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.     

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.     

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.     

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.     

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.     

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).     

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.     

Interpreting spatial heterogeneity of crop yield with a process model and remote sensing

A process-based crop growth model (Vegetation Interface Processes (VIP) model) is used to estimate crop yield with remote sensing over the North China Plain. Spatial pattern of the key parameter—maximum catalytic capacity of Rubisco (V_cmax) for assimilation is retrieved from Normalized Difference of Vegetation Index (NDVI) from Terra-MODIS and statistical yield records. The regional simulation shows that the agreements between the simulated winter wheat yields and census data at county-level are quite well with R² being 0.41-0.50 during 2001-2005. Spatial variability of photosynthetic capacity and yield in irrigated regions depend greatly on nitrogen input. Due to the heavy soil salinity, the photosynthetic capacity and yield in coastal region is less than 50 μmol C m⁻² s⁻¹ and 3000 kg ha⁻¹, respectively, which are much lower than that in non-salinized region, 84.5 μmol C m⁻² s⁻¹ and 5700 kg ha⁻¹. The predicted yield for irrigated wheat ranges from 4000 to 7800 kg ha⁻¹, which is significantly larger than that of rainfed, 1500-3000 kg ha⁻¹. According to the path coefficient analysis, nitrogen significantly affects yield, by which water exerts noticeably indirect influences on yield. The effect of water on yield is regulated, to a certain extent, by crop photosynthetic capacity and nitrogen application. It is believed that photosynthetic parameters retrieved from remote sensing are reliable for regional production prediction with a process-based model.     

Relationships between simulated water stress and mortality and growth rates in underplanted Toona ciliata Roem. in subtropical Argentinean plantations

Toona ciliata Roem. (Australian red cedar) requires a nurse-tree overstory to prevent damage from drought and irradiation in some regions of north-eastern Argentina. T. ciliata was planted in the understory of Pinus taeda L. (625 stems/ha), Pinus elliottii Engelm. × Pinus caribaea Morelet (625 stems/ha), and Grevillea robusta A. Cunn. (833 stems/ha) nurse trees, which were thinned to 0, 25, 50, 75 and 100% of the initial densities. We measured initial T. ciliata mortality and growth as well as Leaf Area Index (LAI) based on light transmission. T. ciliata soil water availability and its effect on early growth and mortality were examined by modelling drought stress using the two-dimensional forest hydrology model ForWaDy. Simulated patterns in T. ciliata water stress for the different overstory treatments were consistent with observed patterns of mortality. Early mortality was lowest with a G. robusta overstory, with corresponding lowest drought stress values and high modelled soil water contents in the top soil layer in intermediate and high overstory densities. Mortality was highest with a P. elliottii × P. caribaea overstory in treatments with the highest modelled drought stress values in the most open treatments. The model supported our field observations by indicating that water stress was an important limitation to T. ciliata survival and growth on our study sites. The linkage between T. ciliata establishment success, early growth and soil water availability as indicated by ForWaDy, leads us to conclude that the model is a suitable stand management tool for guiding establishment of T. ciliata plantations.     

Sanitary felling of Norway spruce due to spruce bark beetles in Slovenia: A model and projections for various climate change scenarios

A model is presented to predict sanitary felling of Norway spruce (Picea abies) due to spruce bark beetles (Ips typographus, Pityogenes chalcographus) in Slovenia according to different climate change scenarios. The model incorporates 21 variables that are directly or indirectly related to the dependent variable, and that can be arranged into five groups: climate, forest, landscape, topography, and soil. The soil properties are represented by 8 variables, 4 variables define the topography, 4 describe the climate, 4 define the landscape, and one additional variable provides the quantity of Norway spruce present in the model cell. The model was developed using the M5′ model tree. The basic spatial unit of the model is 1 km², and the time resolution is 1 year. The model evaluation was performed by three different measures: (1) the correlation coefficient (51.9%), (2) the Theil's inequality coefficient (0.49) and (3) the modelling efficiency (0.32). Validation of the model was carried out by 10-fold cross-validation. The model tree consists of 28 linear models, and model was calculated for three different climate change scenarios extending over a period until 2100, in 10-year intervals. The model is valid for the entire area of Slovenia; however, climate change projections were made only for the Maribor region (596 km²). The model assumes that relationships among the incorporated factors will remain unchanged under climate change, and the influence of humans was not taken into account. The structure of the model reveals the great importance of landscape variables, which proved to be positively correlated with the dependent variable. Variables that describe the water regime in the model cell were also highly correlated with the dependent variable, with evapotranspiration and parent material being of particular importance. The results of the model support the hypothesis that bark beetles do greater damage to Norway spruce artificially planted out of its native range in Slovenia, i.e., lowlands and soils rich in N, P, and K. The model calculation for climate change scenarios in the Maribor region shows an increase in sanitary felling of Norway spruce due to spruce bark beetles, for all scenarios. The model provides a path towards better understanding of the complex ecological interactions involved in bark beetle outbreaks. Potential application of the results in forest management and planning is discussed.     

Modelling habitat overlap among sympatric mesocarnivores in southern Illinois,USA

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

Epidemiological risk assessment using linked network and grid based modelling: Phytophthora ramorum and Phytophthora kernoviae in the UK

We developed a stochastic simulation model incorporating most processes likely to be important in the spread of Phytophthora ramorum and similar diseases across the British landscape (covering Rhododendron ponticum in woodland and nurseries, and Vaccinium myrtillus in heathland). The simulation allows for movements of diseased plants within a realistically modelled trade network and long-distance natural dispersal. A series of simulation experiments were run with the model, representing an experiment varying the epidemic pressure and linkage between natural vegetation and horticultural trade, with or without disease spread in commercial trade, and with or without inspections-with-eradication, to give a 2 × 2 × 2 × 2 factorial started at 10 arbitrary locations spread across England. Fifty replicate simulations were made at each set of parameter values. Individual epidemics varied dramatically in size due to stochastic effects throughout the model. Across a range of epidemic pressures, the size of the epidemic was 5–13 times larger when commercial movement of plants was included. A key unknown factor in the system is the area of susceptible habitat outside the nursery system. Inspections, with a probability of detection and efficiency of infected-plant removal of 80% and made at 90-day intervals, reduced the size of epidemics by about 60% across the three sectors with a density of 1% susceptible plants in broadleaf woodland and heathland. Reducing this density to 0.1% largely isolated the trade network, so that inspections reduced the final epidemic size by over 90%, and most epidemics ended without escape into nature. Even in this case, however, major wild epidemics developed in a few percent of cases. Provided the number of new introductions remains low, the current inspection policy will control most epidemics. However, as the rate of introduction increases, it can overwhelm any reasonable inspection regime, largely due to spread prior to detection.     

A system dynamics model for the management of the Manila clam, Ruditapes philippinarum (Adams and Reeve, 1850) in the Bay of Arcachon (France)

The Manila clam Ruditapes philippinarum (Adams and Reeve, 1850) is one of the mollusc species that, driven mainly by the shellfish market industry, has extended throughout the world, far beyond the limits of its original habitat. The Manila clam was introduced into France for aquaculture purposes, between 1972 and 1975. In France, this venerid culture became increasingly widespread and, since 1988, this species has colonised most of the embayments along the French Atlantic coast. In 2004, this development resulted in a fishery of ca. 520 t in Arcachon Bay.     

Deriving state-and-transition models from an image series of grassland pattern dynamics

We present how state-and-transition models (STMs) may be derived from image data, providing a graphical means of understanding how ecological dynamics are driven by complex interactions among ecosystem events. A temporal sequence of imagery of fine scale vegetation patterning was acquired from close range photogrammetry (CRP) of 1 m quadrats, in a long term monitoring project of Themeda triandra (Forsskal) grasslands in north western Australia. A principal components scaling of image metrics calculated on the imagery defined the state space of the STM, and thereby characterised the different patterns found in the imagery. Using the state space, we were able to relate key events (i.e. fire and rainfall) to both the image data and aboveground biomass, and identified distinct ecological ‘phases’ and ‘transitions’ of the system. The methodology objectively constructs a STM from imagery and, in principle, may be applied to any temporal sequence of imagery captured in any event-driven system. Our approach, by integrating image data, addresses the labour constraint limiting the extensive use of STMs in managing vegetation change in arid and semiarid rangelands.     

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.     

Waterfowls habitat modeling: Simulation of nest site selection for the migratory Little Tern (Sterna albifrons) in the Nakdong estuary

This paper aims to find patterns in nest site selection by Little Terns Sterna albifrons, in the Nakdong estuary in South Korea. This estuary is important waterfowl stopover and breeding habitat, located in the middle of the East Asia-Australasian Flyway. The Little Tern is a common species easily observed near the seashore but their number is gradually declining around the world. We investigated their nests and eggs on a barrier islet in the Nakdong estuary during the breeding season (May to June, 2007), and a pattern for the nest site selection was identified using genetic programming (GP). The GP generated a predictive rule-set model for the number of Little Tern nests (training: R² = 0.48 and test: 0.46). The physical features of average elevation, variation of elevation, plant coverage, and average plant height were estimated to determine the influence on nest numbers for Little Tern. A series of sensitivity analyses stressed that mean elevation and vegetation played an important role in nest distribution for Little Tern. The influence of these two variables could be maximized when elevation changed moderately within the sampled quadrats. The study results are regarded as a good example of applying GP to vertebrate distribution patterning and prediction with several important advantages compared to conventional modeling techniques, and can help establish a management or restoration strategy for the species.     

Ecological role of stomatopods (mantis shrimps) and potential impacts of trawling in a marine ecosystem of the southeast coast of India

Ecosystems are balanced by nature and each component in the system has a role in the sustenance of other components. A change in one component would invariably have an effect on others. Stomatopods (mantis shrimps) are common and ecologically important predatory crustaceans in tropical marine waters. The ecological role of mantis shrimps and potential impacts of trawling in a marine ecosystem were estimated using Ecopath with Ecosim (EwE) Version 5.0 software, by constructing a mass balanced Ecopath model of Parangipettai (Porto Novo) ecosystem. Based on fisheries information from the region, 17 ecological groups were defined including stomatopods. Both primary and secondary data on biomass, P/B, Q/B and diet composition were used as basic inputs. The mass balanced model gave a total system throughput of 14,756 t km⁻² year⁻¹. The gross efficiency of 0.000942 indicated higher contribution of lower food chain groups in the fishery though the mean trophic level was 3.08. The immature and developing stage of the ecosystem was indicated by the ratio of total primary production and total respiration (1.832) and the net system production (2643.30 t km⁻² year⁻¹). Key indices (flow to detritus, net efficiency and omnivory index), split mortality rates and mixed trophic impact of different ecological groups were obtained from the model. A flow diagram was constructed to illustrate the trophic interactions, which explained the biomass flows in the ecosystem with reference to stomatopods. Two temporal simulations were made, with 10 year durations in the mass balanced Ecopath model by using ecosim routine incorporated in EwE software. The effect of decrease in biomass of stomatopods in the ecosystem was well defined, in the first run with increase in stomatopod fishing mortality, and the group showed a high positive impact on benthopelagic fish biomass increase (129%). The simulation with increase in trawling efforts resulted in the biomass decline of different ecological groups as elasmobranchs to 1%, stomatopods to 2%, crabs and lobsters to 36%, cephalopods to 63%, mackerel to 78%, and shrimps to 89%. Present study warns stomatopod discards and further increase in trawling efforts in the region and it explained the need for ecosystem based fisheries management practices for the sustainability of marine fisheries.     

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.     

Modeling net primary production of a fast-growing forest using a light use efficiency model

As interest grows in the quantification of global carbon cycles, Light Use Efficiency (LUE) model predictions of the forest net primary production (NPP) are being developed at an accelerating rate. Such models can provide useful predictions at large scales, but evaluating their performance has been difficult. In this study, a remote sensing-based LUE model was established to estimate forest NPP. Using the forest inventory data (FID) from the regional forest inventory survey in China and established allometric biomass equations, we calculated the biomass, the biomass increment, and the NPP of Eucalyptus urophylla (E. urophylla) plantation plots in the forestry jurisdiction of the Leizhou Forestry Bureau, Southern China. The FID-based NPP and the NPP from LUE model predictions were then compared to each other. Results show that the NPP from model predictions at a spatial resolution of 30 m × 30 m varied from 0 to 265 gC/(m² month) and showed regional differences. In addition, the stand age had variable effects on the average individual biomass of the E. urophylla plantation plots. The average individual biomass of the young and mid-age forests increased exponentially and logarithmically with the stand age (R² = 0.9178 and R² = 0.8683), respectively. For young and mid-age E. urophylla plantation plots, the LUE model-predicted NPP was fairly consistent with the FID-based NPP, but the model predictions of the NPP were higher than the estimates from FID. Through the analysis of the causes of uncertainty and the possible reasons for the discrepancy between the model-based NPP and FID-based NPP, the FID-derived estimates provided a foundation for model evaluation.     

On the sudden disappearance of Egeria densa from a Ramsar wetland site of Southern Chile: A climatic event trigger model

Contemporary shallow lakes theory proposes that these ecosystems may experience abrupt regime shifts due to small changes in controlling variables or triggers. So far, these triggers have been related mostly to nutrients as the immediate driver. During May 2004 the río Cruces wetland, a Ramsar site located in Southern Chile, underwent a major regime shift, from a clear water state, vastly dominated by the invasive macrophyte Egeria densa, to a turbid water state. In this article we show, through the analysis of long-term meteorological data that late fall 2004 was anomalous due to the presence of a high-pressure cell that persisted most of the month of May over Southern Chile. This climatic event caused an almost complete absence of precipitations and lower temperatures during this period, including several freezing nights. Eco-physiological experiments showed that 6 h exposure to desiccation kill the macrophyte. We developed a simple-biology dynamic model, under Stella Research 9.1, to show that the climatic anomaly of May 2004, plus the increased sedimentation of the wetland's floodplains, and the associated response of E. densa, explains its sudden disappearance from río Cruces wetland.