Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

Multi-metric evaluation of the models WARM,CropSyst, and WOFOST for rice

WARM (Water Accounting Rice Model) simulates paddy rice (Oryza sativa L.), based on temperature-driven development and radiation-driven crop growth. It also simulates: biomass partitioning, floodwater effect on temperature, spikelet sterility, floodwater and chemicals management, and soil hydrology. Biomass estimates from WARM were evaluated and compared with the ones from two generic crop models (CropSyst, WOFOST). The test-area was the Po Valley (Italy). Data collected at six sites from 1989 to 2004 from rice crops grown under flooded and non-limiting conditions were split into a calibration (to estimate some model parameters) and a validation set. For model evaluation, a fuzzy-logic based multiple-metrics indicator (MQI) was used: 0 (best) ≤ MQI ≤ 1 (worst). WARM estimates compared well with the actual data (mean MQI = 0.037 against 0.167 and 0.173 with CropSyst and WOFOST, respectively). On an average, the three models performed similarly for individual validation metrics such as modelling efficiency (EF > 0.90) and correlation coefficient (R > 0.98). WARM performed best in a weighed measure of the Akaike Information Criterion: (worst) 0<wk<1$0<w_k<1$ (best), considering estimation accuracy and number of parameters required to achieve it (mean wk=0.983$w_k=0.983$ against 0.007 and ∼0.000 with CropSyst and WOFOST, respectively). WARM results were sensitive to 30% of the model parameters (ratio being lower with both CropSyst, <10%, and WOFOST, <20%), but appeared the easiest model to use because of the lowest number of crop parameters required (10 against 15 and 34 with CropSyst and WOFOST, respectively). This study provides a concrete example of the possibilities offered using a range of assessment metrics to evaluate model estimates, predictive capabilities, and complexity.     

Modeling amphibian energetics, habitat suitability, and movements of western toads, Anaxyrus (=Bufo) boreas, across present and future landscapes

Effective conservation of amphibian populations requires the prediction of how amphibians use and move through a landscape. Amphibians are closely coupled to their physical environment. Thus an approach that uses the physiological attributes of amphibians, together with knowledge of their natural history, should be helpful. We used Niche Mapper™ to model the known movements and habitat use patterns of a population of Western toads (Anaxyrus (=Bufo) boreas) occupying forested habitats in southeastern Idaho. Niche Mapper uses first principles of environmental biophysics to combine features of topography, climate, land cover, and animal features to model microclimates and animal physiology and behavior across landscapes. Niche Mapper reproduced core body temperatures (T_c) and evaporation rates of live toads with average errors of 1.6 ± 0.4 °C and 0.8 ± 0.2 g/h, respectively. For four different habitat types, it reproduced similar mid-summer daily temperature patterns as those measured in the field and calculated evaporation rates (g/h) with an average error rate of 7.2 ± 5.5%. Sensitivity analyses indicate these errors do not significantly affect estimates of food consumption or activity. Using Niche Mapper we predicted the daily habitats used by free-ranging toads; our accuracy for female toads was greater than for male toads (74.2 ± 6.8% and 53.6 ± 15.8%, respectively), reflecting the stronger patterns of habitat selection among females. Using these changing to construct a cost surface, we also reconstructed movement paths that were consistent with field observations. The effect of climate warming on toads depends on the interaction of temperature and atmospheric moisture. If climate change occurs as predicted, results from Niche Mapper suggests that climate warming will increase the physiological cost of landscapes thereby limiting the activity for toads in different habitats.     

Parameter estimation for distributed delay based population models from laboratory data: egg hatching of Oulema duftschmidi Redthenbacher (Coleoptera,Chrysomelidae) as an example

The cohort development of poikilotherms under favorable temperature conditions may be described by the time-invariant distributed delay models that require three parameters, i.e. the thermal threshold T₀, the thermal constant W and the variability parameter H representing distributed maturation times, also known as time distributed or stochastic development. Here, a parsimonious method is developed that uses stage-frequency matrices obtained under controlled conditions. The analysis of these matrices permits the estimation of the three parameters, while the incorporation of both developmental threshold and thermal constant into the time-invariant distributed delay model permits the representation of stochastic cohort development under constant temperatures. The evaluated parameters can also be used in time-varying distributed delay models that are particularly useful for a wide range of fluctuating temperature conditions.We consider stage-frequency matrices obtained from cohorts of eggs and larvae of Oulema duftschmidi Redthenbacher at different constant temperatures. A visual inspection of the matrices clearly shows the temperature dependent as well as the time distributed passage from the egg to the larval stage. Under the current range of temperatures, a linear model for developmental rate satisfactorily describes egg development, and estimates the thermal threshold (T₀=11.2 °C), the thermal constant (W=81.3 day-degrees) and the delay order parameter (H=70). The resulting model can be used to represent the development of cohorts of O. duftschmidi eggs in a favorable temperature range.     

An individual-based model to study the reproduction of egg bearing copepods: Application to Eurytemora affinis (Copepoda Calanoida) from the Seine estuary,France

Limited empirical studies have elucidated the daily egg production and associated reproductive processes of egg bearing copepod. Herein, we present an individual-based model which constitutes a realistic representation of the reproduction in egg bearing copepods. The model has been parameterized using an extensive set of experimental data obtained from the literature and from the laboratory and field experiments on the estuarine copepod Eurytemora affinis. The proposed model takes into account the adult female longevity, the clutch size and interclutch duration, which is a function of egg maturation time and latency time required by the female after egg hatching to produce a new clutch. The embryonic development time and hatching success are also taken into account. The effect of temperature on the means and variances of above-mentioned reproductive parameters has been also incorporated. A multi agent system based generic platform “Mobidyc” has been used to generate and calibrate the model. The model demonstrates the reproductive parameters of females of E. affinis which is validated through individual based experiments. Temperature specific simulations provide a dynamical explanation of temperature effect on the cumulative egg production. The daily survival principally affects the number of clutches produced per female during its life span. The results obtained in the present study by combining temperature and survival effects reveal the relatively greater importance of the first factor on the daily egg production of egg-carrying copepods. The present model is generic and hence easily applicable to other animals with comparable reproductive strategy.     

La maturation sexuelle chez les mâles d'Octopus vulgaris (Cephalopoda: Octopoda), en relation avec le réflexe photo-sexuel

The role of light in induction of sexual maturation in male Octopus vulgaris has been studied on experimentals reared in the laboratory. Experiments were carried out during January, February and March, the time of the year when females do not breed or are just beginning to breed. Males (20 to 500 g) were artificially illuminated for 8 or 16 h/day or kept in complete darkness. Their gonads were compared with those of wild specimens killed a few hours after capture. In the Mediterranean Sea, under natural conditions, O. vulgaris males of less than 150 g never display sexual maturity; under our experimental conditions, young males from 70 g onwards, illuminated 16 h daily, show gonad development. Males of over 150 g, illuminated 16 h daily, have a larger number of spermatophores than wild specimens of individuals illuminated 8 h daily. O. vulgaris reared in complete darkness are sexually more mature than wild individuals. An hypothesis on induction of sexual maturation in the Cephalopoda is proposed.     

GIS-based modeling of the geographic distribution of Quercus emoryi Torr. (Fagaceae) in México and identification of significant environmental factors influencing the species’ distribution

The greatest concentration of oak species in the world is believed to be found in Mexico. These species are potentially useful for reforestation because of their capacity to adapt to diverse environments. Knowledge of their geographic distribution and of species–environment relations is essential for decision-making in the management and conservation of natural resources. The objectives of this study were to develop a model of the distribution of Quercus emoryi Torr. in Mexico, using geographic information systems and data layers of climatic and other variables, and to determine the variables that significantly influence the distribution of the species. The study consisted of the following steps: (A) selection of the target species from a botanical scientific collection, (B) characterization of the collecting sites using images with values or categories of the variables, (C) model building with the overlay of images that meet the habitat conditions determined from the characterization of sites, (D) model validation with independent data in order to determine the precision of the model, (E) model calibration through adjustment of the intervals of some variables, and (F) sensitivity analysis using precision and concordance non-parametric statistics applied to pairs of images. Results show that the intervals of the variables that best describe the species’ habitat are the following: altitude from 1650 to 2750 amsl, slope from 0 to 66°; average minimum temperature of January from −12 to −3 °C; mean temperature of June from 11 to 25 °C; mean annual precipitation from 218 to 1225 mm; soil units: lithosol, eutric cambisol, haplic phaeozem, chromic luvisol, rendzina, luvic xerosol, mollic planosol, pellic vertisol, eutric regosol; type of vegetation: oak forest, oak–pine forest, pine forest, pine–oak forest, juniperus forest, low open forest, natural grassland and chaparral. The resulting model of the geographic distribution of Quercus emoryi in Mexico had the following values for non-parametric statistics of precision and agreement: Kappa index of 0.613 and 0.788, overall accuracy of 0.806 and 0.894, sensitivity of 0.650 and 0.825, specificity of 0.963, positive predictive value of 0.945 and 0.957 and negative predictive value of 0.733 and 0.846. Results indicate that the variable average minimum temperature of January, with a maximum value of −3 °C, is an important factor in limiting the species’ distribution.     

The effect of estimated PAR uncertainties on the physiological processes of biosphere models

Photosynthetically active radiation (PAR) energy reaching on the vegetated surface is a key determinant of plant physiological processes. Most of biosphere or crop models use the ratio of PAR to incoming solar radiation (R_s), PAR/R_s, to convert R_s into PAR in order to reduce weather data-input requirements. Several existing models simply specify a constant ratio, PAR/R_s = 0.5. However, some field experiments have reported that the ratio PAR/R_s may not be constant. Previous empirical equations of PAR/R_s were derived based on the data of monthly or daily timescales collected from only a few measurement sites, hence they may not be appropriate to be used in current global biosphere models usually with hourly simulation time steps. Here, we represent the exponential correlation between PAR/R_s and sky clearness index (0-1) using hourly data from 54 Ameriflux measurement sites. It is found that PAR/R_s increases up to 0.6 in cloudy conditions when the clearness index (CI) is below ∼0.2, whereas it is nearly constant at ∼0.42 when CI is above 0.2. When the identified empirical equation is used in the model simulation, it results in −4 to 2% difference in the stomatal conductance compared to that using the constant ratio PAR/R_s = 0.5.     

A simple Lagrangian model to simulate temporal variability of algae in the Elbe River

We present a five-year (1997–2001) numerical simulation of daily mean chlorophyll a concentrations at station Geesthacht Weir on the lower Elbe River (Germany) using an extremely simple Lagrangian model driven by (a) water discharge, global radiation, water temperature, and (b) silica observations at station Schmilka in the upper reach of the Elbe River. Notwithstanding the lack of many mechanistic details, the model is able to reproduce observed chlorophyll a variability surprisingly well, including a number of sharp valleys and ascents/descents in the observed time series. The model's success is based on the assumption of three key effects: prevailing light conditions, sporadic limitation of algal growth due to lack of silica and algae loss rates that increase above an empirically specified temperature threshold of 20 °C. Trimmed-down model versions are studied to analyse the model's success in terms of these mechanisms.In each of the five years the model consistently fails, however, to properly simulate characteristic steep increases of chlorophyll a concentrations after pronounced spring minima. Curing this model deficiency by global model re-calibration was found to be impossible. However, suspension of silica consumption by algae for up to 10 days in spring is shown to serve as a successful placeholder for processes that are disregarded in the model but apparently play an important role in the distinctly marked period of model failure. For the remainder of the year the very simple model was found to be adequate.     

Climate, canopy conductance and leaf area development controls on evapotranspiration in a boreal coniferous forest over a 10-year period: A united model assessment

The aim of this work was to test a process-based model (hydrological model combined with forest growth model) on the simulation of seasonal variability of evapotranspiration (ET) in an even-aged boreal Scots pine (Pinus sylvestris L.) stand over a 10 year period (1999-2008). The water flux components (including canopy transpiration (E_t) and evaporation from canopy (E_c) and ground surface (E_g) were estimated in order to output the long-term stand water budget considering the interaction between climate variations and stand development. For validation, half-hourly data on eddy water vapor fluxes were measured during the 10 growing seasons (May-September). The model predicted well the seasonal course of ET compared to the measured values, but slightly underestimated the water fluxes both in non-drought and drought (2000, 2003 and 2006) years. The prediction accuracy was, on average, higher in drought years. The simulated ET over the 10 years explained, on average, 58% of the daily variations and 84% of the monthly amount of ET. Water amount from E_t contributed most to the ET, with the fractions of E_t, E_c and E_g being, on average, 67, 11 and 23% over the 10-year period, respectively. Regardless of weather conditions, the daily ET was strongly dependent on air temperature (T_a) and vapor pressure deficit (D_a), but less dependent on soil moisture (W_s). On cloudy and rainy days, there was a non-linear relationship between the ET and solar radiation (R_o). During drought years, the model predicted lower daily canopy stomatal conductance (g_cs) compared with non-drought years, leading to a lower level of E_t. The modeled daily g_cs responded well to D_a and W_s. In the model simulation, the annual LAI increased by 35% between 1999 and 2008. The ratio of E_c: ET correlated strongly with LAI. Furthermore, LAI reduced the proportion of E_g as a result of the increased share of E_c and E_t and radiation interception. Although the increase of LAI affected positively E_t, the contribution of E_t in ET was not significantly correlated with LAI. To conclude, although the model predicted reasonably well the seasonal course of ET, the calculation time steps of different processes in the model should be homogenized in the future to increase the prediction accuracy.     

COLIWAVE a simulation model for survival of E. coli O157:H7 in dairy manure and manure-amended soil

A simulation model was developed to investigate the relative effects of temperature, oxygen concentration, substrate content and competition by autochthonous microbial community on the oscillatory behaviour and survival of Escherichia coli O157:H7 in manure and manure-amended soil. The overall decline in E. coli O157:H7 was primarily determined by competition with autochthonous copiotrophic bacteria simulated by an inter-specific competition term according to Lotka-Volterra. Oscillations of bacterial populations were attained by the relationships between relative growth and death rates with readily available substrate content. The model contains a logistic and exponential relation of relative growth and death rates, respectively, of E. coli O157:H7 and copiotrophic bacteria with temperature, resulting in optimum curves for net growth rates similar to the curves reported in the literature. The model has been both calibrated and validated on experimental data. The model was used to perform sensitivity analysis and to evaluate different manure and soil management scenarios in terms of survival of E. coli O157:H7. The relative effects of changes in temperature on simulated survival time of E. coli O157:H7 were more pronounced than changes in oxygen condition. Testing manure storage scenarios with realistic data revealed that manure stored in a heap that was turned every week resulted in almost 70% reduction of E. coli O157:H7 survival compared to unturned manure. At the surface of a heap with unturned manure, simulated survival time was the longest (2.4 times longer than inside the same heap). The simulation model provides a new approach to investigating dynamic changes of invasive microorganisms in natural substrates such as manure or manure-amended soil.     

Application of a Random Forest algorithm to predict spatial distribution of the potential yield of Ruditapes philippinarum in the Venice lagoon, Italy

We present a modelling framework that combines machine learning techniques and Geographic Information Systems to support the management of an important aquaculture species, Manila clam (Ruditapes philippinarum). We use the Venice lagoon (Italy), the first site in Europe for the production of R. philippinarum, to illustrate the potential of this modelling approach. To investigate the relationship between the yield of R. philippinarum and a set of environmental factors, we used a Random Forest (RF) algorithm. The RF model was tuned with a large data set (n = 1698) and validated by an independent data set (n = 841). Overall, the model provided good predictions of site-specific yields and the analysis of marginal effect of predictors showed substantial agreement among the modelled responses and available ecological knowledge for R. philippinarum. The most influent environmental factors for yield estimation were percentage of sand in the sediment, salinity, and water depth. Our results agree with findings from other North Adriatic lagoons. The application of the fitted RF model to continuous maps of all the environmental variables allowed estimates of the potential yield for the whole basin. Such a spatial representation enabled site-specific estimates of yield in different farming areas within the lagoon. We present a possible management application of our model by estimating the potential yield under the current farming distribution and comparing it to a proposed re-organization of the farming areas. Our analysis suggests a reduction of total yield is likely to result from the proposed re-organization.     

Modeling seasonal course of carbon fluxes and evapotranspiration in response to low temperature and moisture in a boreal Scots pine ecosystem

Environmental conditions act above and below ground, and regulate carbon fluxes and evapotranspiration. The productivity of boreal forest ecosystems is strongly governed by low temperature and moisture conditions, but the understanding of various feedbacks between vegetation and environmental conditions is still unclear. In order to quantify the seasonal responses of vegetation to environmental factors, the seasonality of carbon and heat fluxes and the corresponding responses for temperature and moisture in air and soil were simulated by merging a process-based model (CoupModel) with detailed measurements representing various components of a forest ecosystem in Hyytiälä, southern Finland. The uncertainties in parameters, model assumptions, and measurements were identified by generalized likelihood uncertainty estimation (GLUE). Seasonal and diurnal courses of sensible and latent heat fluxes and net ecosystem exchange (NEE) of CO₂ were successfully simulated for two contrasting years. Moreover, systematic increases in efficiency of photosynthesis, water uptake, and decomposition occurred from spring to summer, demonstrating the strong coupling between processes. Evapotranspiration and NEE flux both showed a strong response to soil temperature conditions via different direct and indirect ecosystem mechanisms. The rate of photosynthesis was strongly correlated with the corresponding water uptake response and the light use efficiency. With the present data and model assumptions, it was not possible to precisely distinguish the various regulating ecosystem mechanisms. Our approach proved robust for modeling the seasonal course of carbon fluxes and evapotranspiration by combining different independent measurements. It will be highly interesting to continue using long-term series data and to make additional tests of optional stomatal conductance models in order to improve our understanding of the boreal forest ecosystem in response to climate variability and environmental conditions.     

Individual-based modeling of flooding and salinity effects on a coastal swamp forest

Coastal swamps are among the rapidly vanishing wetland habitats in Louisiana. Increased flooding, nutrient and sediment deprivation, and salt-water intrusion have been implicated as probable causes of the decline of coastal swamps. We developed a two-species individual-based forest succession model to compare the growth and composition of a cypress-tupelo swamp under various combinations of flooding intensity and salinity levels, using historical time-series of stage and salinity data as inputs. Our model simulates forest succession over 500 years by representing the growth, mortality, and reproduction of individual Taxodium distichum (baldcypress) and Nyssa aquatica (water tupelo) trees in a 1-km² spatial grid of 10 m × 10 m cells that vary in water levels and salinity through differences in elevation. We independently adjusted the elevations of each cell to obtain different grid-wide mean elevations and standard deviations of elevation; this affected the temporal and spatial pattern of flooding. We calibrated the model by adjusting selected parameters until averaged basal area, stem density and wood production rates under two different mean elevations (partially versus highly flooded) were qualitatively similar to comparable values reported for swamps in the literature. Corroboration involved comparing model predictions to four well-monitored contrasting habitat sites within the Maurepas Basin, Louisiana, USA. Model predictions of both species combined showed the same patterns among sites as the data, but the model overestimated wood production and the dominance of T. distichum. Exploratory simulations predicted that increased flooding leads to swamps with reduced basal areas and stem densities, while increased salinity resulted in lower basal areas at low salinity concentration (∼1-3 psu) and complete tree mortality at higher salinity concentrations (∼2-6 psu). Our model can provide insight into the succession dynamics of coastal swamps and information for the effective design of restoration actions.     

Inter-annual variability of ecosystem production in boreal jack pine forests (1975-2004) estimated from tree-ring data using CBM-CFS3

We describe and apply a method of using tree-ring data and an ecosystem model to reconstruct past annual rates of ecosystem production. Annual data on merchantable wood volume increment and mortality obtained by dendrochronological stand reconstruction were used as input to the Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) to estimate net ecosystem production (NEP), net primary production (NPP), and heterotrophic respiration (Rh) annually from 1975 to 2004 at 10 boreal jack pine (Pinus banksiana Lamb.) stands in Saskatchewan and Manitoba, Canada. From 1975 (when sites aged 41-60 years) to 2004 (when they aged 70-89 years), all sites were moderate C sinks except during some warmer than average years where estimated Rh increased. Across all sites and years, estimated annual NEP averaged 57 g Cm⁻² yr⁻¹ (range −31 to 176 g Cm⁻² yr⁻¹), NPP 244 g Cm⁻² yr⁻¹ (147-376 g Cm⁻² yr⁻¹), and Rh 187 g Cm⁻² yr⁻¹ (124-270 g Cm⁻² yr⁻¹). Across all sites, NPP was related to stand age and density, which are proxies for successional changes in leaf area. Regionally, warm spring temperature increased NPP and defoliation by jack pine budworm 1 year previously reduced NPP. Our estimates of NPP, Rh, and NEP were plausible when compared to regional eddy covariance and carbon stock measurements. Inter-annual variability in ecosystem productivity contributes uncertainty to inventory-based assessments of regional forest C budgets that use yield curves predicting averaged growth over time. Our method could expand the spatial and temporal coverage of annual forest productivity estimates, providing additional data for the development of empirical models accounting for factors not presently considered by these models.     

Estimating Plecoglossus altivelis altivelis migration using a mass balance model expressed by hydrological distribution parameters in a major limpid river basin in Japan

We examined the influence of several hydrological and meteorological parameters on the migratory movements of ayu Plecoglossus altivelis altivelis in central Japan. When comprehensively evaluating rivers and ayu behaviour on a catchment scale, the subjects of analysis typically include human activities and hydrological and meteorological phenomena. However, limiting analyses to such factors may be too restrictive when human activities are being conducted. Accordingly, we incorporated a biological viewpoint into the evaluation method, analysing hydrological data (river discharge, river water temperature, sea water temperature) to determine watershed characteristics and examining the relationship between these characteristics and the habitat conditions of ayu. Then we constructed a numerical model for ayu migratory runs that incorporated ayu ecology and watershed characteristics. Analyses of ayu movements from a lower estuarine dam demonstrated that downstream displacements were associated with high water flows of more than 200 m³ s⁻¹ at the beginning of summer. We conclude that it is important to consider the effects of environmental parameters on the movements of different fish species to understand the causes of spatial variation in fish distribution in lowland rivers.     

Towards carrying capacity assessment for aquaculture in the Bolinao Bay, Philippines: A numerical study of tidal circulation

The increase in intensive aquaculture production in the Bolinao Bay, Philippines reached the point of harmful influence to production stock. Up to the present, there has been no estimation of aquaculture carrying capacity which is based on quantification of processes responsible for (a) water quality inside the units, (b) impact to the seabed and (c) water quality in the whole Bolinao Bay. The numerical estimation of tidal circulation, which is the most dominant part of the hydrodynamical regime in the Bolinao Bay, represents an unavoidable step in the carrying capacity determination considering points (a), (b) and (c). The hydrodynamical model we apply is a free surface, 3D finite element tidal model, forced with sea elevation dynamics at three open boundaries. It incorporates an increase in bottom stress drag coefficients in the coral areas and advanced transport corrected advection scheme. The model simulations of water flow show good agreement with measured currents in the central part of the Bolinao Bay, southern and northeastern channel, while agreement in the areas in vicinity of northern channel is not as tight. In order to provide an insight into the water exchange in aquaculture units, to support local water quality models and seabed deposition models (points (a) and (b)), the area is mapped with neap tide mean, spring tide mean and 14-day mean current velocity contours. The highest 14-day mean velocities are attained in the southern channel (>17 cm s⁻¹), while the mean velocities characteristic for northern part (<6 cm s⁻¹) and shallow areas of coral reefs (<2 cm s⁻¹) are much lower. Area-mean difference between spring tide and 14-day mean velocities is estimated to be 18.32% (std=7.31%), while difference between neap tide and 14-day mean velocities is 17.62 % (std=11.19%). To support global basin-wide water quality models (point (c)), retention of water in the bay is estimated by Lagrangian and Eulerian calculation procedure of mean residence time field. Both calculations estimate the highest (no-wind) residence times (Lan: 25.4 days, Eul: 21.03 days) in the central northern part, but most of the area (Lan: 73.11%, Eul: 79.31%) is characterized by residence time values significantly lower than 15 days. The results are readily applicable for upcoming implementation in the models of local (aquaculture units, seabed) and basin-wide (Bolinao Bay) nutrient dynamics, primary and secondary production, organic matter decomposition and oxygen dynamics.     

Modelling llama population development under environmental and market constraints in the Bolivian highlands

Changes in the size of animal populations over time are mainly determined by demographic and environmental factors. Livestock population dynamics are additionally influenced by harvesting decisions taken by herders. In Bolivia, not much is known about current llama husbandry and the main influencing factors determining population sizes. We collected data on demography, environmental factors and market values affecting the current and future llama population in three different regions in Bolivia. We generated a population model and assessed the future development of the llama population including environmental factors (rangeland carrying capacity, disturbance phenomena), herd structure and dynamics, and economic market demands. We calibrated and validated the llama model on the basis of 20-year data sets of the regions of Oruro, Potosi and La Paz, respectively. Model calibration by means of the Gauss-Marquardt-Levenberg algorithm yielded a model efficiency of 0.94. For model validation, however, the simulation slightly overestimated the observed llama population yielding model efficiencies of 0.91 and 0.87 for Potosi and La Paz, respectively. Model outcomes were most sensitive to death and birth rates of juveniles and death rate of females compared to environmental or other demographic factors. Population trajectories approached an overall carrying capacity for Oruro, Potosi and La Paz of 8.8 × 10⁵, 9.1 × 10⁵, and 9.0 × 10⁵ llama individuals after 100 years of simulation. Hence, detailed monitoring of demographic, environmental, and economic factors can improve predictions of llama population development over time. Further management should focus on improving birth rates and lowering female mortality through providing supplemental food and shelters against the harsh environmental conditions of the Andean highlands.     

Dissolved organic carbon concentrations and fluxes in forest catchments and streams: DOC-3 model

Dissolved organic carbon (DOC) concentrations in south-western Nova Scotia streams, sampled at weekly to biweekly intervals, varied across streams from about 3 to 40 mg L⁻¹, being highest mid-summer to fall, and lowest during winter to spring. A 3-parameter model (DOC-3) was proposed to project daily stream DOC concentrations and fluxes from modelled estimates for daily soil temperature and moisture, year-round, and in relation to basin size and wetness. The parameters of this model refer to (i) a basin-specific DOC release parameter “k_DOC^”, related to the wet- and open-water area percentages per basin, (ii) the lag time “τ” between DOC production and subsequent stream DOC emergence, related to the catchment area above the stream sampling location; and (iii) the activation energy “Ea”, to deal with the temperature effect on DOC production. This model was calibrated with the 1988-2006 DOC concentration data from three streams (Pine Marten, Moosepit Brook, and the Mersey River sampled at or near Kejimkujik National Park, or KNP), and was used to interpret the biweekly 1999-2003 DOC concentrations data (stream, ground and lake water, soil lysimeters) of the Pockwock-Bowater Watershed Project near Halifax, Nova Scotia. The data and the model revealed that the DOC concentrations within the streams were not correlated to the DOC concentrations within the soil- and groundwater, but were predictable based on (i) the hydrologically inferred weather-induced changes in soil moisture and temperature next to each stream, and (ii) the topographically inferred basin area and wet- and open-water area percentages associated with each stream (R² = 0.53; RMSE = 3.5 mg L⁻¹). Model-predicted fluxes accounted 74% of the hydrometrically determined DOC exports at KNP.     

Mechanisms of moisture stress in a mid-latitude temperate forest: Implications for feedforward and feedback controls from an irrigation experiment

While it is well established that stomata close during moisture stress, strong correlations among environmental (e.g., vapor pressure deficit, soil moisture, air temperature, radiation) and internal (e.g., leaf water potential, sap flow, root-shoot signaling) variables obscure the identification of causal mechanisms from field experiments. Models of stomatal control fitted to field data therefore suffer from ambiguous parameter identification, with multiple acceptable (i.e., nearly optimal) model structures emphasizing different moisture status indicators and different processes. In an effort to minimize these correlations and improve parameter and process identification, we conducted an irrigation experiment on red maples (Acer rubrum L.) at Harvard Forest (summers of 2005 and 2006). Control and irrigated trees experienced similar radiative and boundary layer forcings, but different soil moisture status, and thus presumably different diurnal cycles of internal leaf water potential. Measured soil moisture and atmospheric forcing were used to drive a transient tree hydraulic model that incorporated a Jarvis-type leaf conductance in a Penman–Monteith framework with a Cowan-type (resistance and capacitance) tree hydraulic representation. The leaf conductance model included dependence on both leaf matric potential, Ψ_L (so-called feedback control) and on vapor pressure deficit, D (so-called feedforward control). Model parameters were estimated by minimizing the error between predicted and measured sap flow. The whole-tree irrigation treatment had the effect of elevating measured transpiration during summer dry-downs, demonstrating the limiting effect that subsurface resistance may have on transpiration during these times of moisture stress. From the best fitted model, we infer that during dry downs, moisture stress manifests itself in an increase of soil resistance with a resulting decrease in Ψ_L, leading to both feedforward and feedback controls in the control trees, but only feedforward control for the irrigated set. Increases in the sum-of-squares error when individual model components were disabled allow us to reject the following three null hypotheses: (1) the f(D) stress is statistically insignificant (p = 0.01); (2) the f(Ψ_L) stress is statistically insignificant (p = 0.07); and (3) plant storage capacitance is independent of moisture status (p = 0.07).