Abundance of introduced species at home predicts abundance away in herbaceous communities

Many ecosystems worldwide are dominated by introduced plant species, leading to loss of biodiversity and ecosystem function. A common but rarely tested assumption is that these plants are more abundant in introduced vs. native communities, because ecological or evolutionary-based shifts in populations underlie invasion success. Here, data for 26 herbaceous species at 39 sites, within eight countries, revealed that species abundances were similar at native (home) and introduced (away) sites – grass species were generally abundant home and away, while forbs were low in abundance, but more abundant at home. Sites with six or more of these species had similar community abundance hierarchies, suggesting that suites of introduced species are assembling similarly on different continents. Overall, we found that substantial changes to populations are not necessarily a pre-condition for invasion success and that increases in species abundance are unusual. Instead, abundance at home predicts abundance away, a potentially useful additional criterion for biosecurity programmes.

Life-history constraints in grassland plant species : a growth-defence trade-off is the norm

Plant growth can be limited by resource acquisition and defence against consumers, leading to contrasting trade-off possibilities. The competition-defence hypothesis posits a trade-off between competitive ability and defence against enemies (e.g. herbivores and pathogens). The growth-defence hypothesis suggests that strong competitors for nutrients are also defended against enemies, at a cost to growth rate. We tested these hypotheses using observations of 706 plant populations of over 500 species before and following identical fertilisation and fencing treatments at 39 grassland sites worldwide. Strong positive covariance in species responses to both treatments provided support for a growth-defence trade-off: populations that increased with the removal of nutrient limitation (poor competitors) also increased following removal of consumers. This result held globally across 4 years within plant life-history groups and within the majority of individual sites. Thus, a growth-defence trade-off appears to be the norm, and mechanisms maintaining grassland biodiversity may operate within this constraint.

Anthropogenic-based regional-scale factors most consistently explain plot-level exotic diversity in grasslands

Aim Evidence linking the accumulation of exotic species to the suppression of native diversity is equivocal, often relying on data from studies that have used different methods. Plot-level studies often attribute inverse relationships between native and exotic diversity to competition, but regional abiotic filters, including anthropogenic influences, can produce similar patterns.We seek to test these alternatives using identical scale-dependent sampling protocols in multiple grasslands on two continents. Location Thirty-two grassland sites in North America and Australia. Methods We use multiscale observational data, collected identically in grain and extent at each site, to test the association of local and regional factors with the plot-level richness and abundance of native and exotic plants. Sites captured environmental and anthropogenic gradients including land-use intensity, human population density, light and soil resources, climate and elevation. Site selection occurred independently of exotic diversity, meaning that the numbers of exotic species varied randomly thereby reducing potential biases if only highly invaded sites were chosen. Results Regional factors associated directly or indirectly with human activity had the strongest associations with plot-level diversity. These regional drivers had divergent effects: urban-based economic activity was associated with high exotic : native diversity ratios; climate- and landscape-based indicators of lower human population density were associated with low exotic : native ratios. Negative correlations between plot-level native and exotic diversity, a potential signature of competitive interactions, were not prevalent; this result did not change along gradients of productivity or heterogeneity. Main conclusion We show that plot-level diversity of native and exotic plants are more consistently associatedwith regional-scale factors relating to urbanization and climate suitability than measures indicative of competition. These findings clarify the long-standing difficulty in resolving drivers of exotic diversity using single-factor mechanisms, suggesting that multiple interacting anthropogenic-based processes best explain the accumulation of exotic diversity in modern landscapes.

Anthropogenic nitrogen deposition predicts local grassland primary production worldwide

Humans dominate many important Earth system processes including the nitrogen (N) cycle. Atmospheric N deposition affects fundamental processes such as carbon cycling, climate regulation, and biodiversity, and could result in changes to fundamental Earth system processes such as primary production. Both modelling and experimentation have suggested a role for anthropogenically altered N deposition in increasing productivity, nevertheless, current understanding of the relative strength of N deposition with respect to other controls on production such as edaphic conditions and climate is limited. Here we use an international multiscale data set to show that atmospheric N deposition is positively correlated to aboveground net primary production (ANPP) observed at the 1-m2 level across a wide range of herbaceous ecosystems. N deposition was a better predictor than climatic drivers and local soil conditions, explaining 16% of observed variation in ANPP globally with an increase of 1 kg N·ha-1·yr-1 increasing ANPP by 3%. Soil pH explained 8% of observed variation in ANPP while climatic drivers showed no significant relationship. Our results illustrate that the incorporation of global N deposition patterns in Earth system models are likely to substantially improve estimates of primary production in herbaceous systems. In herbaceous systems across the world, humans appear to be partially driving local ANPP through impacts on the N cycle.

Forecasting Daily Chlorophyll a Concentration during the Spring Phytoplankton Bloom Period in Xiangxi Bay of the Three-Gorges Reservoir by Means of a Recurrent Artificial Neural Network

A recurrent artificial neural network was used for 0-and 7-days-ahead forecasting of daily spring phytoplankton bloom dynamics in Xiangxi Bay of Three-Gorges Reservoir with meteorological, hydrological, and limnological parameters as input variables. Daily data from the depth of 0.5 m was used to train the model, and data from the depth of 2.0 m was used to validate the calibrated model. The trained model achieved reasonable accuracy in predicting the daily dynamics of chlorophyll a both in 0-and 7-days-ahead forecasting. In 0-day-ahead forecasting, the R-2 values of observed and predicted data were 0.85 for training and 0.89 for validating. In 7-days-ahead forecasting, the R-2 values of training and validating were 0.68 and 0.66, respectively. Sensitivity analysis indicated that most ecological relationships between chlorophyll a and input environmental variables in 0-and 7-days-ahead models were reasonable. In the 0-day model, Secchi depth, water temperature, and dissolved silicate were the most important factors influencing the daily dynamics of chlorophyll a. And in 7-days-ahead predicting model, chlorophyll a was sensitive to most environmental variables except water level, DO, and NH3N.

Relating sardine recruitment in the Northern Benguela to satellite-derived sea surface height using a neural network pattern recognition approach

Processes of enrichment, concentration and retention are thought to be important for the successful recruitment of small pelagic fish in upwelling areas, but are difficult to measure. In this study, a novel approach is used to examine the role of spatio-temporal oceanographic variability on recruitment success of the Northern Benguela sardine Sardinops sagax. This approach applies a neural network pattern recognition technique, called a self-organising map (SOM), to a seven-year time series of satellite-derived sea level data. The Northern Benguela is characterised by quasi-perennial upwelling of cold, nutrient-rich water and is influenced by intrusions of warm, nutrient-poor Angola Current water from the north. In this paper, these processes are categorised in terms of their influence on recruitment success through the key ocean triad mechanisms of enrichment, concentration and retention. Moderate upwelling is seen as favourable for recruitment, whereas strong upwelling, weak upwelling and Angola Current intrusion appear detrimental to recruitment success. The SOM was used to identify characteristic patterns from sea level difference data and these were interpreted with the aid of sea surface temperature data. We found that the major oceanographic processes of upwelling and Angola Current intrusion dominated these patterns, allowing them to be partitioned into those representing recruitment favourable conditions and those representing adverse conditions for recruitment. A marginally significant relationship was found between the index of sardine recruitment and the frequency of recruitment favourable conditions (r super(2) = 0.61, p = 0.068, n = 6). Because larvae are vulnerable to environmental influences for a period of at least 50 days after spawning, the SOM was then used to identify windows of persistent favourable conditions lasting longer than 50 days, termed recruitment favourable periods (RFPs). The occurrence of RFPs was compared with back-calculated spawning dates for each cohort. Finally, a comparison of RFPs with the time of spawning and the index of recruitment showed that in years where there were 50 or more days of favourable conditions following spawning, good recruitment followed (Mann-Whitney U-test: p = 0.064, n = 6). These results show the value of the SOM technique for describing spatio-temporal variability in oceanographic processes. Variability in these processes appears to be an important factor influencing recruitment in the Northern Benguela sardine, although the available data time series is currently too short to be conclusive. Nonetheless, the analysis of satellite data, using a neural network pattern-recognition approach, provides a useful framework for investigating fisheries recruitment problems.

Development and Deployment of Wireless Sensor Network in Paddy Fields of Kuttanad

The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.

Predicting body and carcass characteristics of 2 broiler chicken strains using support vector regression and neural network models

As a new modeling method, support vector regression (SVR) has been regarded as the state-of-the-art technique for regression and approximation. In this study, the SVR models had been introduced and developed to predict body and carcass-related characteristics of 2 strains of broiler chicken. To evaluate the prediction ability of SVR models, we compared their performance with that of neural network (NN) models. Evaluation of the prediction accuracy of models was based on the R-2, MS error, and bias. The variables of interest as model output were BW, empty BW, carcass, breast, drumstick, thigh, and wing weight in 2 strains of Ross and Cobb chickens based on intake dietary nutrients, including ME (kcal/bird per week), CP, TSAA, and Lys, all as grams per bird per week. A data set composed of 64 measurements taken from each strain were used for this analysis, where 44 data lines were used for model training, whereas the remaining 20 lines were used to test the created models. The results of this study revealed that it is possible to satisfactorily estimate the BW and carcass parts of the broiler chickens via their dietary nutrient intake. Through statistical criteria used to evaluate the performance of the SVR and NN models, the overall results demonstrate that the discussed models can be effective for accurate prediction of the body and carcass-related characteristics investigated here. However, the SVR method achieved better accuracy and generalization than the NN method. This indicates that the new data mining technique (SVR model) can be used as an alternative modeling tool for NN models. However, further reevaluation of this algorithm in the future is suggested.

Phenol biodegradation by a microbial consortium: application of artificial neural network (ANN) modelling

In this study, an effective microbial consortium for the biodegradation of phenol was grown under different operational conditions, and the effects of phosphate concentration (1.4 g L-1, 2.8 g L-1, 4.2 g L-1), temperature (25 degrees C, 30 degrees C, 35 degrees C), agitation (150 rpm, 200 rpm, 250 rpm) and pH (6, 7, 8) on phenol degradation were investigated, whereupon an artificial neural network (ANN) model was developed in order to predict degradation. The learning, recall and generalization characteristics of neural networks were studied using data from the phenol degradation system. The efficiency of the model generated by the ANN was then tested and compared with the experimental results obtained. In both cases, the results corroborate the idea that aeration and temperature are crucial to increasing the efficiency of biodegradation.

Wiring the Vascular Network with Neural Cues: A CNS Perspective

The vascular and the nervous system are responsible for oxygen, nutrient, and information transfer and thereby constitute highly important communication systems in higher organisms. These functional similarities are reflected at the anatomical, cellular, and molecular levels, where common developmental principles and mutual crosstalks have evolved to coordinate their action. This resemblance of the two systems at different levels of complexity has been termed the "neurovascular link." Most of the evidence demonstrating neurovascular interactions derives from studies outside the CNS and from the CNS tissue of the retina. However, little is known about the specific properties of the neurovascular link in the brain. Here, we focus on regulatory effects of molecules involved in the neurovascular link on angiogenesis in the periphery and in the brain and distinguish between general and CNS-specific cues for angiogenesis. Moreover, we discuss the emerging molecular interactions of these angiogenic cues with the VEGF-VEGFR-Delta-like ligand 4 (Dll4)-Jagged-Notch pathway.

Seawater carbonate chemistry and nutrient fluxes during experiments with brittlestar Amphiura filiformis, 2009

Rising levels of atmospheric carbon dioxide and the concomitant increased uptake of this by the oceans is resulting in hypercapnia-related reduction of ocean pH. Research focussed on the direct effects of these physicochemical changes on marine invertebrates has begun to improve our understanding of impacts at the level of individual physiologies. However, CO2-related impairment of organisms' contribution to ecological or ecosystem processes has barely been addressed. The burrowing ophiuroid Amphiura filiformis, which has a physiology that makes it susceptible to reduced pH, plays a key role in sediment nutrient cycling by mixing and irrigating the sediment, a process known as bioturbation. Here we investigate the role of A. filiformis in modifying nutrient flux rates across the sediment-water boundary and the impact of CO2- related acidification on this process. A 40 day exposure study was conducted under predicted pH scenarios from the years 2100 (pH 7.7) and 2300 (pH 7.3), plus an additional treatment of pH 6.8. This study demonstrated strong relationships between A. filiformis density and cycling of some nutrients; activity increases the sediment uptake of phosphate and the release of nitrite and nitrate. No relationship between A. filiformis density and the flux of ammonium or silicate were observed. Results also indicated that, within the timescale of this experiment, effects at the individual bioturbator level appear not to translate into reduced ecosystem influence. However, long term survival of key bioturbating species is far from assured and changes in both bioturbation and microbial processes could alter key biogeochemical processes in future, more acidic oceans.

Seawater carbonate chemistry, nutrient uptake and biological processes of coral Stylophora pistillata during experiments, 2011

The effects of ocean acidification and elevated seawater temperature on coral calcification and photosynthesis have been extensively investigated over the last two decades, whereas they are still unknown on nutrient uptake, despite their importance for coral energetics. We therefore studied the separate and combined impacts of increases in temperature and pCO2 on phosphate, ammonium, and nitrate uptake rates by the scleractinian coral S. pistillata. Three experiments were performed, during 10 days i) at three pHT conditions (8.1, 7.8, and 7.5) and normal temperature (26°C), ii) at three temperature conditions (26°, 29°C, and 33°C) and normal pHT(8.1), and iii) at three pHT conditions (8.1, 7.8, and 7.5) and elevated temperature (33°C). After 10 days of incubation, corals had not bleached, as protein, chlorophyll, and zooxanthellae contents were the same in all treatments. However, photosynthetic rates significantly decreased at 33°C, and were further reduced for the pHT 7.5. The photosynthetic efficiency of PSII was only decreased by elevated temperature. Nutrient uptake rates were not affected by a change in pH alone. Conversely, elevated temperature (33°C) alone induced an increase in phosphate uptake but a severe decrease in nitrate and ammonium uptake rates, even leading to a release of nitrogen into seawater. Combination of high temperature (33°C) and low pHT(7.5) resulted in a significant decrease in phosphate and nitrate uptake rates compared to control corals (26°C, pHT = 8.1). These results indicate that both inorganic nitrogen and phosphorus metabolism may be negatively affected by the cumulative effects of ocean warming and acidification.