Center for Agricultural Resources Research

Invasive alien species (IAS) threaten human livelihoods and biodiversity globally. Increasing globalization facilitates IAS arrival, and environmental changes, including climate change, facilitate IAS establishment. Here we provide the first global, spatial analysis of the terrestrial threat from IAS in light of twenty-first century globalization and environmental change, and evaluate national capacities to prevent and manage species invasions. We find that one-sixth of the global land surface is highly vulnerable to invasion, including substantial areas in developing economies and biodiversity hotspots. The dominant invasion vectors differ between high-income countries (imports, particularly of plants and pets) and low-income countries (air travel). Uniting data on the causes of introduction and establishment can improve early-warning and eradication schemes. Most countries have limited capacity to act against invasions. In particular, we reveal a clear need for proactive invasion strategies in areas with high poverty levels, high biodiversity and low historical levels of invasion.

The concept of food system has gained prominence in recent years amongst both scholars and policy-makers. Experts from diverse disciplines and backgrounds have in particular discussed the nature and origin of the “unsustainability” of our modern food systems. These efforts tend, however, to be framed within distinctive disciplinary narratives. In this paper we propose to explore these narratives and to shed light on the explicit -or implicit- epistemological assumptions, mental models, and disciplinary paradigms that underpin those. The analysis indicates that different views and interpretations prevail amongst experts about the nature of the “crisis”, and consequently about the research and priorities needed to “fix” the problem. We then explore how sustainability is included in these different narratives and the link to the question of healthy diets. The analysis reveals that the concept of sustainability, although widely used by all the different communities of practice, remains poorly defined, and applied in different ways and usually based on a relatively narrow interpretation. In so doing we argue that current attempts to equate or subsume healthy diets within sustainability in the context of food system may be misleading and need to be challenged. We stress that trade-offs between different dimensions of food system sustainability are unavoidable and need to be navigated in an explicit manner when developing or implementing sustainable food system initiatives. Building on this overall analysis, a framework structured around several entry points including outcomes, core activities, trade-offs and feedbacks is then proposed, which allows to identify key elements necessary to support the transition toward sustainable food systems.

In recent years, increased awareness of the potential interactions between rising atmospheric CO2 concentrations ([ CO2 ]) and temperature has illustrated the importance of multifactorial ecosystem manipulation experiments for validating Earth System models. To address the urgent need for increased understanding of responses in multifactorial experiments, this article synthesizes how ecosystem productivity and soil processes respond to combined warming and [ CO2 ] manipulation, and compares it with those obtained in single factor [ CO2 ] and temperature manipulation experiments. Across all combined elevated [ CO2 ] and warming experiments, biomass production and soil respiration were typically enhanced. Responses to the combined treatment were more similar to those in the [ CO2 ]-only treatment than to those in the warming-only treatment. In contrast to warming-only experiments, both the combined and the [ CO2 ]-only treatments elicited larger stimulation of fine root biomass than of aboveground biomass, consistently stimulated soil respiration, and decreased foliar nitrogen (N) concentration. Nonetheless, mineral N availability declined less in the combined treatment than in the [ CO2 ]-only treatment, possibly due to the warming-induced acceleration of decomposition, implying that progressive nitrogen limitation (PNL) may not occur as commonly as anticipated from single factor [ CO2 ] treatment studies. Responses of total plant biomass, especially of aboveground biomass, revealed antagonistic interactions between elevated [ CO2 ] and warming, i.e. the response to the combined treatment was usually less-than-additive. This implies that productivity projections might be overestimated when models are parameterized based on single factor responses. Our results highlight the need for more (and especially more long-term) multifactor manipulation experiments. Because single factor CO2 responses often dominated over warming responses in the combined treatments, our results also suggest that projected responses to future global warming in Earth System models should not be parameterized using single factor warming experiments.

Crop diversity underpins the productivity, resilience and adaptive capacity of agriculture. Loss of this diversity, termed crop genetic erosion, is therefore concerning. While alarms regarding evident declines in crop diversity have been raised for over a century, the magnitude, trajectory, drivers and significance of these losses remain insufficiently understood. We outline the various definitions, measurements, scales and sources of information on crop genetic erosion. We then provide a synthesis of evidence regarding changes in the diversity of traditional crop landraces on farms, modern crop cultivars in agriculture, crop wild relatives in their natural habitats and crop genetic resources held in conservation repositories. This evidence indicates that marked losses, but also maintenance and increases in diversity, have occurred in all these contexts, the extent depending on species, taxonomic and geographic scale, and region, as well as analytical approach. We discuss steps needed to further advance knowledge around the agricultural and societal significance, as well as conservation implications, of crop genetic erosion. Finally, we propose actions to mitigate, stem and reverse further losses of crop diversity.

The largest livestock production and greatest fertilizer use in the world occurs in China. However, quantification of the nutrient flows through the manure management chain and their interactions with management-related measures is lacking. Herein, we present a detailed analysis of the nutrient flows and losses in the “feed intake–excretion–housing–storage–treatment–application” manure chain, while considering differences among livestock production systems. We estimated the environmental loss from the manure chain in 2010 to be up to 78% of the excreted nitrogen and over 50% of the excreted phosphorus and potassium. The greatest losses occurred from housing and storage stages through NH3 emissions (39% of total nitrogen losses) and direct discharge of manure into water bodies or landfill (30–73% of total nutrient losses). There are large differences among animal production systems, where the landless system has the lowest manure recycling. Scenario analyses for the year 2020 suggest that significant reductions of fertilizer use (27–100%) and nutrient losses (27–56%) can be achieved through a combination of prohibiting manure discharge, improving manure collection and storages infrastructures, and improving manure application to cropland. We recommend that current policies and subsidies targeted at the fertilizer industry should shift to reduce the costs of manure storage, transport, and application.

Nitrogen (N) and phosphorus (P) are essential nutrients for primary producers and decomposers in terrestrial ecosystems. Although climate change affects terrestrial N cycling with important feedbacks to plant productivity and carbon sequestration, the impacts of climate change on the relative availability of N with respect to P remain highly uncertain. In a semiarid grassland in Wyoming, USA, we studied the effects of atmospheric CO(2) enrichment (to 600 ppmv) and warming (1.5/3.0°C above ambient temperature during the day/night) on plant, microbial and available soil pools of N and P. Elevated CO(2) increased P availability to plants and microbes relative to that of N, whereas warming reduced P availability relative to N. Across years and treatments, plant N : P ratios varied between 5 and 18 and were inversely related to soil moisture. Our results indicate that soil moisture is important in controlling P supply from inorganic sources, causing reduced P relative to N availability during dry periods. Both wetter soil conditions under elevated CO(2) and drier conditions with warming can further alter N : P. Although warming may alleviate N constraints under elevated CO(2) , warming and drought can exacerbate P constraints on plant growth and microbial activity in this semiarid grassland.

The grand challenge confronting agriculture is the development of technologies for sustainable intensification of crop production systems to feed the estimated future human population of 9 to 10 billion. It is thought that crop production must be increased by 60 to 100% by the year 2050 to meet these nutritional needs. Crop production systems that yield more food of higher nutritional content are needed that at the same time have a diminished impact on the environment. Prior agricultural intensification was through substantial use of fertilizer, pesticides, and irrigation all at significant environmental cost. As a part of Sustainable Agriculture, next-generation, on cropping systems that couple biologically based technologies (plant-beneficial microbes, cover crops) and precision agriculture need to be developed to decrease fertilizer, pesticide, and water inputs. Over the past two decades, Information Technology has been the disruptive force in industries by driving out market inefficiencies through automation and better decision support tools that require the inclusion of both the citizens and consumers in the process. Like all industries, Agriculture has not been immune to the constant disruptions over the past century. However, recent advances in the computing infrastructure, sensor technology, big data and advanced algorithms ( suggest that a major disruption or paradigm shift is on the horizon, leading to opportunities for sustainable agriculture entering the mainstream. Specifically, solutions based on these new technologies will be needed for mass transfer of genomic and other genetic data for development of these advanced crop cultivars, and for the management of agronomic data for the development of these next-generation production systems. Geospatial solutions based on imagery, IoT, AI, mobile data collection, etc. will be critical for the operation of precision agriculture systems where intelligent application of resource inputs are applied at precise geo-specific field locations based on crop need. Finally, solutions will be needed to allow immediate feedback from digital farm communities regarding the performance of these new cropping systems; speeding their development. Here we describe a “system of systems” approach to building a scientific network that integrates the scientific and farming communities, based on a Geoinformatics cloud framework.

Until recently, Intergovernmental Panel on Climate Change (IPCC) emission factor methodology, based on simple empirical relationships, has been used to estimate carbon (C) and nitrogen (N) fluxes for regional and national inventories. However, the 2005 USEPA greenhouse gas inventory includes estimates of N2O emissions from cultivated soils derived from simulations using DAYCENT, a process-based biogeochemical model. DAYCENT simulated major U.S. crops at county-level resolution and IPCC emission factor methodology was used to estimate emissions for the approximately 14% of cropped land not simulated by DAYCENT. The methodology used to combine DAYCENT simulations and IPCC methodology to estimate direct and indirect N2O emissions is described in detail. Nitrous oxide emissions from simulations of presettlement native vegetation were subtracted from cropped soil N2O to isolate anthropogenic emissions. Meteorological data required to drive DAYCENT were acquired from DAYMET, an algorithm that uses weather station data and accounts for topography to predict daily temperature and precipitation at 1-km2 resolution. Soils data were acquired from the State Soil Geographic Database (STATSGO). Weather data and dominant soil texture class that lie closest to the geographical center of the largest cluster of cropped land in each county were used to drive DAYCENT. Land management information was implemented at the agricultural-economic region level, as defined by the Agricultural Sector Model. Maps of model-simulated county-level crop yields were compared with yields estimated by the USDA for quality control. Combining results from DAYCENT simulations of major crops and IPCC methodology for remaining cropland yielded estimates of approximately 109 and approximately 70 Tg CO2 equivalents for direct and indirect, respectively, mean annual anthropogenic N2O emissions for 1990-2003.

Why do some exotic plant species become invasive? Two common hypotheses, increased resource availability and enemy release, may more effectively explain invasion if they favor the same species, and therefore act in concert. This would be expected if plant species adapted to high levels of available resources in their native range are particularly susceptible to enemies, and therefore benefit most from a paucity of enemies in their new range. We tested this possibility by examining how resource adaptations influence pathogen richness and release among 243 European plant species naturalized in the United States. Plant species adapted to higher resource availability hosted more pathogen species in their native range. Plants from mesic environments hosted more fungi than plants from xeric environments, and plants from nitrogen-rich environments hosted more viruses than plants from nitrogen-poor environments. Furthermore, plants classified as competitors hosted more than 4 times as many fungi and viruses as did stress tolerators. Patterns of enemy release mirrored those of pathogen richness: competitors and species from mesic and nitrogen-rich environments were released from many pathogen species, while stress tolerators and species from xeric and nitrogen-poor environments were released from relatively few pathogen species. These results suggest that enemy release contributes most to invasion by fast-growing species adapted to resource-rich environments. Consequently, enemy release and increases in resource availability may act synergistically to favor exotic over native species.

Cryogenic technologies help to preserve plant biodiversity in seed banks, particularly in the tropics.

Abstract Plant traits can provide unique insights into plant performance at the community scale. Functional composition, defined by both functional diversity and community‐weighted trait means (CWMs), can affect the stability of above‐ground net primary production (ANPP) in response to climate extremes. Further complexity arises, however, when functional composition itself responds to environmental change. The duration of climate extremes, such as drought, is expected to increase with rising global temperatures; thus, understanding the impacts of long‐term drought on functional composition and the corresponding effect that has on ecosystem function could improve predictions of ecosystem sensitivity to climate change. We experimentally reduced growing season precipitation by 66% across six temperate grasslands for 4 years and measured changes in three indices of functional diversity (functional dispersion, richness and evenness), community‐weighted trait means and phylogenetic diversity (PD). Specific leaf area (SLA), leaf nitrogen content (LNC) and (at most sites) leaf turgor loss point ( π TLP ) were measured for species cumulatively representing ~90% plant cover at each site. Long‐term drought led to increased community functional dispersion in three sites, with negligible effects on the remaining sites. Species re‐ordering following the mortality/senescence of dominant species was the main driver of increased functional dispersion. The response of functional diversity was not consistently matched by changes in phylogenetic diversity. Community‐level drought strategies (assessed as CWMs) largely shifted from drought tolerance to drought avoidance and/or escape strategies, as evidenced by higher community‐weighted π TLP , SLA and LNC. Lastly, ecosystem drought sensitivity (i.e. relative reduction in ANPP in drought plots) was positively correlated with community‐weighted SLA and negatively correlated with functional diversity. Synthesis. Increased functional diversity following long‐term drought may stabilize ecosystem functioning in response to future drought. However, shifts in community‐scale drought strategies may increase ecosystem drought sensitivity, depending on the nature and timing of drought. Thus, our results highlight the importance of considering both functional diversity and abundance‐weighted traits means of plant communities as their collective effect may either stabilize or enhance ecosystem sensitivity to drought.

Persistence of anhydrous organisms in nature may depend on how long they remain viable in dry environments. Longevity is determined by interactions of humidity, temperature, and unknown cellular factors that affect the propensity for damaging reactions. Here we describe our research to elucidate those cellular factors and to ultimately predict how long a population can survive under extreme conditions. Loss of viability typically follows a sigmoidal pattern, where a period of small changes precedes a cataclysmic decline. The time for viability to decrease to 50% (P50) varied among seed species and among 10 phylogenetically diverse organisms. When stored at elevated temperatures of 35°C and 32% relative humidity (RH), P50 ranged from about a week for spores of Serratia marcescens to several years for fronds of Selaginella lepidophylla. Most of the species studied survived longest at low humidity (10-20% RH), but suffered under complete dryness. Temperature dependencies of aging kinetics appeared similar among diverse organisms despite the disparate longevities. The effect of temperature on seed aging rates was consistent with the temperature dependency of molecular mobility of aqueous glasses, with both showing a reduction by several orders of magnitude when seeds were cooled from 60°C to 0°C. Longevity is an inherited trait in seeds, but its complex expression among widely divergent taxa suggests that it developed through multiple pathways.

Exotic species dominate many communities; however the functional significance of species' biogeographic origin remains highly contentious. This debate is fuelled in part by the lack of globally replicated, systematic data assessing the relationship between species provenance, function and response to perturbations. We examined the abundance of native and exotic plant species at 64 grasslands in 13 countries, and at a subset of the sites we experimentally tested native and exotic species responses to two fundamental drivers of invasion, mineral nutrient supplies and vertebrate herbivory. Exotic species are six times more likely to dominate communities than native species. Furthermore, while experimental nutrient addition increases the cover and richness of exotic species, nutrients decrease native diversity and cover. Native and exotic species also differ in their response to vertebrate consumer exclusion. These results suggest that species origin has functional significance, and that eutrophication will lead to increased exotic dominance in grasslands.

Rice is the most important food security crop in Asia. Information on its seasonal extent forms part of the national accounting of many Asian countries. Synthetic Aperture Radar (SAR) imagery is highly suitable for detecting lowland rice, especially in tropical and subtropical regions, where pervasive cloud cover in the rainy seasons precludes the use of optical imagery. Here, we present a simple, robust, rule-based classification for mapping rice area with regularly acquired, multi-temporal, X-band, HH-polarized SAR imagery and site-specific parameters for classification. The rules for rice detection are based on the well-studied temporal signature of rice from SAR backscatter and its relationship with crop stages. We also present a procedure for estimating the parameters based on “temporal feature descriptors” that concisely characterize the key information in the rice signatures in monitored field locations within each site. We demonstrate the robustness of the approach on a very large dataset. A total of 127 images across 13 footprints in six countries in Asia were obtained between October 2012, and April 2014, covering 4.78 m ha. More than 1900 in-season site visits were conducted across 228 monitoring locations in the footprints for classification purposes, and more than 1300 field observations were made for accuracy assessment. Some 1.6 m ha of rice were mapped with classification accuracies from 85% to 95% based on the parameters that were closely related to the observed temporal feature descriptors derived for each site. The 13 sites capture much of the diversity in water management, crop establishment and maturity in South and Southeast Asia. The study demonstrates the feasibility of rice detection at the national scale using multi-temporal SAR imagery with robust classification methods and parameters that are based on the knowledge of the temporal dynamics of the rice crop. We highlight the need for the development of an open-access library of temporal signatures, further investigation into temporal feature descriptors and better ancillary data to reduce the risk of misclassification with surfaces that have temporal backscatter dynamics similar to those of rice. We conclude with observations on the need to define appropriate SAR acquisition plans to support policies and decisions related to food security.

ABSTRACT Aim Extrapolation of tower CO 2 fluxes will be greatly facilitated if robust relationships between flux components and remotely sensed factors are established. Long‐term measurements at five Northern Great Plains locations were used to obtain relationships between CO 2 fluxes and photosynthetically active radiation ( Q ), other on‐site factors, and Normalized Difference Vegetation Index ( NDVI ) from the SPOT VEGETATION data set. Location CO 2 flux data from the following stations and years were analysed: Lethbridge, Alberta 1998–2001; Fort Peck, MT 2000, 2002; Miles City, MT 2000–01; Mandan, ND 1999–2001; and Cheyenne, WY 1997–98. Results Analyses based on light‐response functions allowed partitioning net CO 2 flux ( F ) into gross primary productivity ( P g ) and ecosystem respiration ( R e ). Weekly averages of daytime respiration, γ day , estimated from light responses were closely correlated with weekly averages of measured night‐time respiration, γ night ( R 2 0.64 to 0.95). Daytime respiration tended to be higher than night‐time respiration, and regressions of γ day on γ night for all sites were different from 1 : 1 relationships. Over 13 site‐years, gross primary production varied from 459 to 2491 g CO 2 m −2 year −1 , ecosystem respiration from 996 to 1881 g CO 2 m −2 year −1 , and net ecosystem exchange from −537 (source) to +610 g CO 2 m −2 year −1 (sink). Maximum daily ecological light‐use efficiencies, ɛ d , max = P g /Q , were in the range 0.014 to 0.032 mol CO 2 (mol incident quanta) −1 . Main conclusions Ten‐day average P g was significantly more highly correlated with NDVI than 10‐day average daytime flux, P d ( R 2 = 0.46 to 0.77 for P g ‐NDVI and 0.05 to 0.58 for P d ‐NDVI relationships). Ten‐day average R e was also positively correlated with NDVI , with R 2 values from 0.57 to 0.77. Patterns of the relationships of P g and R e with NDVI and other factors indicate possibilities for establishing multivariate functions allowing scaling‐up local fluxes to larger areas using GIS data, temporal NDVI, and other factors.

Plant breeders require genetic diversity to develop cultivars that are productive, nutritious, tolerant of biotic and abiotic stresses, and make efficient use of water and fertilizer. The USDA‐ARS National Plant Germplasm System (NPGS) is a major source for global plant genetic resources (PGR), with accessions representing improved cultivars, breeding lines, landraces, and crop wild relatives (CWR), coupled with passport and trait evaluation data. The goal of this article is to facilitate use of PGR in plant breeding programs. Our specific objectives are (i) to summarize the structure and operation of the NPGS and its consultative and support committees, (ii) to review current use of the system by plant breeders, (iii) to describe constraints to improving the utility of PGR, and (iv) to discuss ways in which the NPGS might evolve to better meet the challenges facing agriculture and society in coming decades. The NPGS will enhance its relevance to plant breeding provided there is (i) ongoing attention to filling the gaps in NPGS collections, especially for CWR; (ii) a major increase in efforts to phenotype and genotype accessions using standardized methods; (iii) enhanced information content of the Genetic Resources Information Network (GRIN)‐Global system and improved interoperability with other databases; (iv) increased attention to prebreeding activities; (v) improved training opportunities in practices for incorporating PGR in breeding programs; and (vi) expanded outreach efforts to strengthen public support for the NPGS. We believe these steps will be implemented most effectively through coordinated efforts among USDA‐ARS, universities, the private sector, and international partners.

In many plant species, exposure to a prolonged period of cold during the winter promotes flowering in the spring, a process termed vernalization. In Arabidopsis thaliana, the vernalization requirement of winter-annual ecotypes is caused by the MADS-box gene FLOWERING LOCUS C (FLC), which is a repressor of flowering. During the vernalization process, FLC is downregulated by alteration of its chromatin structure, thereby permitting flowering to occur. In wheat, a vernalization requirement is imposed by a different repressor of flowering, suggesting that some components of the regulatory network controlling the vernalization response differ between monocots and dicots. The extent to which the molecular mechanisms underlying vernalization have been conserved during the diversification of the angiosperms is not well understood. Using phylogenetic analysis, we identified homologs of FLC in species representing the three major eudicot lineages. FLC homologs have not previously been documented outside the plant family Brassicaceae. We show that the sugar beet FLC homolog BvFL1 functions as a repressor of flowering in transgenic Arabidopsis and is downregulated in response to cold in sugar beet. Cold-induced downregulation of an FLC-like floral repressor may be a central feature of the vernalization response in at least half of eudicot species.

Non‐steady‐state (NSS) chambers are widely used to measure trace gas emissions from the Earth's surface to the atmosphere. Unfortunately, traditional interpretations of time‐dependent chamber concentrations often systematically underestimate predeployment exchange rates because they do not accurately represent the fundamental physics of diffusive soil gas transport that follows chamber deployment. To address this issue, we formally derived a time‐dependent diffusion model applicable to NSS chamber observations and evaluated its performance using simulated chamber headspace CO 2 concentration data generated by an independent, three‐dimensional, numerical diffusion model. Using nonlinear regression to estimate the model parameters, we compared the performance of the non‐steady‐state diffusive flux estimator (NDFE) to that of the linear, quadratic, and steady‐state diffusion models that are widely cited in the literature, determined its sensitivity to violation of the primary assumptions on which it is based, and addressed some of the practicalities of its application. In sharp contrast to the other models, NDFE proved an accurate and robust estimator of trace gas emissions across a wide range of soil, chamber design, and deployment scenarios.

Previous studies have shown that there is considerable population structure in cultivated barley ( Hordeum vulgare L.), with the strongest structure corresponding to differences in row number and growth habit. U.S. barley breeding programs include six‐row and two‐row types and winter and spring types in all combinations. To facilitate mapping of complex traits in breeding germplasm, 1816 barley lines from 10 U.S. breeding programs were scored with 1536 single nucleotide polymorphism (SNP) genotyping assays. The number of SNPs segregating within breeding programs varied from 854 to 1398. Model‐based analysis of population structure showed the expected clustering by row type and growth habit; however, there was additional structure, some of which corresponded to the breeding programs. The model that fit the data best had seven populations: three two‐row spring, two six‐row spring, and two six‐row winter. Average linkage disequilibrium (LD) within populations decayed over a distance of 20 to 30 cM, but some populations showed long‐range LD suggestive of admixture. Genetic distance (allele‐sharing) between populations varied from 0.11 (six‐row spring vs. six‐row spring) to 0.45 (two‐row spring vs. six‐row spring). Analyses of pairwise LD revealed that the phase of allelic associations was not well correlated between populations, particularly when their allele‐sharing distance was >0.2. These results suggest that pooling divergent barley populations for purposes of association mapping may be inadvisable.

The compartmental pharmacokinetics of anidulafungin (VER-002; formerly LY303366) in plasma were characterized with normal rabbits, and the relationships between drug concentrations and antifungal efficacy were assessed in clinically applicable infection models in persistently neutropenic animals. At intravenous dosages ranging from 0.1 to 20 mg/kg of body weight, anidulafungin demonstrated linear plasma pharmacokinetics that fitted best to a three-compartment open pharmacokinetic model. Following administration over 7 days, the mean (+/- standard error of the mean) peak plasma concentration (C(max)) increased from 0.46 +/- 0.02 microg/ml at 0.1 mg/kg to 63.02 +/- 2.93 microg/ml at 20 mg/kg, and the mean area under the concentration-time curve from 0 h to infinity (AUC(0-infinity)) rose from 0.71 +/- 0.04 to 208.80 +/- 24.21 microg. h/ml. The mean apparent volume of distribution at steady state (V(ss)) ranged from 0.953 +/- 0.05 to 1.636 +/- 0.22 liter/kg (nonsignificant [NS]), and clearance ranged from 0.107 +/- 0.01 to 0.149 +/- 0.00 liter/kg/h (NS). Except for a significant prolongation of the terminal half-life and a trend toward an increased V(ss) at the higher end of the dosage range after multiple doses, no significant differences in pharmacokinetic parameters were noted in comparison to single-dose administration. Concentrations in tissue at trough after multiple dosing (0.1 to 10 mg/kg/day) were highest in lung and liver (0.85 +/- 0.16 to 32.64 +/- 2.03 and 0.32 +/- 0.05 to 43.76 +/- 1.62 microg/g, respectively), followed by spleen and kidney (0.24 +/- 0.65 to 21.74 +/- 1.86 and <0.20 to 16.92 +/- 0.56, respectively). Measurable concentrations in brain tissue were found at dosages of > or =0.5 mg/kg (0.24 +/- 0.02 to 3.90 +/- 0.25). Implementation of optimal plasma sampling in persistently neutropenic rabbit infection models of disseminated candidiasis and pulmonary aspergillosis based on the Bayesian approach and model parameters from normal animals as priors revealed a significantly slower clearance (P < 0.05 for all dosage groups) with a trend toward higher AUC(0-24) values, higher plasma concentrations at the end of the dosing interval, and a smaller volume of distribution (P < 0.05 to 0.193 for the various comparisons among dosage groups). Pharmacodynamic modeling using the residual fungal tissue burden in the main target sites as the primary endpoint and C(max), AUC(0-24), time during the dosing interval of 24 h with plasma drug concentration equaling or exceeding the MIC or the minimum fungicidal concentration for the isolate, and tissue concentrations as pharmacodynamic parameters showed predictable pharmacokinetic-pharmacodynamic relationships in experimental disseminated candidiasis that fitted well with an inhibitory sigmoid maximum effect pharmacodynamic model (r(2), 0.492 to 0.819). However, no concentration-effect relationships were observed in experimental pulmonary aspergillosis using the residual fungal burden in lung tissue and survival as parameters of antifungal efficacy. Implementation of optimal plasma sampling in discriminative animal models of invasive fungal infections and pharmacodynamic modeling is a novel approach that holds promise of improving and accelerating our understanding of the action of antifungal compounds in vivo.