from hydrologic and nutrient constraints to C[O.sub.2] fixation caused by seasonality of precipitation and adverse chemical properties of some major tropical soil types. Using the ecosystem model ecosys, we show that water uptake to a depth of 8 m avoids constraints to C[O.sub.2] and energy exchange from soil drying during five-month dry seasons typical for eastern Amazonian forests. This avoidance in the model was tested with eddy covariance (EC) measurements of C[O.sub.2] and energy fluxes during 2003 and 2004 over an old-growth forest on an acidic, nutrient-poor oxisol in the Tapajds National Forest (TNF) in Para, Brazil. Modeled C[O.sub.2] fixation was strongly constrained by slow phosphorus (P) uptake caused by low soil pH. Daytime C[O.sub.2] influxes in the model were in close agreement with EC measurements ([R.sup.2] > 0.8) during both wet and dry seasons. Both modeled and measured fluxes indicated that seasonality of precipitation affected C[O.sub.2] and energy exchange more through its effect on radiation and air temperature than on soil water content. When aggregated to a yearly scale, modeled and gap-filled EC C[O.sub.2] fluxes indicated that old-growth forest stands in the TNF remained within 100 g C*[m.sup.-2]*[yr.sup.-1] of C neutrality in the absence of major disturbance. Annual C transformations in ecosys were further corroborated by extensive biometric measurements taken in the TNF and elsewhere in the Amazon basin, which also indicated that old-growth forests were either small C sources or small C sinks. Long-term model runs suggested that rain forests could be substantial C sinks for several decades while regenerating after stand-replacing disturbances, but would gradually decline toward C neutrality thereafter. The time course of net ecosystem productivity (NEP) in the model depended upon annual rates of herbivory and tree mortality, which were based on site observations as affected by weather (e.g., El Nino Southern Oscillation [ENSO] events). This dependence suggests that rain forest NEP is strongly controlled by disturbance as well as by weather. Key words: Brazil; C[O.sub.2] exchange; disturbance; ecosys; ecosystem modeling; Her ecosystem productivity; rain forest.

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1523-1739.2008.01160.x Byline: DUNCAN S. WILSON (*[double dagger]), MARGO A. STODDARD ([dagger]), MATTHEW G. BETTS (*), KLAUS J. PUETTMANN (*) Keywords: amphibian conservation; Ascaphus truei; Dicamptodon tenebrosus; hierarchical Bayesian models; Rhyacotriton kezeri; Rhyacotriton variegatus; risk assessment Abstract: Abstract: Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species. Abstract (Spanish): Modelos Bayesianos de Area Reducida para Evaluar el Riesgo de Conservacion de Vida Silvestre en Poblaciones Fragmentadas Resumen: Las evaluaciones de riesgo de conservacion de especies requieren de mapas precisos, probabilisticos y biologicamente significativos de la distribucion de la poblacion. En poblaciones fragmentadas, las razones de las discontinuidades a menudo no son bien entendidas. Probamos un nuevo metodo para modelar habitats en el que se usaron metodos de estimacion de areas pequenas en un marco Bayesiano jerarquico. La ocurrencia de anfibios fue modelada con regresion logistica que incluyo escurrimientos de tercer orden como efectos jerarquicos para explicar las poblaciones fragmentadas. Los modelos que incluyeron los efectos de los escurrimientos aleatorios representaron adecuadamente la ocurrencia de especies en poblaciones fragmentadas de cuatro especies de anfibios en la Cordillera Costera de Oregon (E.U.A.). Utilizamos muestreos de anfibios en otras localidades en el mismo escurrimiento para calibrar los efectos del escurrimiento a escala local. La validacion cruzada mostro que los errores de prediccion para los modelos calibrados fueron entre 77% y 86% menores que los modelos comparables construidos regionalmente, dependiendo de la especie. Cuando no se disponia de datos de calibracion, los modelos de areas pequenas y regionales funcionaron similarmente, aunque pobremente. Los modelos de estimacion de areas pequenas complementan los estudios de ecologia y habitat de vida silvestre, y pueden ayudar a que los manejadores desarrollen una vision regional del estatus de conservacion de especies relativamente raras. Author Affiliation: (*)Department of Forest Science, Oregon State University, 321 Richardson Hall, Corvallis, OR 97331-5704 ([dagger])Department of Wildlife Ecology and Conservation, University of Florida, 110 Newins-Ziegler Hall, Gainesville, FL 32611-0430 Article History: Paper submitted April 19, 2008; revised manuscript accepted October 15, 2008. Article note: ([double dagger]) Current address: FPInnovations-Forintek Division, 2665 East Mall, Vancouver, B.C. V6T 1W5, Canada, email: dunc_steil@yahoo.com

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1600-0706.2009.17220.x Abstract: Growing empirical evidence suggests that aboveground and belowground multitrophic communities interact. However, investigations that comprehensively explore the impacts of above- and belowground third and higher trophic level organisms on plant and herbivore performance are thus far lacking. We tested the hypotheses that above- and belowground higher trophic level organisms as well as decomposers affect plant and herbivore performance and that these effects cross the soil-surface boundary. We used a well-validated simulation model that is individual-based for aboveground trophic levels such as shoot herbivores, parasitoids, and hyperparasitoids while considering belowground herbivores and their antagonists at the population level. We simulated greenhouse experiments by removing trophic levels and decomposers from the simulations in a factorial design. Decomposers and above- and belowground third trophic levels affected plant and herbivore mortality, root biomass, and to a lesser extent shoot biomass. We also tested the effect of gradual modifications of the interactions between different trophic level organisms with a sensitivity analysis. Shoot and root biomass were highly sensitive to the impact of the fourth trophic level. We found effects that cross the soil surface, such as aboveground herbivores and parasitoids affecting root biomass and belowground herbivores influencing aboveground herbivore mortality. We conclude that higher trophic level organisms and decomposers can strongly influence plant and herbivore performance. We propose that our modelling framework can be used in future applications to quantitatively explore the possible outcomes of complex above- and belowground multitrophic interactions under a range of environmental conditions and species compositions. Article History: Manuscript Accepted 16 March 2009 Article note: K. M. Meyer (kmeyer5@uni-goettingen.de), L. E. M. Vet and W. H. van der Putten, Netherlands Inst. of Ecology NIOO-KNAW, Centre for Terrestrial Ecology, Dept of Multitrophic Interactions, Boterhoeksestraat 48, NL-6666 GA Heteren, the Netherlands. Present address for KMM: Faculty of Forest Sciences and Ecology, Ecosystem Modelling, Univ. of Gottingen, Busgenweg 4, DE-37077 Gottingen, Germany. - M. Vos, Netherlands Inst. of Ecology NIOO-KNAW, Centre for Estuarine and Marine Ecology, Dept of Ecosystem Studies, Korringaweg 7, NL-4401 NT Yerseke, the Netherlands. Present address: Dept of Ecology and Ecosystem Modeling, Inst. of Biochemistry and Biology, Univ. of Potsdam, Am Neuen Palais 10, DE-14469 Potsdam, Germany. - W. M. Mooij, Netherlands Inst. of Ecology NIOO-KNAW, Centre for Limnology, Dept of Food Web Studies, Rijkstraatweg 6, NL-3631 AC Nieuwersluis, the Netherlands. - W. H. Gera Hol, Netherlands Inst. of Ecology NIOO-KNAW, Centre for Terrestrial Ecology, Dept of Terrestrial Microbial Ecology, Boterhoeksestraat 48, NL-6666 GA Heteren, the Netherlands. - A. J. Termorshuizen, Blgg, Nieuwe Kanaal 7f, NL-6709 PA Wageningen, the Netherlands.

The switch point theorem (SPT) is the quantitative statement of the hypothesis that stochastic effects on survival, mate encounter, and latency affect individuals' time available for mating, the mean and variance in fitness, and thus, originally favored the evolution of individuals able to make adaptively flexible reproductive decisions. The SPT says that demographic stochasticity acting through variation in (i) individual survival probability, s; (ii) individual encounter probability, e; (iii) latency, I; (iv) the number of potential mates in the population, n; and (v) the distribution of fitness conferred, the w distribution, together affect average lifetime fitness, and induce adaptive switches in individual reproductive decisions. The switch point is the rank of potential mates at which focal individuals switch from accepting to rejecting potential mates, a decision rule that the SPT proves maximizes the average lifetime fitness of a focal individual under given values of ecological constraints on time. The SPT makes many predictions, including that the shape of the distribution of fitness conferred affects individual switch points. All else equal, higher probabilities of individual survival and encounter decrease the fraction of acceptable potential mates, such that focal individuals achieve higher average lifetime fitness by rejecting more potential mates. The primary prediction of the SPT is that each decision a focal individual makes is determined jointly by e, s, I, n, and the w distribution. demographic stochasticity | encounter probability | mate choice | sexual selection | survival probability

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1600-0706.2008.17250.x Byline: Andreas Linden, Jonas Knape Abstract: Within the paradigm of population dynamics a central task is to identify environmental factors affecting population change and to estimate the strength of these effects. We here investigate the impact of observation errors in measurements of population densities on estimates of environmental effects. Adding observation errors may change the autocorrelation of a population time series with potential consequences for estimates of effects of autocorrelated environmental covariates. Using Monte Carlo simulations, we compare the performance of maximum likelihood estimates from three stochastic versions of the Gompertz model (log-linear first order autoregressive model), assuming 1) process error only, 2) observation error only, and 3) both process and observation error (the linear state-space model on log-scale). We also simulated population dynamics using the Ricker model, and evaluated the corresponding maximum likelihood estimates for process error models. When there is observation error in the data and the considered environmental variable is strongly autocorrelated, its estimated effect is likely to be biased when using process error models. The environmental effect is overestimated when the sign of the autocorrelations of the intrinsic dynamics and the environment are the same and underestimated when the signs differ. With non-autocorrelated environmental covariates, process error models produce fairly exact point estimates as well as reliable confidence intervals for environmental effects. In all scenarios, observation error models produce unbiased estimates with reasonable precision, but confidence intervals derived from the likelihood profiles are far too optimistic if there is process error present. The safest approach is to use state-space models in presence of observation error. These are factors worthwhile to consider when interpreting earlier empirical results on population time series, and in future studies, we recommend choosing carefully the modelling approach with respect to intrinsic population dynamics and covariate autocorrelation. Article History: Manuscript Accepted 17 November 2008 Article note: A. Linden (andreas.linden@helsinki.fi), Dept of Biological and Environmental Sciences, Integrative Ecology Unit, Post Office Box 65 (Viikinkaari 1), FI-00014, Univ. of Helsinki, Finland. - J. Knape, Dept of Theoretical Ecology, Ecology Building, Lund Univ., SE-22362 Lund, Sweden.

To authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1600-0706.2008.17142.x Byline: Jean-Baptiste Mihoub, Pascaline Le Gouar, Francois Sarrazin Abstract: Animal movement and habitat selection behavior are important considerations in ecology, and remain a major issue for successful animal reintroductions. However, simple rules are often used to model movement or focus only on intrinsic environmental cues, neglecting recent insights in behavioral ecology on habitat selection processes. In particular, social information has been proposed as a widespread source of information for habitat evaluation. We investigated the role of explicit breeding habitat selection strategies on the establishment pattern of reintroduced populations and their persistence. We considered local movement at the scale of a single population. We constructed a spatially-implicit demographic model that considered five breeding habitat selection rules: 1) random, 2) intrinsic habitat quality, 3) avoidance of conspecifics, 4) presence of conspecifics and 5) reproductive success of conspecifics. The impact of breeding habitat selection was examined for different release methods under various levels of environmental heterogeneity levels, for both long and short-lived monogamous species. When heterogeneity between intrinsic habitat patch qualities is high, the persistence of reintroduced populations strongly depends on habitat selection strategies. Strategies based on intrinsic quality and conspecific reproductive success lead to a lower reintroduction failure risk than random, conspecific presence or avoidance-based strategies. Conspecific presence or avoidance-based strategies may aggregate individuals in suboptimal habitats. The release of adults seems to be more efficient independent of habitat selection strategy. We emphasize the crucial role of oriented habitat selection behavior and non ideal habitat selection in movement modeling, particularly for reintroduction. Article History: Manuscript Accepted 14 November 2008 Article note: J.-B. Mihoub (mihoub@mnhn.fr), P. Le Gouar and F. Sarrazin, Univ. Pierre et Marie Curie, UMR 5173 MNHN-CNRS-UPMC 'Conservation des Especes, Restauration et Suivi des Populations', 61 rue Buffon, FR-75005 Paris, France. PG also at: UMR 6553 CNRS-Rennes1 'Ecobio', Station Biologique de Paimpont. Bat A, piece 111, FR-35380 Paimpont, France.

We present a theoretical framework to describe stochastic, size-structured community assembly, and use this framework to make community-level ecological predictions. Our model can be thought of as adding biological realism to Neutral Biodiversity Theory by incorporating size variation and growth dynamics, and allowing demographic rates to depend on the sizes of individuals. We find that the species abundance distribution (SAD) is insensitive to the details of the size structure in our model, demonstrating that the SAD is a poor indicator of size-dependent processes. We also derive the species biomass distribution (SBD) and find that the form of the SBD depends on the underlying size structure. This leads to a prescription for testing multiple, intertwined ecological predictions of the model, and provides evidence that alternatives to the traditional SAD are more closely tied to certain ecological processes. Finally, we describe how our framework may be extended to make predictions for more general types of community structure. neutral theory | allometry | ecological drift | complex systems

Secondary succession is impacted by both biotic and abiotic forces, but their relative importance varies due to environmental drivers. Across estuarine salinity gradients, physical stress increases with salinity, and biotic stresses are greater at lower salinities. In southern New England tidal marshes spanning a landscape-scale salinity gradient, we experimentally examined the effects of physical stress and consumer pressure by mammalian herbivores on secondary succession in artificially created bare patches. Recovery was slower in marshes exposed to full-strength seawater, where physical stress is high. Compared to full-strength salt marshes, recovery in low-salinity marshes was much faster and was influenced by small-mammal consumers. At lower salinities, small mammals selectively ate and prevented the establishment of several native and two invasive, nuisance species (Typha angustifolia and Phragmites australis) but were unable to control the expansion of established P. australis stands. By controlling the establishment of competitively dominant species and the trajectory of secondary succession in low-salinity marshes, small mammals may play a cryptic keystone role in estuarine plant communities and are a critical, overlooked consideration in the conservation and management of estuarine marshes. Key words: abiotic and biotic factors; consumer control; environmental stress models; herbivory; invasive species; New England tidal marshes; physical stress; salinity; secondary succession; small-mammal herbivores; stress gradients.

Hierarchical statistical models are increasingly being used to describe complex ecological processes. The data cloning (DC) method is a new general technique that uses Markov chain Monte Carlo (MCMC) algorithms to compute maximum likelihood (ML) estimates along with their asymptotic variance estimates for hierarchical models. Despite its generality, the method has two inferential limitations. First, it only provides Wald-type confidence intervals, known to be inaccurate in small samples. Second, it only yields ML parameter estimates, but not the maximized likelihood values used for profile likelihood intervals, likelihood ratio hypothesis tests, and information-theoretic model selection. Here we describe how to overcome these inferential limitations with a computationally efficient method for calculating likelihood ratios via data cloning. The ability to calculate likelihood ratios allows one to do hypothesis tests, construct accurate confidence intervals and undertake information-based model selection with hierarchical models in a frequentist context. To demonstrate the use of these tools with complex ecological models, we reanalyze part of Gause's classic Paramecium data with star-space population models containing both environmental noise and sampling error. The analysis results include improved confidence intervals for parameters, a hypothesis test of laboratory replication, and a comparison of the Beverton-Holt and the Ricker growth forms based on a model selection index. Key words: AIC; Bayesian statistics; data cloning; frequentist statistics; hierarchical models; likelihood ratio; Markov chain Monte Carlo; maximum likelihood; model selection; profile likelihood; state-space models; stochastic population models.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1600-0706.2008.17025.x Byline: Karen Mustin, Tim G. Benton, Calvin Dytham, Justin M. J. Travis Abstract: Predicted future climate change will alter species' distributions as they attempt to track the most suitable 'climate window'. Climate envelope models indicate the direction of likely range changes but do not incorporate population dynamics, therefore observed responses may differ greatly from these projections. We use simulation modelling to explore the consequences of a period of environmental change for a species structured across an environmental gradient. Results indicate that a species' range may lag behind its climate envelope and demonstrate that the rate of movement of a range can accelerate during a period of climate change. We conclude that the inclusion of both population dynamics and spatial environmental variability is vital to develop models that can both predict, and be used to manage, the impact of changing climate on species' biogeography. Article History: Manuscript Accepted 21 July 2008 Article note: K. Mustin (karen_mustin@abdn.ac.uk) and J. M. J. Travis, School of Biological Sciences, Univ. of Aberdeen, Zoology Building, Tillydrone Avenue, Aberdeen, AB24 2TZ, UK. - T. G. Benton, Inst. of Integrative and Comparative Biology, Univ. of Leeds, LS2 9JT, UK. - C. Dytham, Plant Ecology and Conservation, Inst. of Biology and Biochemistry, Maulbeerallee 2, Univ. of Potsdam, DE-14469 Potsdam, Germany. CD also at: Dept of Biology, Univ. of York, Heslington, York, YO10 5YW, UK.

Functional ecology aims at determining the relationships between species traits and environmental variables in order to better understand biological processes in ecosystems. From a methodological point of view, this biological objective calls for a method linking three data matrix tables: a table L with abundance or presence-absence values for species at a series of sites, a table R with variables describing the environmental conditions of the sites, and a table Q containing traits (e.g., morphological or behavioral attributes) of the species. Ten years ago, the fourth-corner method was proposed to measure and test the relationships between species traits and environmental variables using tables R, L, and Q simultaneously. In practice, this method is rarely used. The major reasons for this lack of interest are the restriction of the original method and program to presence--absence data in L and to the analysis of a single trait and a single environmental variable at a time. Moreover, ecologists often have problems in choosing a permutation model among the four originally proposed. In this paper, we revisit the fourth-corner method and propose improvements to the original approach. First, we present an extension to measure the link between species traits and environmental variables when the ecological community is described by abundance data. A new multivariate fourth-corner statistic is also proposed. Then, using numerical simulations, we discuss and evaluate the existing testing procedures. A new two-step testing procedure is presented. We hope that these elements will help ecologists use the best possible methodology to analyze this type of ecological problem. Key words: ecological community; fourth-corner statistic; functional ecology; permutational model; RLQ analysis; species traits.

To purchase or authenticate to the full-text of this article, please visit this link: http://dx.doi.org/10.1111/j.1365-2745.2008.01421.x Byline: Olivier J. Hardy (*) Keywords: community ecology; neutral model; null model; phylogenetic structure; randomization test; simulation; Type I error rate Abstract: Summary Analyzing the phylogenetic structure of natural communities may illuminate the processes governing the assembly and coexistence of species. For instance, an association between species co-occurrence in local communities and their phylogenetic proximity may reveal the action of habitat filtering, niche conservatism and/or competitive exclusion. Different methods were recently proposed to test such community-wide phylogenetic patterns, based on the phylogenetic clustering or overdispersion of the species in a local community. This provides a much needed framework for addressing long standing questions in community ecology as well as the recent debate on community neutrality. The testing procedures are based on (i) a metric measuring the association between phylogenetic distance and species co-occurrence, and (ii) a data set randomization algorithm providing the distribution of the metric under a given 'null model'. However, the statistical properties of these approaches are not well-established and their reliability must be tested against simulated data sets. This paper reviews metrics and null models used in previous studies. A 'locally neutral' subdivided community model is simulated to produce data sets devoid of phylogenetic structure in the spatial distribution of species. Using these data sets, the consistency of Type I error rates of tests based on 10 metrics combined with nine null models is examined. This study shows that most tests can become liberal (i.e. tests rejecting too often the null hypothesis that only neutral processes structured spatially the local community) when the randomization algorithm breaks down a structure in the original data set unrelated to the null hypothesis to test. Hence, when overall species abundances are distributed non-randomly across the phylogeny or when local abundances are spatially autocorrelated, better statistical performances were achieved by randomization algorithms preserving these structural features. The most reliable randomization algorithm consists of permuting species with similar abundances among the tips of the phylogenetic tree. One metric, R.sub.PD-DO, also proved to be robust under most simulated conditions using a variety of null models. Synthesis. Given the suboptimal performances of several tests, attention must be paid to the testing procedures used in future studies. Guidelines are provided to help choosing an adequate test. Article History: Received 3 October 2007; accepted 18 June 2008Handling Editor: Christopher Lortie Article note: (*) Correspondence author. E-mail: ohardy@ulb.ac.be

This article begins with a brief resume of how the book Living Systems came into being, following which we are reminded that Alfred N. Whitehead's philosophy is an important part of the thinking upon which the book is built. Certain other philosophers are also mentioned. There is then a discussion of systems science, after which I deal with three different points of view regarding how to see the earth as a system: one which emanates from James and Jessie Miller's article 'The earth as a system'; one which can be called a scientific point of view; and one which is based on the standpoint that the earth should be seen as a ninth level of life according to Miller's living systems analytical framework. This latter standpoint is then taken as a starting point for simulating a model of the earth system. Keywords philosophy of organism; living systems; systems science; system; earth as living system, INTRODUCTION Miller's living systems theory is a life's work; it has a philosophical foundation and incorporates the views and findings of very large numbers of researchers representing a wide range [...]

Edge effects are among the most extensively studied ecological phenomena, yet we lack a general, predictive framework to understand the patterns and variability observed. We present a conceptual model, based on resource distribution, that predicts whether organismal abundances near edges are expected to increase, decrease, or remain unchanged for any species at any edge type. Predictions are based on whether resources are found predominantly in one habitat (decreased abundance in preferred habitat, increase in non-preferred), divided between habitats (predicts an increase near both edges), spread equally among habitats (predicts a neutral edge response), or concentrated along the edge (increase). There are several implications of this model that can explain much of the variability reported in the edge literature. For instance, our model predicts that a species may show positive, negative, and neutral responses, depending on the edge type encountered, which explains some intraspecific variability observed in the literature. In addition, any predictable change in resource use (for example, by region or season) may explain temporal or spatial variability in responses even for the same species at the same edge type. We offer a preliminary test of our model by making predictions for 52 bird species from three published studies of abundance responses near forest edges. Predictions are based solely on general information about each species' habitat associations and resource use. Our model correctly predicted the direction of 25 out of 29 observed edge responses, although it tended to under-predict increases and over-predict decreases. This model is important because it helps make sense of a largely descriptive literature and allows future studies to be carried out under a predictive framework. Key words: ecological boundary; ecotone,' edge responses,' habitat edge; predictive model,' resource distribution.

Although an ecological model of social work practice has been important to the profession since the 1970s, advances in ecological theory based on developments in deep ecology (Naess 1989) and social ecology (Bookchin 1980, 1982) inform a significantly different understanding of ecological theory on which to base an emerging practice. Earlier conceptualizations of ecology in social work, synonymous with mechanistic systems models, differ from the more mutualistic, nonhierarchical, and emancipatory use of ecological principles found in this new ecology. Eight principles are explored for their applicability to the practice of social work.

We describe and test a method for fitting noisy differential equation models to a time series of population counts, motivated by stage-structured models of insect and zooplankton populations. We consider semimechanistic models, in which the model structure is derived from knowledge of the life cycle, but the rate equations are estimated nonparametrically from the time-series data. The method involves smoothing the population time series x(t) in order to estimate the gradient dx/dr, and then fitting rate equations using penalized regression splines. Computer-intensive methods are used to estimate and remove the biases that result from the data being discrete time samples with sampling errors from a continuous time process. Semimechanistic modeling makes it possible to test assumptions about the mechanisms behind population fluctuations without the results being confounded by possibly arbitrary choices of parametric forms for process-rate equations. To illustrate this application, we analyze time-series data on laboratory populations of blowflies Lucilia cuprina and Lucilia sericata. The models assume that the populations are limited by competition among adults affecting their current birth and death rates. The results correspond to the actual experimental conditions. For L. cuprina (where the model's structure is appropriate) a good fit can be obtained, while for L. sericata (where the model is inappropriate), the fitted model does not reproduce some major features of the observed cycles. A documented set of R functions for all steps in the model-fitting process is provided as a supplement to this article. Key words: blowflies; gradient matching; Lucilia cuprina; Lucilia sericata; model fitting; partially specified models; population dynamics; semimechanistic models; semiparametric models; stage structured models.

Nondetection of a species at a site does not imply that the species is absent unless the probability of detection is 1. We propose a model and likelihood-based method for estimating site occupancy rates when detection probabilities are < 1. The model provides a flexible framework enabling covariate information to be included and allowing for missing observations. Via computer simulation, we found that the model provides good estimates of the occupancy rates, generally unbiased for moderate detection probabilities (>0.3). We estimated site occupancy rates for two anuran species at 32 wetland sites in Maryland, USA, from data collected during 2000 as part of an amphibian monitoring program, Frog-watch USA. Site occupancy rates were estimated as 0.49 for American toads (Bufo americanus), a 44% increase over the proportion of sites at which they were actually observed, and as 0.85 for spring peepers (Pseudacris crucifer), slightly above the observed proportion of 0.83. Key words: anurans; bootstrap; Bufo americanus; detection probability; maximum likelihood; metapopulation; monitoring; patch occupancy; Pseudacris crucifer; site occupancy.

Two major challenges of spatial ecology are understanding the effects of landscape heterogeneity on movement, and translating observations taken at small spatial and temporal scales into expected patterns at greater scales. Using a combination of computer simulations and micro-landscape experiments with Tribolium confusum beetles we found that conventional correlated random walk models with constant parameters severely underestimated spatial spread because organisms changed movement behaviors over time. However, a model incorporating behavioral heterogeneity between individuals, and within individuals over time, was able to account for observed patterns of spread. Our results suggest that the main challenge for scaling up movement patterns resides in the complexities of individual behavior rather than in the spatial structure of the landscape. Key words: animal movement; correlated random walk; diffusion; land-management information; landscape heterogeneity, and movement; model, individual based; population heterogeneity; random walk models; scaling up; spatial ecology; Tribolium confusum.

J.M. Diamond's assembly rules model predicts that competitive interactions between species lead to nonrandom co-occurrence patterns. We conducted a meta-analysis of 96 published presence--absence matrices and used a realistic 'null model' to generate patterns expected in the absence of species interactions. Published matrices were highly nonrandom and matched the predictions of Diamond's model: there were fewer species combinations, more checkerboard species pairs, and less co-occurrence in real matrices than expected by chance. Moreover, nonrandom structure was greater in homeotherm vs. poikilotherm matrices. Although these analyses do not confirm the mechanisms of Diamond's controversial assembly rules model, they do establish that observed co-occurrence in most natural communities is usually less than expected by chance. These results contrast with previous analyses of species co-occurrence patterns and bridge the apparent gap between experimental and correlative studies in community ecology. Key words: community assembly rules; meta-analysis; null models; presence-absence matrix; species co-occurrence.

Many ecological studies require analysis of collections of estimates. For example, population change is routinely estimated for many species from surveys such as the North American Breeding Bird Survey (BBS), and the species are grouped and used in comparative analyses. We developed a hierarchical model for estimation of group attributes from a collection of estimates of population trend. The model uses information from predefined groups of species to provide a context and to supplement data for individual species; summaries of group attributes are improved by statistical methods that simultaneously analyze collections of trend estimates. The model is Bayesian; trends are treated as random variables rather than fixed parameters. We use Markov Chain Monte Carlo (MCMC) methods to fit the model. Standard assessments of population stability cannot distinguish magnitude of trend and statistical significance of trend estimates, but the hierarchical model allows us to legitimately describe the probability that a trend is within given bounds. Thus we define population stability in terms of the probability that the magnitude of population change for a species is less than or equal to a predefined threshold. We applied the model to estimates of trend for 399 species from the BBS to estimate the proportion of species with increasing populations and to identify species with unstable populations. Analyses are presented for the collection of all species and for 12 species groups commonly used in BBS summaries. Overall, we estimated that 49% of species in the BBS have positive trends and 33 species have unstable populations. However, the proportion of species with increasing trends differs among habitat groups, with grassland birds having only 19% of species with positive trend estimates and wetland birds having 68% of species with positive trend estimates. Key words: birds; Breeding Bird Survey; conservation action; hierarchical models; Markov chain Monte Carlo methods; population stability; population trends; ranking estimates; species group attributes; surveys.

We introduce a heuristic model for studying the evolution of ecological ideas based on Thomas Kuhn's concept of the development of scientific paradigms. This model is useful for examining processes leading to ecological progress and the elaboration of ecological theories. Over time, ecological knowledge diverges and evolves as data are collected that either refute or support the current trajectories of accepted paradigms. As a result, the direction of ecological research continuously branches out into new domains leading to increased ecological understanding. Unfortunately, heightened ecological understanding also builds impediments to future progress. Increased specialization and the parallel evolution of seemingly independent subdisciplines generally compel researchers to become increasingly canalized. Specialization also accelerates the expansion of the ecological literature, making it difficult for researchers to track developments in their own subdisciplines, let alone the general field of ecology. Furthermore, specialization inherently focuses attention on contemporary research and hastens the erasure of memory of historical contributions to modern ecology. As a result, contemporary ecologists are in danger of losing touch with their historical roots and face a greater likelihood of recycling ideas and impeding real scientific momentum. Enhancing our historical perspective on the evolution of ecological ideas will be key in overcoming the negative consequences of progress and safeguarding the continued advancement of ecology. Key words: ecological knowledge; ecology; evolution of ideas; evolution of theories; historical perspective; historical roots; modern ecology; paradigms; scientific progress; scientific revolution; specialization; theories.

We evaluate a method for fitting models to time series of population abundances that incorporates both process noise and observation error in a likelihood framework. The method follows the probability logic of the Kalman filter, but whereas the Kalman filter applies to linear, Gaussian systems, we implement the full probability calculations numerically so that any nonlinear, non-Gaussian model can be used. We refer to the method as the 'numerically integrated state-space (NISS) method' and compare it to two common methods used to analyze nonlinear time series in ecology: least squares with only process noise (LSPN) and least squares with only observation error (LSOE). We compare all three methods by fitting Beverton-Holt and Ricker models to many replicate model-generated time series of length 20 with several parameter choices. For the Ricker model we chose parameters for which the deterministic part of the model produces a stable equilibrium, a two-cycle, or a four-cycle. For each set of parameters we used three process-noise and observation-error scenarios: large standard deviation (0.2) for both, and large for one but small (0.05) for the other. The NISS method had lower estimator bias and variance than the other methods in nearly all cases. The only exceptions were for the Ricker model with stable-equilibrium parameters, in which case the LSPN and LSOE methods has lower bias when noise variances most closely met their assumptions. For the Beverton-Holt model, the NISS method was much less biased and more precise than the other methods. We also evaluated the utility of each method for model selection by fitting simulated data to both models and using information criteria for selection. The NISS and LSOE methods showed a strong bias toward selecting the Ricker over the Beverton-Holt, even when data were generated with the Beverton-Holt. It remains unclear whether the LSPN method is generally superior for model selection or has fortuitously better biases in this particular case. These results suggest that information criteria are best used with caution for nonlinear population models with short time series. Finally we evaluated the convergence of likelihood ratios to theoretical asymptotic distributions. Agreement with asymptotic distributions was very good for stable-point Ricker. parameters, less accurate for two-cycle and four-cycle Ricker parameters, and least accurate for the Beverton-Holt model. The numerically integrated state-space method has a number of advantages over least squares methods and offers a useful tool for connecting models and data and ecology. Key words: Beverton-Holt model; Kalman filter; least-squares cf. state-space models; model-fitting; observation error; parameter estimation; population models; process noise; Ricker model; time series.

Issues of spatial scale are inherent in many ecological systems. This study uses a spatially explicit cellular automaton model to explore how the scale of dispersal interacts with the scale and strength of negative frequency dependence to determine patterns of species distribution. Counter to expectation, strong local frequency-dependent interactions result in random spatial patterns. When dispersal scale and interaction scale are decoupled, the resulting patterns are not necessarily random. For strong negative frequency dependence, stable bands result when the scale of interaction exceeds the scale of dispersal, and bands with two-point cycles result when the scale of dispersal exceeds the scale of interaction. However, for weaker interactions occurring over intermediate scales, only random patterns result. Thus, our results call into question the utility of inferring any ecological interaction from only the spatial distributions of the putatively interacting species. Furthermore, our results call for new experimental studies that explicitly manipulate the strength and the scale of the processes being studied. Key words: cellular automata; competition scale; dispersal scale; negative frequency dependence and pattern; pattern vs. process; population dynamics, scale and process; spatial patterns; spatial scale; stochastic spatial model.

The study of spatial patterns in the distribution of organisms is a central issue in ecology. Here we address the question of whether predator--prey interactions can induce nonuniform distributions. We study how diffusion affects the stability of predator--prey coexistence equilibria and show a new difference between ratio- and prey-dependent models. Recently, Peter Abrams and Lev Ginzburg reviewed the controversial issue of what kind of function better describes the rate of prey consumption by an average predator, the so-called 'predator functional response.' Here, we focus on reaction-diffusion predator--prey models with and without predator dependence in the functional response. We show that classical prey-dependent models cannot give rise to spatial structures through diffusion-driven instabilities; however, predator-dependent models with the same degree of complexity can. The origin of predator dependence in the rate of prey consumption is the mutual interference between predators. Therefore, we show that this mechanism can generate patchiness in a homogeneous environment under certain conditions of trophic interaction and predator--prey relative diffusion. Key words: Beddington's functional response; functional response, ratio-dependent; linear stability analysis; patchiness in a homogeneous environment; predators, mutual interference effects; predator--prey models; prey dependence vs. ratio dependence; reaction-diffusion models; Turing patterns.

The problem of scale has been a critical impediment to incorporating important fine-scale processes into global ecosystem models. Our knowledge of fine-scale physiological and ecological processes comes from a variety of measurements, ranging from forest plot inventories to remote sensing, made at spatial resolutions considerably smaller than the large scale at which global ecosystem models are defined. In this paper, we describe a new individual-based, terrestrial biosphere model, which we label the ecosystem demography model (ED). We then introduce a general method for scaling stochastic individual-based models of ecosystem dynamics (gap models) such as ED to large scales. The method accounts for the fine-scale spatial heterogeneity within an ecosystem caused by stochastic disturbance events, operating at scales down to individual canopy-tree-sized gaps. By conditioning appropriately on the occurrence of these events, we derive a size-and age-structured (SAS) approximation for the first moment of the stochastic ecosystem model. With this approximation, it is possible to make predictions about the large scales of interest from a description of the fine-scale physiological and population-dynamic processes without simulating the fate of every plant individually. We use the SAS approximation to implement our individual-based biosphere model over South America from 15 [degrees] N to 15 [degrees] S, showing that the SAS equations are accurate across a range of environmental conditions and resulting ecosystem types. We then compare the predictions of the biosphere model to regional data and to intensive data at specific sites. Analysis of the model at these sites illustrates the importance of fine-scale heterogeneity in governing large-scale ecosystem function, showing how population and community-level processes influence ecosystem composition and structure, patterns of aboveground carbon accumulation, and net ecosystem production. Key words: biogeochemical dynamics; ecosystem dynamics; ecosystem model, terrestrial; individual-based model; moment approximation; plant community dynamics; scaling; size- and age-structured; South America; sub-grid scale heterogeneity; terrestrial biosphere model; vegetation dynamics.

The author suggests that increased use of short-term, flexible experiments and more extensive research on natural history will help improve methods for measuring levels of interspecific interactions within biological populations. Single numerical approaches are inadequate, as most interactions are nonlinear.

A model is presented to depict the interrelationships between insects, the plants they feed on, and their natural enemies, based on a tri-trophic system that incorporates compensatory ability of insect-enemy behavior and nutritional quality of food plants and resultant insect herbivory.

A method is presented for constructing a causal scientific explanation for describing ecological processes. This method includes definitions of consistent causal processes that depict system functions, provides general data about events of similar kinds under similar conditions, and enables experiments to produce a predictable response.

Community ecologists have long sought to understand the basis for two apparently conflicting observations. The first is the evident persistence of complex communities through time. The second is the theoretical result that, in general, complex model communities are less likely to be stable than simpler ones. Previous attempts to reconcile these observations have studied the average properties of model communities constructed under a variety of different assumptions. The problem with such studies is that the set of all possible models, even when subject to strict constraints, is very large relative to the subset that may be representative of real communities, and it is unclear which constraints to apply. Here, it is assumed that real communities are a highly restricted subset of all possible models, and attention is focused instead on properties of communities constructed to be as stable as they could be. Geometrically derived analytic results show that in general, communities constructed in this way require high levels of connectance, as measured by the product of the strength and frequency of interspecific interaction. In particular, connectance between weakly and strongly self-regulated elements of these communities is of critical importance. Key words: community stability vs. community complexity; connectance; connectivity; ecosystem models; ecosystem stability; eigenvalues; interaction strength; stability and complexity.

What exactly is science? This question has received considerable attention from contemporary philosophers of science, notably Popper (1968) on the central role of falsifiability in scientific theory, Kuhn (1962) on [...]

Resilience is a component of ecological stability; it is assessed as the rate at which perturbations to a stable ecological system decay. The most frequently used estimate of resilience is based on the eigenvalues of the system at its equilibrium. In most cases, this estimate describes the rate of recovery only asymptotically, as time goes to infinity. However, in the short term, perturbations can grow significantly before they decay, and eigenvalues provide no information about this transient behavior. We present several new measures of transient response that complement resilience as a description of the response to perturbation. These indices measure the extent and duration of transient growth in models with asymptotically stable equilibria. They are the reactivity (the maximum possible growth rate immediately following the perturbation), the maximum amplification (the largest proportional deviation that can be produced by any perturbation), and the time at which this amplification occurs. We demonstrate the calculation of these indices using previously published linear compartment models (two models for phosphorus cycling through a lake ecosystem and one for the flow of elements through a tropical rain forest) and a standard nonlinear predator-prey model. Each of these models exhibits transient growth of perturbations, despite asymptotic stability. Measures of relative stability that ignore transient growth will often give a misleading picture of the response to a perturbation. Key words: compartment models; eigenvalues; pulse perturbations; reactivity; relative stability; resilience; return time; transient vs. asymptotic dynamics., INTRODUCTION Ecological systems are subject to continual perturbation. Their responses to perturbation are characterized qualitatively by stability (does the system return to its original state after perturbation, or does it [...]

I develop a general framework for natural and human values based on the position that end value is constructed by persons, but not wholly referent to them, identify and analyze three hierarchically related levels of end value in relation to the functional values which support them and the held and ascribed values generated by entities possessing teleological value, use this framework to indicate the context in which economic values should be located, and assess the implications of the framework for environmental policy and future valuation work.

Theories on spatial spread are utilized to predict the biological invasiveness of introduced or imported species and their potential impact in the native plant and animal ecology. Models of spatial spread such as simple reaction-diffusion models, complex reaction-diffusion models and discrete-time versions of reaction-diffusion models focused on asymptotic linear spread. However, more detailed models are needed to determine the connection between the initial and later stages of biological invasions.

A physical-biological model of phytoplankton explains the mechanism regulating plankton production and patchiness on the Georges Bank during summer. Tidal forcing forms a well-mixed region on the top of the bank, and tidal fronts at the bank edges. Biological fields are homogeneous on the bank and patches of phytoplankton develops in the fronts. The model predicts biomass and fluxes of biological variables that matches well with field measurements. Phytoplankton in the well-mixed region is nutrient replete and the patches in the fronts get vertical fluxes of nutrient from below the euphotic zone.

In this paper a revised version of Lettau's evapoclimatonomy model is introduced. Climatonomy is a one-dimensional representation of mean climate, which includes a complete characterization of the surface energy and water balances. The model is fundamentally forced by two input variables: incoming solar radiation and precipitation. All processes related to the ultimate distribution and exchange of the thereby available energy and moisture are parameterized. The goal of this paper is to describe the model's evolution and demonstrate its utility by sketching results of its application to several diverse climate problems in arid and semiarid Africa. Both the original and the revised evapoclimatonomy models are described, their conceptualization to that of more recent land-atmosphere interaction schemes is compared, their components in terms of the ecosystem are interpreted, and the model improvements incorporated in the current version are proposed. Finally, the use of the model in three applications to studies of climate and ecology in the Sahel and Kalahari regions of Africa is illustrated.