Global demand for agricultural products such as food, feed, and fuel is now a major driver of cropland and pasture expansion across much of the developing world. Whether these new agricultural lands replace forests, degraded forests, or grasslands greatly influences the environmental consequences of expansion. Although the general pattern is known, there still is no definitive quantification of these land-cover changes. Here we analyze the rich, pan-tropical database of classified Landsat scenes created by the Food and Agricultural Organization of the United Nations to examine pathways of agricultural expansion across the major tropical forest regions in the 1980s and 1990s and use this information to highlight the future land conversions that probably will be needed to meet mounting demand for agricultural products. Across the tropics, we find that between 1980 and 2000 more than 55% of new agricultural land came at the expense of intact forests, and another 28% came from disturbed forests. This study underscores the potential consequences of unabated agricultural expansion for forest conservation and carbon emissions.

Twenty-four multiparous dairy cows (eight with ruminal cannulae) were blocked by days in milk and assigned to six balanced 4 x 4 Latin squares with 21-d periods. The four diets, formulated from alfalfa silage plus a concentrate mix based on ground high moisture ear corn, contained (dry matter basis): 1) 20% concentrate, 80% alfalfa silage (24% nonfiber carbohydrate; NFC), 2) 35% concentrate, 65% alfalfa silage (30% NFC), 3) 50% concentrate, 50% alfalfa silage (37% NFC), or 4) 65% concentrate, 35% alfalfa silage (43% NFC). Soybean meal and urea were added to make diets isonitrogenous with equal nonprotein nitrogen (NPN) (43% of total N). Total urine was collected with indwelling Folley catheters for 24 h during each period. There was no effect of diet on urinary creatinine excretion (average 29 mg/kg of BW/d). There were quadratic effects of diet on total urinary ecretion of allantoin, uric acid, and purine derivatives (allantoin plus uric acid), and on ruminal synthesis of microbial N estimated from purine derivatives; maxima occurred at about 35% dietary NFC. Urinary excretion also was estimated with spot urine samples from creatinine concentration and the mean daily creatinine excretion. Daily excretion of allantoin, uric acid, and purine derivatives estimated from spot urine sampling followed the same pattern as that observed with total collection; differences between measured and estimated urine volume were significant only for 35% dietary concentrate. Spot urine sampling appeared to yield satisfactory estimates of purine derivative excretion. Maximal urea N excretion was estimated to occur at about 31% dietary NFC. Milk allantoin secretion increased linearly with concentrate and accounted for 4 to 6% of the total purine derivative excretion. Microbial yield was maximal at 35% dietary NFC, suggesting that this was the optimal level for utilization of dietary NPN from alfalfa silage and other sources.

Periodic wildfire maintains the integrity and species composition of many ecosystems, including the mediterranean-climate shrublands of California. However, human activities alter natural fire regimes, which can lead to cascading ecological effects. Increased human ignitions at the wildland-urban interface (WUI) have recently gained attention, but fire activity and risk are typically estimated using only biophysical variables. Our goal was to determine how humans influence fire in California and to examine whether this influence was linear, by relating contemporary (2000) and historic (1960-2000) fire data to both human and biophysical variables. Data for the human variables included fine-resolution maps of the WUI produced using housing density and land cover data. Interface WUI, where development abuts wildland vegetation, was differentiated from intermix WUI, where development intermingles with wildland vegetation. Additional explanatory variables included distance to WUI, population density, road density, vegetation type, and ecoregion. All data were summarized at the county level and analyzed using bivariate and multiple regression methods. We found highly significant relationships between humans and fire on the contemporary landscape, and our models explained fire frequency (R2 = 0.72) better than area burned (R2 = 0.50). Population density, intermix WUI, and distance to WUI explained the most variability in fire frequency, suggesting that the spatial pattern of development may be an important variable to consider when estimating fire risk. We found nonlinear effects such that fire frequency and area burned were highest at intermediate levels of human activity, but declined beyond certain thresholds. Human activities also explained change in fire frequency and area burned (1960-2000), but our models had greater explanatory power during the years 1960-1980, when there was more dramatic change in fire frequency. Understanding wildfire as a function of the spatial arrangement of ignitions and fuels on the landscape, in addition to nonlinear relationships, will be important to fire managers and conservation planners because fire risk may be related to specific levels of housing density that can be accounted for in land use planning. With more fires occurring in close proximity to human infrastructure, there may also be devastating ecological impacts if development continues to grow farther into wildland vegetation.

Data from 35 trials with 482 lactating cows fed 106 diets were used to study the effects of animal and dietary factors on the relationship between milk and blood urea N and the value of milk urea N in the assessment of protein status. In two trials, urea N in whole blood and in blood plasma were closely related (r2 = 0.952); the slope was not significantly different from 1.0, and the intercept was not significantly different from 0. Regression of milk urea N on blood urea N with a mixed effects model using all 2231 observations yielded the equation: milk urea N (milligrams of N per deciliter) = 0.620 x blood urea N (milligrams of N per deciliter) + 4.75 (r2 = 0.842); this model accounted for a significant interaction of cow and blood urea N. Single factors that yielded significant regressions on milk urea N with the mixed effects models were dietary crude protein (CP) (percentage of dry matter; r2 = 0.839), dietary CP per megacalorie of net energy for lactation (NEL) (r2 = 0.833), excess N intake (r2 = 0.772), N efficiency (r2 = 0.626), and ruminal NH3 (r2 = 0.574). When all factors were analyzed at once, 12 were significant in a mixed effects model. Blood urea N, body weight, yield of fat-corrected milk, dietary CP content, excess N intake, dry matter intake, and days in milk were positively related to milk urea N, and parity, milk and fat yield, dietary CP per unit of NEL content, and NEL intake were negatively related to milk urea N. In one trial, the mean urea concentration was 35 times greater in urine than in milk; lower proportions of total urea excretion in milk were observed in the a.m. sampling (1.8%) than in the p.m. sampling (3.3%). Measuring urea N in a composite milk sample from the whole day substantially improved reliability of data. The number of cows fed a specific diet that must be sampled to determine mean milk urea N within 95% confidence intervals with half widths of 1.0 and 2.0 mg of N/dl was estimated to be 16 and 4, respectively.

Stable isotopes of carbon, nitrogen, and sulfur are used as ecological tracers for a variety of applications, such as studies of animal migrations, energy sources, and food web pathways. Yet uncertainty relating to the time period integrated by isotopic measurement of animal tissues can confound the interpretation of isotopic data. There have been a large number of experimental isotopic diet shift studies aimed at quantifying animal tissue isotopic turnover rate λ (%·day-1, often expressed as isotopic half-life, ln(2)/λ, days). Yet no studies have evaluated or summarized the many individual half-life estimates in an effort to both seek broad-scale patterns and characterize the degree of variability. Here, we collect previously published half-life estimates, examine how half-life is related to body size, and test for tissue- and taxa-varying allometric relationships. Half-life generally increases with animal body mass, and is longer in muscle and blood compared to plasma and internal organs. Half-life was longest in ecotherms, followed by mammals, and finally birds. For ectotherms, different taxa-tissue combinations had similar allometric slopes that generally matched predictions of metabolic theory. Half-life for ectotherms can be approximated as: ln (half-life) = 0.22*ln (body mass) + group-specific intercept; n = 261, p<0.0001, r2 = 0.63. For endothermic groups, relationships with body mass were weak and model slopes and intercepts were heterogeneous. While isotopic half-life can be approximated using simple allometric relationships for some taxa and tissue types, there is also a high degree of unexplained variation in our models. Our study highlights several strong and general patterns, though accurate prediction of isotopic half-life from readily available variables such as animal body mass remains elusive.

There are several indices for measuring the similarity of two populations, including the ratio of the number of shared species to the number of distinct species (Jaccard's index) and the conditional probability of observing a shared species (Smith et al., (1)). However, these indices only take into account the number of species and species proportions of shared species.In this paper, we propose a new similarity index which includes the species proportions of both the shared and non-shared species in each population, and also propose a Nonparametric Maximum Likelihood Estimator (NPMLE) for this index. Bootstrap and delta methods are used to evaluate the standard errors of the NPMLE. Based on a loss function, we also compare a class of nonparametric estimators for the proposed index in various situations.

Humans influence the frequency and spatial pattern of fire and contribute to altered fire regimes, but fuel loading is often the only factor considered when planning management activities to reduce fire hazard. Understanding both the human and biophysical landscape characteristics that explain how fire patterns vary should help to identify where fire is most likely to threaten values at risk. We used human and biophysical explanatory variables to model and map the spatial patterns of both fire ignitions and fire frequency in the Santa Monica Mountains, a human-dominated southern California landscape. Most fires in the study area are caused by humans, and our results showed that fire ignition patterns were strongly influenced by human variables. In particular, ignitions were most likely to occur close to roads, trails, and housing development but were also related to vegetation type. In contrast, biophysical variables related to climate and terrain (January temperature, transformed aspect, elevation, and slope) explained most of the variation in fire frequency. Although most ignitions occur close to human infrastructure, fires were more likely to spread when located farther from urban development. How far fires spread was ultimately related to biophysical variables, and the largest fires in southern California occurred as a function of wind speed, topography, and vegetation type. Overlaying predictive maps of fire ignitions and fire frequency may be useful for identifying high-risk areas that can be targeted for fire management actions.

Fluxes of organic matter across habitat boundaries are common in food webs. These fluxes may strongly influence community dynamics, depending on the extent to which they are used by consumers. Yet understanding of basal resource use by consumers is limited, because describing trophic pathways in complex food webs is difficult. We quantified resource use for zooplankton, zoobenthos, and fishes in four low-productivity lakes, using a Bayesian mixing model and measurements of hydrogen, carbon, and nitrogen stable isotope ratios. Multiple sources of uncertainty were explicitly incorporated into the model. As a result, posterior estimates of resource use were often broad distributions; nevertheless, clear patterns were evident. Zooplankton relied on terrestrial and pelagic primary production, while zoobenthos and fishes relied on terrestrial and benthic primary production. Across all consumer groups terrestrial reliance tended to be higher, and benthic reliance lower, in lakes where light penetration was low due to inputs of terrestrial dissolved organic carbon. These results support and refine an emerging consensus that terrestrial and benthic support of lake food webs can be substantial, and they imply that changes in the relative availability of basal resources drive the strength of cross-habitat trophic connections.