Sample Optimization for Five Plant-Parasitic Nematodes in an Alfalfa Field

A data base representing nematode counts and soil weight from 1,936 individual soil cores taken from a 7-ha alfalfa field was used to investigate sample optimization for five plant-parasitic nematodes: Meloidogyne arenaria, Pratylenchus minyus, Merlinius brevidens, Helicotylenchus digonicus, and Paratrichodorus minor. Sample plans were evaluated by the accuracy and reliability of their estimation of the population and by the cost of collecting, processing, and counting the samples. Interactive FORTRAN programs were constructed to simulate four collecting patterns: random; division of the field into square sub-units (cells); and division of the field into rectangular sub-traits (strips) running in two directions. Depending on the pattern, sample numbers varied from 1 to 25 with each sample representing from 1 to 50 cores. Each pattern, sample, and core combination was replicated 50 times. Strip stratification north/south was the most optimal sampling pattern in this field because it isolated a streak of fine-textured soil. The mathematical optimmn was not found because of data range limitations. When practical economic time constraints (5 hr to collect, process, and count nematode samples) are placed on the optimization process, all species estimates deviate no more than 25 % from the true mean. If accuracy constraints are placed on the process (no more than 15% deviation from true field mean), all species except Merlinius required less than 5 hr to complete the sample process.     

Sweet or not: Using information and cognitive dissonance to nudge children toward healthier food choices

In the interest of public health, it is important to nudge children toward healthier food choices (e.g., beverages with less added sugar). We conducted a field experiment in a peri-urban region in Vietnam to evaluate the effects of information and cognitive dissonance on the food choices of children. Our sample consisted of more than 1200 primary school children, randomly assigned into three groups: control, health information, and health information plus hypocrisy inducement. The third group was intended to raise cognitive dissonance by illustrating the gap between what people know they should do (socially desired behaviors) and what they actually do (transgressions). The results indicate that health information increased the likelihood of selecting milk with less sugar by around 30 %, as compared to the control group. Hypocrisy inducement did not make any additional contribution to healthier food choices. The treatment effects declined when there was a delay between the treatment and the behavioral choice. We discuss the practical implications of our findings for short-term intervention field studies.     

Natural Resource Management: Historical Lessons from Indonesia

This paper uses a variety of historical evidence from Indonesia to explore the conditions for sustainable management of natural resources. In the agricultural sphere, history gives reason for optimism regarding the ability of individuals to conserve and improve soil resources on an uncoordinated, anarchic basis under systems of intensive smallholder farming and agroforestry. It also suggests that this ability may be enhanced, rather than eroded, both by population growth and by the commercialization of agriculture. When it comes to the management of forests and fisheries and the conservation of nature, by contrast, there is less reason for optimism. If sustainable solutions are to be found in these spheres, the historical evidence suggests that they will involve political hierarchy, and will depend on the honouring of a social contract in which the state serves the public interest while retaining the powers of coercion which it needs in order to do just that.     

Incorporating pressure–volume traits into the leaf economics spectrum

In recent years, attempts have been made in linking pressure–volume parameters and the leaf economics spectrum to expand our knowledge of the interrelationships among leaf traits. We provide theoretical and empirical evidence for the coordination of the turgor loss point and associated traits with net CO₂ assimilation (A_n) and leaf mass per area (LMA). We measured gas exchange, pressure–volume curves and leaf structure in 45 ferns and angiosperms, and explored the anatomical and chemical basis of the key traits. We propose that the coordination observed between mass-based A_n, capacitance and the turgor loss point (π_tlp) emerges from their shared link with leaf density (one of the components of LMA) and, specially, leaf saturated water content (LSWC), which in turn relates to cell size and nitrogen and carbon content. Thus, considering the components of LMA and LSWC in ecophysiological studies can provide a broader perspective on leaf structure and function.     

Ecological engineering: First steps towards economic analysis

Ecosystems fulfill a large number of ecological and economic functions. Increasing economic activity and population pressure are threatening the quality of ecosystems, and strengthen the need for ecological engineering. In this article some of the economic aspects of ecological engineering are discussed. In particular, the various methods to establish the economic costs and benefits of ecological engineering. For benefit estimation various methods are developed, including the contingent valuation method, the hedonic pricing method, the travel cost method and the shadow project method. The economic background, and the applicability and appropriateness of these methods are discussed. Next, the results of several studies on wetland valuation are shortly presented. It is concluded that the full socio-economic assessment of ecological engineering is still to be developed, and that further cooperation between ecologists and economists is required to make progress in this field that is rapidly gaining importance in policy making, both at the European and the global level.     

Global leaf-trait mapping based on optimality theory

Aim

Leaf traits are central to plant function, and key variables in ecosystem models. However recently published global trait maps, made by applying statistical or machine-learning techniques to large compilations of trait and environmental data, differ substantially from one another. This paper aims to demonstrate the potential of an alternative approach, based on eco-evolutionary optimality theory, to yield predictions of spatio-temporal patterns in leaf traits that can be independently evaluated.

Innovation

Global patterns of community-mean specific leaf area (SLA) and photosynthetic capacity (V_cmax) are predicted from climate via existing optimality models. Then leaf nitrogen per unit area (N_area) and mass (N_mass) are inferred using their (previously derived) empirical relationships to SLA and V_cmax. Trait data are thus reserved for testing model predictions across sites. Temporal trends can also be predicted, as consequences of environmental change, and compared to those inferred from leaf-level measurements and/or remote-sensing methods, which are an increasingly important source of information on spatio-temporal variation in plant traits.

Main conclusions

Model predictions evaluated against site-mean trait data from > 2,000 sites in the Plant Trait database yielded R² = 73% for SLA, 38% for N_mass and 28% for N_area. Declining species-level N_mass, and increasing community-level SLA, have both been recently reported and were both correctly predicted. Leaf-trait mapping via optimality theory holds promise for macroecological applications, including an improved understanding of community leaf-trait responses to environmental change.