Driving forces of soil organic carbon evolution at the landscape and regional scale using data from a stratified soil monitoring

Soil monitoring programmes face significant challenges as there is an important trade‐off between detecting significant changes in soil properties on the one hand (which can be achieved by minimizing variability by higher sampling density or stratification approaches), and identifying the driving forces responsible for these changes on the other hand (which requires enough variability). This study aims to reconcile these two objectives by identifying the driving forces of soil organic carbon (SOC) evolution over a long period, based on an extensive but stratified soil monitoring programme. Data at both the finest level (questionnaires to the farmers) and the large scale (agricultural census, climate and soil databases for southern Belgium) were used in a cluster analysis, multiple linear regressions and mixed odels in order to discriminate between the driving forces involved. Results indicated that the negative ‘baseline effect’ (i.e. the inversely proportional effect of the initial SOC content on the SOC evolution) was responsible for an important part of the SOC variability. Consequently, the systems are not at steady state when starting the observations, although this assumption is used by most SOC dynamic models. Moreover, the baseline effect resulted in a trend of the soils to converge towards a regional SOC stock which significantly differed according to land use (36.4 t C ha^?1 for the plough depth of cropland and 92.2 t C ha^?1 for the 0–30 cm layer of grassland). Despite this strong effect, the main driving forces of the SOC decrease of cropland (?0.2 t C ha^?1 yr^?1) and SOC increase of grassland (+0.2 t C ha^?1 yr^?1) over a period of 50 years were discriminated. The agricultural management (cropland) and the clay content (grassland), together with the change in precipitation (to a lesser degree for cropland) were highlighted as the predominant factors involved in SOC evolution, when land use change is excluded. The use of questionnaires allowed to better understanding the impact of an intensive agricultural management on the SOC content, as the lowest SOC stocks were associated to the most intensively managed fields. The mixed models partly succeeded in predicting SOC evolution as they presented still large uncertainties after validation (mean error from 3% to 25%, root mean square error of prediction from 21% to 242%). While SOC monitoring schemes are increasingly being implemented, our results will likely apply to those using a similar design. It was shown that this strategy succeeded to reconcile both the SOC change detection and the distinction of the driving forces involved at the regional scale.     

Ecological assessment of plant communities by reference to species traits and habitat preferences

Where vegetation is managed for nature conservation, results should be assessed against criteria linked to the objectives of management. An assessment method is presented in which the goal vegetation was defined as a specific biotope limited by a set of biophysical conditions. Vegetation was sampled from field boundary strips intended for the conservation of arable plant communities. Species suited to the specified conditions (suited species) were defined by applying rule sets to a matrix of species with their traits and habitat preferences, compiled from a range of data sources. The proportional contribution of suited species to the total vegetation was calculated for each set of conditions. Scores for each condition (suited species scores) were combined to provide overall comparative site values representing the extent to which the goal vegetation was established. There was close correlation with results of a previous assessment by expert opinion poll. Variation between sites in soil type and cultivation frequency was reflected by differences in individual suited species scores. Ideally, suited species selection would be by traits alone but currently there are insufficient data available. The method is readily applicable to other vegetation types.     

Validation of a decision support system for the cytodiagnosis of fine needle aspirates of the breast using a prospectively collected dataset from multiple observers in a working clinical environment

We have used a 692 case dataset, collected retrospectively by a single observer, to develop decision support systems for the cytodiagnosis of fine needle aspirates of breast lesions. In this study, we use a 322 case dataset that was prospectively collected by multiple observers in a working clinical environment to test two predictive systems, using logistic regression and the multilayer perceptron (MLP) type of neural network. Ten observed features and the patient age were used as input features. The systems were developed using a training set and test set from the single observer dataset and then applied to the multiple observer dataset. For the independent test cases from the single observer dataset, with a threshold set for no false positives on the training set, logistic regression produced a sensitivity of 82% (95% confidence interval 73-91) and a predictive value of a positive result (PV +) of 98% (95-99), the values for the MLP were 79% (69-89) and 100%, respectively. However the performance on the prospective multiple observer dataset was much worse, with a sensitivity of 72% (65-80), and PV + of 97% (94-99) for logistic regression and 67% (60-75) and 91% (85-97) for the MLP. These results suggest that there is considerable interobserver variability for the defined features and that this system is unsuitable for further development in the clinical environment unless this problem can be overcome.     

Developing tests of successional hypotheses with size-structured populations,and an assessment using long-term data from a Ugandan rain forest

In 1947, W. J. Eggeling published an account of forest succession at Budongo, Uganda. This interpretation was based on a large-scale comparative plot study, performed in the 1930s and 1940s. This account, with its implication that species richness declines in late succession, endures as a controversial corner-stone in theories and disputes about community diversity. Data have now been collected over six decades from five of Eggeling's original plots.This paper evaluates Eggeling's successional interpretation of the Budongo vegetation. The first set of analyses assesses the consistency of the original data with the predictions of compositional progression and convergence implicit in Eggeling's model. The second analyses do the same for the time-series observations. A logical approach shows how temporal information may be derived from both between plot, and within plot, evaluations using size-structured data. A Detrended-Correspondence-Analysis (DCA) of canopy-tree composition, from the original data, ranks the plots in perfect correspondence to Eggeling's successional sequence. A development-scoring procedure is developed using passive-ordination against this sequence; this is then applied to composition by plot and stem-size class.Eggeling's original data are consistent with each prediction assessed. The analyses show compositional progression and apparent convergence across the plot series, and also progression and convergence within each plot. A monodominant-Cynometra forest is the natural end-point of this progression. The time-series results, though in apparent agreement for one early successional plot, do not generally accord with Eggeling's ideas. The analyses illustrate a general means for evaluating explicit and implicit compositional trends in communities with structured populations.     

Determinants of bird species richness: role of climate and vegetation structure at a regional scale

We examined the respective roles of climate and vegetation structure on geographical variation in bird species richness. The Province of Buenos Aires (central-eastern Argentina) was divided into 146 squares of 50 km on a side. For each square we evaluated the number of bird species, the value of thirteen climatic variables, and the value of a vegetation strata index. The climatic matrix was analyzed by Principal Component Analysis (PCA), and the first factors resulting from PCA were considered as multifactorial climatic gradients. Simple and Partial Correlation Analysis among bird species richness, vegetation strata, and the first two factors derived from PCA (65% of total variation) indicated that bird richness distribution was determined by the availability of vegetation strata, associated with different vegetation types that, at the same time, were influenced by the climatic conditions summarized in the first climatic factor (a gradient of precipitation, relative humidity, annual termical amplitude, and frost occurrence). This relationships reflect the complexity of factors that can act directly as well as indirectly on the geographical patterns in species richness. Also, we evaluated the importance of study scale comparing our results with previous studies at macrogeographic and local scales, found out that the vegetation structure was the principal determinant of bird species richness at this three geographical scales.     

The regional effects of CO2 and landscape change using a coupled plant and meteorological model

A meteorological model, the Regional Atmospheric Modelling System (RAMS), and a plant model, the General Energy and Mass Transfer Model (GEMTM), are coupled in this study. The integrated modelling system was used to investigate regional weather conditions in the central grasslands of the USA for three experimental scenarios: ? land cover is changed from current to potential vegetation; ? radiative forcing is changed from 1 × CO₂ to 2 × CO₂; and ? biological CO₂ partial pressures are doubled. Results indicate that the biological effect of enriched CO₂, and of land‐use change exhibit dominant effects on regional meteorological and biological fields, which were observed for daily to seasonal time scales and grid to regional spatial scales. Simulated radiation impacts of 2 × CO₂ were minimal, with interactive effects between the three experimental scenarios as large as the radiational impact alone. Model results highlight the importance of including 2 × CO₂ biological effects when simulating possible future changes in regional weather.     

Spatio‐temporal scaling of biodiversity and the species–time relationship in a stream fish assemblage

1. The increase of species richness with the area of the habitat sampled, that is the species–area relationship, and its temporal analogue, the species–time relationship (STR), are among the few general laws in ecology with strong conservation implications. However, these two scale‐dependent phenomena have rarely been considered together in biodiversity assessment, especially in freshwater systems. 2. We examined how the spatial scale of sampling influences STRs for a Central‐European stream fish assemblage (second‐order Bernecei stream, Hungary) using field survey data in two simulation‐based experiments. 3. In experiment one, we examined how increasing the number of channel units, such as riffles and pools (13 altogether), and the number of field surveys involved in the analyses (12 sampling occasions during 3 years), influence species richness. Complete nested curves were constructed to quantify how many species one observes in the community on average for a given number of sampling occasions at a given spatial scale. 4. In experiment two, we examined STRs for the Bernecei fish assemblage from a landscape perspective. Here, we evaluated a 10‐year reach level data set (2000–09) for the Bernecei stream and its recipient watercourse (third‐order Kemence stream) to complement results on experiment one and to explore the mechanisms behind the observed patterns in more detail. 5. Experiment one indicated the strong influence of the spatial scale of sampling on the accumulation of species richness, although time clearly had an additional effect. The simulation methodology advocated here helped to estimate the number of species in a diverse combination of spatial and temporal scale and, therefore, to determine how different scale combinations influence sampling sufficiency. 6. Experiment two revealed differences in STRs between the upstream (Bernecei) and downstream (Kemence) sites, with steeper curves for the downstream site. Equations of STR curves were within the range observed in other studies, predominantly from terrestrial systems. Assemblage composition data suggested that extinction–colonisation dynamics of rare, non‐resident (i.e. satellite) species influenced patterns in STRs. 7. Our results highlight that the determination of species richness can benefit from the joint consideration of spatial and temporal scales in biodiversity inventory surveys. Additionally, we reveal how our randomisation‐based methodology may help to quantify the scale dependency of diversity components (α, β, γ) in both space and time, which have critical importance in the applied context.     

Predictive map of Ixodes ricinus high-incidence habitats and a tick-borne encephalitis risk assessment using satellite data

The main objective of this project was to predict Ixodes ricinus abundant habitats reliably as a means of tick-borne encephalitis (TBE) risk assessment for the prevention of this disease. The vegetation types were used as the indicators of an ecosystem suitable for tick occurrence, for TBE virus circulation and, accordingly, for the existence of natural foci of this infection. Remote sensing methods were used to determine the indicative plant cover. Satellite data covering an experimental area of 70 × 70 km in Central Bohemia, the Czech Republic, was acquired by the Landsat 5 TM scanner. Nine forest classes were recognized in the experimental area by successive supervised and unsupervised classifications and identified in a field-checking botanical survey. An epidemiological TBE map based on human cases contracted in the territory under study was exploited for the evaluation of risk in particular forest classes. Predictive maps are expressed both in digital and in printed forms at a scale of 1 : 300 000 for an overall risk evaluation and at a scale of 1 : 25 000 for a detailed local orientation.     

Harnessing the potential of the multi‐indicator palaeoecological approach: an assessment of the nature and causes of ecological change in a eutrophic shallow lake

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Quantifying carbon sequestration as a result of soil erosion and deposition: retrospective assessment using caesium-137 and carbon inventories

The role of soil erosion in the global carbon cycle remains a contested subject. A new approach to the retrospective derivation of erosion‐induced quantitative fluxes of carbon between soil and atmosphere is presented and applied. The approach is based on the premise that soil redistribution perturbs the carbon cycle by driving disequilibrium between soil carbon content and input. This perturbation is examined by establishing the difference between measured carbon inventories and the inventories that would be found if input and content were in dynamic equilibrium. The carbon inventory of a profile in dynamic equilibrium is simulated by allowing lateral and vertical redistribution of carbon but treating all other profile inputs as equal to outputs. Caesium‐137 is used to derive rates of vertical and lateral soil redistribution. Both point and field‐scale estimates of carbon exchange with the atmosphere are derived using the approach for a field subject to mechanized agricultural in the United Kingdom. Sensitivity analysis is undertaken and demonstrates that the approach is robust. The results indicate that, despite a 15% decline in the carbon content of the cultivation layer of the eroded part of the field, this area has acted as a net sink of 11 ± 2 g C m^?2 yr^?1 over the last half century and that in the field as a whole, soil redistribution has driven a sink of 7 ± 2 g C m^?2 yr^?1 (6 ± 2 g C m^?2 yr^?1 if all eroded carbon transported beyond the field boundary is lost to the atmosphere) over the same period. This is the first empirical evidence for, and quantification of, dynamic replacement of eroded carbon. The relatively modest field‐scale net sink is more consistent with the identification of erosion and deposition as a carbon sink than a carbon source. There is a clear need to assemble larger databases with which to evaluate critically the carbon sequestration potential of erosion and deposition in a variety of conditions of agricultural management, climate, relief, and soil type. In any case, this study demonstrated that the operation of erosion and deposition processes within the boundaries of agricultural fields must be understood as a key driver of the net carbon cycle consequences of cultivating land.     

On the limitations of life cycle assessment and environmental systems analysis tools in general

The potential and limitations of life cycle assessment and environmental systems analysis tools in general are evaluated. More specifically this is done by exploring the limits of what can be shown by LCA and other tools. This is done from several perspectives. First, experiences from current LCAs and methodology discussions are used including a discussion on the type of impacts typically included, quality of inventory data, methodological choices in relation to time aspects, allocation, characterisation and weighting methods and uncertainties in describing the real world. Second, conclusions from the theory of science are practised. It is concluded that it can in general not be shown that one product is environmentally preferable to another one, even if this happens to be the case. This conclusion has important policy implications. If policy changes require that it must be shown that one product is more (or less) environmentally preferable before any action can be taken, then it is likely that no action is ever going to take place. If we want changes to be made, decisions must be taken on a less rigid basis. It is expected that in this decision making process, LCA can be a useful input. Since it is the only tool that can be used for product comparisons over the whole life cycle, it can not be replaced by any other tool and should be used. Increased harmonisation of LCA methodology may increase the acceptability of chosen methods and increase the usefulness of the tool.     

Achieving Target 2 of the Global Strategy for Plant Conservation: building a preliminary assessment of vascular plant species using data from herbarium specimens

The Global Strategy for Plant Conservation calls for a preliminary assessment of the conservation status of all known plant species by the year 2010. To date insufficient progress has been made on meeting this target. New efforts to develop a preliminary list beyond using the full IUCN criteria in plant assessments are needed. Here we present an algorithm that provides a preliminary assessment of the conservation status of plant species using data from herbarium specimens. We use Hawaiian specimen data from the United States National Herbarium to calibrate the parameters of the algorithm and then use specimen data from the Arecaceae, Commelinaceae, Gesneriaceae and Heliconiaceae as examples of the application of the algorithm. The algorithm was calibrated to insure 95% accuracy in placing the Hawaiian plant species into previously and independently determined threatened categories. Our results indicate that 28% of the Hawaiian taxa, 27% of the species of Arecaceae, 45% of the species of Commelinaceae, 32% of the species of Gesneriaceae, and 35% of the species of Heliconiaceae are Not Threatened and will not need any further evaluation for the preliminary assessment. Species identified here as Potentially Extinct and Potentially Threatened can be further assessed by additional herbarium material and/or conservation specialists for final evaluation using other assessment strategies (e.g., regional and national lists, taxonomic expert assessment, etc.).     

Effects of the sampling design and selection of parameter values on pollen-based quantitative reconstructions of regional vegetation: a case study in southern Sweden using the REVEALS model

The need for quantification of land cover from pollen data has led to the development of a Landscape Reconstruction Algorithm (LRA). The LRA includes several models of which the REVEALS model estimates regional vegetation abundance using pollen assemblages from large sites (lakes or bogs). In this paper we explore the effects of selection and number of pollen samples, and choice of pollen productivity estimates on the REVEALS results. The effect of the size of vegetation surveys is also tested. The results suggest that the differences between two sizes of vegetation surveys have little effect on the model validation. The “characteristic radius” of regional vegetation in southern Sweden was estimated as 200 km. However, the vegetation composition in a 100 × 100 km² square matches well with that estimated by REVEALS. Whether 25, 20 (outliers excluded) or 4 pollen samples are used does not change the REVEALS reconstructions much although the error estimates are larger when outliers are included, and very large when only four samples are used. Therefore validation of the REVEALS model and REVEALS reconstructions of past vegetation can be performed using a limited number of pollen samples, although with caution. The use of many pollen samples from multiple sites is always better whenever possible. REVEALS reconstructions are closer to the actual vegetation when the Danish Pollen Productivity Estimates (PPEs) are used instead of the Swedish PPEs for Cereals, Rumex acetosa/acetosella, Plantago lanceolata and Calluna, indicating that the Danish PPEs are more reliable than the Swedish ones for those taxa. It is recommended to test more than one set of PPEs in validation and applications of the REVEALS model for a better evaluation of the results.     

Addressing a whole bioprocess in real-time using an optical biosensor-formation,recovery and purification of antibody fragments from a recombinant<Emphasis Type="Italic"> E. coli</Emphasis> host

The use of biosensor technology is described to address in real-time the production and subsequent purification of a bioactive recombinant protein product. The product, D1.3 Fv antibody fragment, was expressed in Escherichia coli and purified via two process routes, one for extracellular and one for intracellular product material. The cells were harvested by centrifugation in a solid bowl CARR Powerfuge and stored at –70°C. Clarification of the supernatant was performed by depth filtration, followed by affinity chromatography for final purification of the extracellular product. To purify the intracellular product the harvested cells were resuspended and homogenised. Removal of debris in the CARR Powerfuge was followed by depth filtration and affinity chromatography. In this work we have shown the rapid determination of bioactive product levels, and the impact this has on improved accountability and confidence is demonstrated in process mass balances on the product using the data acquired during process operation.     

Application and assessment of a nutrient pollution indicator using eelgrass (Zostera marina L.) in Barnegat Bay-Little Egg Harbor estuary, New Jersey

Eutrophication degrades numerous estuaries worldwide and a myriad of assessment metrics have been developed. Here, we apply an example of a previously developed metric (Lee et al., 2004) designed to indicate incipient estuarine eutrophication to validate this technique in an already eutrophic estuary end-member, Barnegat Bay-Little Egg Harbor, New Jersey. The metric, termed ‘Nutrient Pollution Indicator’ (NPI) uses eelgrass (Zostera marina L.) as a bioindicator and is calculated as the ratio of leaf nitrogen content (%N) to area normalized leaf mass (mg dry wt cm⁻²). Eelgrass samples were collected along the entire length of the Barnegat Bay-Little Egg Harbor from June to October 2008 to determine if leaf chemistry and morphology reflect eutrophication status and a north-south gradient of nitrogen loading from the Barnegat Bay watershed. Nitrogen content, area normalized leaf mass, and NPI values all significantly (p < 0.05) varied temporally but not spatially. NPI values did not significantly correspond to the north-south gradient of nitrogen loading from the Barnegat Bay watershed. The NPI metric is therefore not deemed to reliably indicate estuarine eutrophic status. Differences between sampling effort (number of stations) and replication did not bias the overall conclusions.     

Towards a more objective assessment of equine personality using behavioural and physiological observations from performance test training

Current definitions of horse personality traits are rather vague, lacking clear, universally accepted guidelines for evaluation in performance tests. Therefore, the aim of the present study was to screen behavioural and physiological measurements taken during riding for potential links with scores the same horses received in the official stallion performance test for rideability and personality traits. Behaviour, heart rate (HR) and HR variability from thirty-six stallions participating in a performance test were recorded repeatedly during their performance test training. Using the coefficient of determination, regression analysis revealed that about 1/3 of variation (ranging between r = 0.26 (“constitution” (i.e. fitness, health)) and r = 0.46 (rideability)) in the personality trait scores could be explained by selecting the three most influential behaviour patterns per trait. These behaviour patterns included stumbling (with all traits except character), head-tossing (temperament, rideability), tail-swishing (willingness to work), involuntary change in gait (character) and the rider's use of her/his hands (constitution, rideability), voice (temperament) or whip (constitution). Subsequent mixed model analysis revealed a significant (P < 0.05) influence of the behaviour pattern “horse-induced change in gait” on character (−0.98 ± 0.31 scores per additional occurrence of change in gaits), of head-tossing (−0.25 ± 0.08 scores) and rider's use of voice (−0.51 ± 0.25; P = 0.0594) on temperament, and of stumbling on each of the following: willingness to work (−2.5 ± 1.2), constitution (−2.5 ± 1.2 scores; P = 0.0516) and rideability scores (−3.3 ± 1.4). In addition, constitution scores tended (P = 0.0889) to increase with higher low frequency/high frequency heart rate variation ratios (LF/HF), indicating a shift towards sympathetic dominance and thus a higher stress load in horses with higher scores for constitution. Rideability scores from the training phase were also significantly influenced by head-tossing (−0.5 ± 0.1), and in addition rideability scores from the final test were influenced by the training rider, ranging between average estimated rideability scores of 6.8 ± 0.4 for one training rider and 8.36 ± 0.3 scores for another training rider. Horses ridden with their nose-line predominantly behind the vertical received higher scores for rideability (8.3 ± 0.3) than horses ridden with their nose-line at the vertical (7.7 ± 0.2). These findings indicate that either judges perceive horses to have a better rideability when they readily offer a more extreme poll flexion, or that riders make use of horses’ better rideability by imposing a more extreme poll flexion. Several of the above described associations, but also of the non-existing links (e.g. no association between shying or heart rate and temperament) between behaviour patterns and scores for personality traits are rather surprising, warranting further investigation regarding the underlying causes of these relationships. Some of these behaviour patterns should be considered when redesigning the current guidelines for evaluation of personality traits during breeding horse performance tests, ultimately leading to improved genetic selection for equine personality traits. However, ethical implication of defining aversive behaviour such as head-tossing as an indicator of, for example, poor temperament, should not be neglected when devising new guidelines: such aversive behaviour may in fact be an indication of inadequate training techniques rather than poor horse personality.     

A simple field validation of daily transpiration derived from sapflow using a porometer and minimal meteorological data

Heat-pulse techniques are routinely used to estimate transpiration from canopies of woody plants typically without any local calibration, mainly because of the difficulty of doing so in the field and, frequently, lack of detailed weather data. This is despite concerns that the techniques may produce erroneous values under certain conditions, such as when evaporative demand is high. In this study, we used a micrometeorological approach to validate transpiration from irrigated olives deduced from heat-pulse technique by ascertaining precise values for the parameters that are critical for converting heat-pulse velocity to sapflow. The micrometeorological approach involved limited data on stomatal conductance (g_s), obtained hourly with a porometer on four contrasting days, and was used to calibrate a simple model for predicting conductance. Predicted stomatal conductance (g_sm) agreed well with that measured, and when both were used to calculate hourly transpiration, they produced values that were within 10% of each other. This was despite brief underestimations of transpiration based on g_sm (T_m) in the early hours of the day that arose from poor determination of incident radiation at this time. We then used T_m to iteratively set the values for the various parameters, including the time-out value that accounts for zero-flow conditions, needed to convert heat-pulse velocity to sapflow, for the four days. The best fit between T_m and transpiration from sapflow (T_s) was obtained with time-out value set to 120 s. All heat-pulse velocity data were therefore analysed with this time-out value to obtain sapflow and, hence, transpiration (T_s). Comparison of T_m and T_s for the whole season showed that the former tended to produce higher values on certain days when vapour pressure deficit (D) was high in summer (December–February). While T_s occasionally produced larger values than T_m under the mild conditions of autumn (March–April). Totals of the daily transpiration during the 190-day period were within 10% of each other. Responsible Editor: Yan Li     

Life history costs and benefits of encephalization: a comparative test using data from long-term studies of primates in the wild

The correlation between brain size and life history has been investigated in many previous studies, and several viable explanations have been proposed. However, the results of these studies are often at odds, causing uncertainties about whether these two character complexes underwent correlated evolution. These disparities could arise from the mixture of wild and captive values in the datasets, potentially obscuring real relationships, and from differences in the methods of controlling for phylogenetic non independence of species values. This paper seeks to resolve these difficulties by (1) proposing an overarching hypothesis that encompasses many of the previously proposed hypotheses, and (2) testing the predictions of this hypothesis using rigorously compiled data and utilizing multiple methods of analysis. We hypothesize that the adaptive benefit of increased encephalization is an increase in reproductive lifespan or efficiency, which must be sufficient to outweigh the costs due to growing and maturing the larger brain. These costs and benefits are directly reflected in the length of life history stages. We tested this hypothesis on a wide range of primate species. Our results demonstrate that encephalization is significantly correlated with prolongation of all stages of developmental life history except the lactational period, and is significantly correlated with an extension of the reproductive lifespan. These results support the contention that the link between brain size and life history is caused by a balance between the costs of growing a brain and the survival benefits the brain provides. Thus, our results suggest that the evolution of prolonged life history during human evolution is caused by increased encephalization.     

Phylogeny and biogeography of Croton alabamensis (Euphorbiaceae), a rare shrub from Texas and Alabama, using DNA sequence and AFLP data

Croton alabamensis (Euphorbiaceae s.s.) is a rare plant species known from several populations in Texas and Alabama that have been assigned to var. texensis and var. alabamensis, respectively. We performed maximum parsimony, maximum likelihood, and Bayesian analyses of DNA sequences from the nuclear ribosomal internal transcribed spacer (ITS) and 5.8S regions and chloroplast trnL-trnF regions from collections of the two varieties of C. alabamensis and from outgroup taxa. C. alabamensis emerges alone on a long branch that is sister to Croton section Corylocroton and the Cuban endemic genus Moacroton. Molecular clock analysis estimates the split of C. alabamensis from its closest relatives in sect. Corylocroton at 41 million years ago, whereas the split of the two varieties of C. alabamensis occurred sometime in the Quaternary. Amplified fragment length polymorphism (AFLP) analyses were performed using two selective primer pairs on a larger sampling of accessions (22 from Texas, 17 from Alabama) to further discriminate phylogenetic structure and quantify genetic diversity. Using both neighbour joining and minimum evolution, the populations from the Cahaba and Black Warrior watersheds in Alabama form two well-separated groups, and in Texas, geographically distinct populations are recovered from Fort Hood, Balcones Canyonlands, and Pace Bend Park. Most of the molecular variance is accounted for by variance within populations. Approximately equal variance is found among populations within states and between states (varieties). Genetic distance between the Texas populations is significantly less than genetic distance between the Alabama populations. Both sequence and AFLP data support the same relationships between the varieties of C. alabamensis and their outgroup, while the AFLP data provide better resolution among the different geographical regions where C. alabamensis occurs. The conservation implications of these findings are discussed.