Integrated studies of coupled human and natural systems reveal new and complex patterns and processes not evident when studied by social or natural scientists separately. Synthesis of six case studies from around the world shows that couplings between human and natural systems vary across space, time, and organizational units. They also exhibit nonlinear dynamics with thresholds, reciprocal feedback loops, time lags, resilience, heterogeneity, and surprises. Furthermore, past couplings have legacy effects on present conditions and future possibilities.

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Humans have continuously interacted with natural systems, resulting in the formation and development of coupled human and natural systems (CHANS). Recent studies reveal the complexity of organizational, spatial, and temporal couplings of CHANS. These couplings have evolved from direct to more indirect interactions, from adjacent to more distant linkages, from local to global scales, and from simple to complex patterns and processes. Untangling complexities, such as reciprocal effects and emergent properties, can lead to novel scientific discoveries and is essential to developing effective policies for ecological and socioeconomic sustainability. Opportunities for truly integrating various disciplines are emerging to address fundamental questions about CHANS and meet society's unprecedented challenges.

In vitro gas production, measured by computer-interfaced pressure sensors, was used to follow the digestion of a crystalline processed cellulose, a bacterial cellulose, and mixtures of these substrates by mixed ruminal bacteria. A first-order, substrate limited model (simple exponential with lag) and two bacterial growth models (logistic, Gompertz) were tested to fit these data. No single pool model gave an optimal fit to all substrates, but dual pool versions of both the logistic and Gompertz models fitted the data extremely well. Derivations of these models in the context of gas production are presented. The dual pool version of the exponential model commonly used to analyze fiber digestion was not able to reproduce the slope variations seen with mixed substrates. A modified dual pool logistic equation, with a single lag value, was selected to model the in vitro digestion of these substrates. The model was able to predict adequately both the input composition and the kinetic parameters for a defined mixture and gave a good fit (r2> .995) to data from all the single and mixed substrates tested. This model may be useful for interpreting gas accumulation from natural feedstuffs.

The techniques reported in this paper were developed to facilitate the study of the kinetics of forage digestion in vitro by measuring gas production. Fiber disappearance as a measure of the reaction rate has been replaced by the use of computerized pressure sensors to monitor the gaseous products (CO2, CH4) of microbial metabolism. The recording system described requires a computer, pressure sensors, an interface card, and appropriate software to monitor gas production continuously. Several variables, including sample size, inoculum size, vessel size, and type of pressure sensor, have been investigated to determine ranges within which gas production can be measured accurately, and the reproducibility of the results has been established. Because this technique uses small (100-mg) samples, a modified NDF method has been introduced that allows determination of extent of digestion at the end of an incubation in which gas production has been monitored. A strong linear relationship existed between NDF disappearance and gas production.

Most environmental concerns about waste management either have focused on the effects of nutrients, especially N and P, on water quality or have emphasized odor problems and air quality. Microbes from manure are often low on the priority list for control and remediation, despite the fact that several outbreaks of gastroenteritis have been traced to livestock operations. The pathogens discussed in this paper include protozoans ( Cryptosporidium parvum, Giardia spp.), bacteria ( Listeria monocytogenes, Escherichia coli O157:H7, Salmonella spp., and Mycobacterium paratuberculosis) , and some enteric viruses. Clinical symptoms, prospects for zoonotic infection, and control methods other than the use of antimicrobials are considered. Recommendations to avoid disease transmission include taking steps to ensure the provision of clean, unstressful environments to reduce disease susceptibility and the careful handling and spreading of manure from animals at high risk for infection, especially young calves. Composting and drying of manure decrease the number of viable pathogens. Environmental controls, such as filter strips, also reduce the risk of water contamination. (

ABSTRACT:The Cornell Net Carbohydrate and Protein System (CNCPS), a mechanistic model that predicts nutrient requirements and biological values of feeds for cattle, was modified for use with sheep. Published equations were added for predicting the energy and protein requirements of sheep, with a special emphasis on dairy sheep, whose specific needs are not considered by most sheep-feeding systems. The CNCPS for cattle equations that are used to predict the supply of nutrients from each feed were modified to include new solid and liquid ruminal passage rates for sheep, and revised equations were inserted to predict metabolic fecal N. Equations were added to predict fluxes in body energy and protein reserves from BW and condition score. When evaluated with data from seven published studies (19 treatments), for which the CNCPS for sheep predicted positive ruminal N balance, the CNCPS for sheep predicted OM digestibility, which is used to predict feed ME values, with no mean bias (1.1 g/100 g of OM; P > 0.10) and a low root mean squared prediction error (RMSPE; 3.6 g/100 g of OM). Crude protein digestibility, which is used to predict N excretion, was evaluated with eight published studies (23