The utility of a digital simulation language for ecological modeling

Dynamic modeling of ecological phenomena has been greatly facilitated by the recent development of continuous system simulator programs. This paper illustrates the application of one of these programs, S/360 Continuous System Modeling Program (S/360 CSMP), to four systems of graduated complexity. The first is a two species system, with one feeding on the other, using differential equations with constant coefficients. The second and third systems involve two competing plant species in which the coefficients of the differential equations are varying with time. The final example considers the management of a postulated buffalo herd in which the dynamics of the herd population and composition by sex and age is combined with various strategies to control its size and to optimize buffalo production

A weather generator for hydrological, ecological, and agricultural applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95112/1/wrcr11029.pd

Daily minimum and maximum temperature simulation over complex terrain

Spatiotemporal simulation of minimum and maximum temperature is a fundamental requirement for climate impact studies and hydrological or agricultural models. Particularly over regions with variable orography, these simulations are difficult to produce due to terrain driven nonstationarity. We develop a bivariate stochastic model for the spatiotemporal field of minimum and maximum temperature. The proposed framework splits the bivariate field into two components of "local climate" and "weather." The local climate component is a linear model with spatially varying process coefficients capturing the annual cycle and yielding local climate estimates at all locations, not only those within the observation network. The weather component spatially correlates the bivariate simulations, whose matrix-valued covariance function we estimate using a nonparametric kernel smoother that retains nonnegative definiteness and allows for substantial nonstationarity across the simulation domain. The statistical model is augmented with a spatially varying nugget effect to allow for locally varying small scale variability. Our model is applied to a daily temperature data set covering the complex terrain of Colorado, USA, and successfully accommodates substantial temporally varying nonstationarity in both the direct-covariance and cross-covariance functions.Comment: Published in at http://dx.doi.org/10.1214/12-AOAS602 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

An early warning indicator for atmospheric blocking events using transfer operators

The existence of persistent midlatitude atmospheric flow regimes with time-scales larger than 5-10 days and indications of preferred transitions between them motivates to develop early warning indicators for such regime transitions. In this paper, we use a hemispheric barotropic model together with estimates of transfer operators on a reduced phase space to develop an early warning indicator of the zonal to blocked flow transition in this model. It is shown that, the spectrum of the transfer operators can be used to study the slow dynamics of the flow as well as the non-Markovian character of the reduction. The slowest motions are thereby found to have time scales of three to six weeks and to be associated with meta-stable regimes (and their transitions) which can be detected as almost-invariant sets of the transfer operator. From the energy budget of the model, we are able to explain the meta-stability of the regimes and the existence of preferred transition paths. Even though the model is highly simplified, the skill of the early warning indicator is promising, suggesting that the transfer operator approach can be used in parallel to an operational deterministic model for stochastic prediction or to assess forecast uncertainty

Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000-2009, 2046-2065 and 2081-2100, using the period of 1962-1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000-2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scale

Mitigating impacts of climate change in stream food webs

AbstractUnderstanding the effects of changing climates on the processes which support aquatic biodiversity is of critical importance for managing aquatic ecosystems. This research used an experimental approach to determine whether there are potential ecological surprises in terms of threshold relationships between climate and critical aquatic processes. These results were then placed in the context of the potential for riparian replanting to mitigate against these impacts.A review was carried out of climate change experiments in freshwaters, and revealed that the vast majority of studies have failed to take into account predicted increases in the frequency of extreme events (such as heatwaves) on biota. In order to include these components of changes in climate, a methodology was developed for downscaling global circulation models of climate change to generate realistic temperature data to use as an experimental treatment. Stream communities from the field were brought into experimental flumes and warmed according to the predictions of the down-scaled climate change models. Experiments were run for six weeks and responses were measured for basal processes (algal productivity and carbon dynamics) and aquatic invertebrate communities. Basal processes showed relatively small responses to the changed temperature regime, and appear to be relatively resistant for warming on the scale predicted under climate change scenarios for the next century. Aquatic invertebrate communities did show some responses, but these tended to be in terms of changes in size structure withion particular taxa rather than major impacts on patterns of biodiversity.The largest effects were seen for emerging adults of aquatic insects, were all species in the community responded in some way to our 2100 climate change treatment. Responses were species- and sex-specific. Males of all mayfly species emerged faster under 2100 temperatures compared to 1990-2000 temperatures. For the mayfly Ulmerophlebia pipinna (Leptophlebiidae), this implied a change in the sex ratio that could potentially compromise populations and, ultimately, lead to local extinctions. Furthermore, our results show a decrease in the overall community body size (average across taxa) due to a shift from bigger to smaller species.These results are in accord with the ecological rules dealing with the temperature-size relationships (in particular, Bergmann’s rule). Studies of streams in the field revealed that riparian vegetation did cool stream temperatures, and that the presence of riparian vegetation, ideally with extensive vegetation cover across the catchment, did appear to maintain higher diversity and abundance in stream invertebrate communities. Therefore it seems that restoring riparian vegetation does represent an effective means of adaptation to changing climates for temperate south eastern Australian freshwaters.Please cite this report as: Thompson, RM, Beardall, J, Beringer, J, Grace, M, Sardina, P 2013 Mitigating impacts of climate change on stream food webs: impacts of elevated temperature and CO2 on the critical processes underpinning resilience of aquatic ecosystems National Climate Change Adaptation Research Facility, Gold Coast, pp.136.Understanding the effects of changing climates on the processes which support aquatic biodiversity is of critical importance for managing aquatic ecosystems. This research used an experimental approach to determine whether there are potential ecological surprises in terms of threshold relationships between climate and critical aquatic processes. These results were then placed in the context of the potential for riparian replanting to mitigate against these impacts.A review was carried out of climate change experiments in freshwaters, and revealed that the vast majority of studies have failed to take into account predicted increases in the frequency of extreme events (such as heatwaves) on biota. In order to include these components of changes in climate, a methodology was developed for downscaling global circulation models of climate change to generate realistic temperature data to use as an experimental treatment. Stream communities from the field were brought into experimental flumes and warmed according to the predictions of the down-scaled climate change models. Experiments were run for six weeks and responses were measured for basal processes (algal productivity and carbon dynamics) and aquatic invertebrate communities. Basal processes showed relatively small responses to the changed temperature regime, and appear to be relatively resistant for warming on the scale predicted under climate change scenarios for the next century. Aquatic invertebrate communities did show some responses, but these tended to be in terms of changes in size structure withion particular taxa rather than major impacts on patterns of biodiversity.The largest effects were seen for emerging adults of aquatic insects, were all species in the community responded in some way to our 2100 climate change treatment. Responses were species- and sex-specific. Males of all mayfly species emerged faster under 2100 temperatures compared to 1990-2000 temperatures. For the mayfly Ulmerophlebia pipinna (Leptophlebiidae), this implied a change in the sex ratio that could potentially compromise populations and, ultimately, lead to local extinctions. Furthermore, our results show a decrease in the overall community body size (average across taxa) due to a shift from bigger to smaller species.These results are in accord with the ecological rules dealing with the temperature-size relationships (in particular, Bergmann’s rule). Studies of streams in the field revealed that riparian vegetation did cool stream temperatures, and that the presence of riparian vegetation, ideally with extensive vegetation cover across the catchment, did appear to maintain higher diversity and abundance in stream invertebrate communities. Therefore it seems that restoring riparian vegetation does represent an effective means of adaptation to changing climates for temperate south eastern Australian freshwaters

Regeneration in gap models: priority issues for studying forest responses to climate change

Recruitment algorithms in forest gap models are examined with particular regard to their suitability for simulating forest ecosystem responses to a changing climate. The traditional formulation of recruitment is found limiting in three areas. First, the aggregation of different regeneration stages (seed production, dispersal, storage, germination and seedling establishment) is likely to result in less accurate predictions of responses as compared to treating each stage separately. Second, the relatedassumptions that seeds of all species are uniformly available and that environmental conditions are homogeneous, are likely to cause overestimates of future species diversity and forest migration rates. Third, interactions between herbivores (ungulates and insect pests) and forest vegetation are a big unknown with potentially serious impacts in many regions. Possible strategies for developing better gap model representations for the climate-sensitive aspects of each of these key areas are discussed. A working example of a relatively new model that addresses some of these limitations is also presented for each case. We conclude that better models of regeneration processes are desirable for predicting effects of climate change, but that it is presently impossible to determine what improvements can be expected without carrying out rigorous tests for each new formulation