Yield response of potato to spatially patterned nitrogen application

Although crop response to nitrogen fertilization has long been studied, classical experimental designs have led to inadequate accounting of spatial variability in field properties and yield response. Analytical methods to explicitly account for spatial variability now exist but the complementary modification of experimental design is still developing. There is a need to combine these analytical methods with non-traditional experimental design. A 2-year study was implemented to assess the response of potato (Solanum tuberosum cv. Kennebec) yield to nitrogen fertilizer rate. We used a transect-type plot design where four nitrogen treatments (0, 56, 112, and 280 kg N ha^?1) were applied systematically in a continuous sinusoidal pattern along longitudinal transects. Measured field properties included topography, soil texture, pre-application soil nitrate levels, and plant available soil water content. A random field linear model was used to simultaneously account for treatment effects and soil properties. The results showed that treatment effects were significantly different from each other; however, if spatially correlated errors were accounted for, these differences were smaller and significance levels lower. Nitrogen response functions varied widely throughout the field. Of the covariates, only clay content proved important in explaining spatial differences in response to N. The sinusoidal response pattern of N was similar over the 2 years but the amplitudes varied due to differences in weather. Interactions between uncharacteristically high rainfall and a sandy field soil may have minimized discernable effects of the other covariates. The results demonstrated how the statistical analysis of potato response to a patterned application of nitrogen fertilizer can take advantage of spatial correlations to understand the response of potato to nitrogen application over larger areas.     

Modelling with uncertainty: Introducing a probabilistic framework to predict animal population dynamics

Predictive population models designed to assist managers and policy makers require an explicit treatment of inherent uncertainty and variability. These are particular concerns when modelling non-native and reintroduced species, when data have been collected within one geographical or ecological context but predictions are required for another, or when extending models to predict the consequences of environmental change (e.g., climate or land-use). We present an aspatial, probabilistic framework of hierarchical process models for predicting population growth even when data are sparse or of poor quality. Insight into the factors affecting population dynamics in real landscapes can be provided and Kullback–Leibler distances are used to compare the relative output of models. This flexible yet robust framework gives easily interpretable results, allowing managers as well as modellers to invalidate anomalous models and apply others to real-life scenarios.We illustrate the framework’s power with a meta-analysis of European wild boar (Sus scrofa) data. We test hypotheses about the effect of geographic region, hunting and mast years on wild boar population growth, to build models of wild boar dynamics for the UK. The framework quantifies the importance of hunting pressure as a driver of population growth, and confirms that reproductive success is greatly decreased in poor mast years, suggesting that the key to predicting wild boar dynamics is to ascertain local hunting pressure and to better understand changing food availability. Geography had no significant effect, indicating that it is not a good proxy for modelling the impact of change in climate or land-use on wild boar populations at the European scale. We use the framework to predict population abundance 9 years after an isolated population of wild boar established in the UK; in a comparison with the only field data and two independent modelling exercises, our framework provides the most robust and informative results.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.     

Prevalence of the Crayfish Plague Pathogen Aphanomyces astaci in Invasive American Crayfishes in the Czech Republic

Abstract:  In Central Europe invasive North American crayfishes are carriers of the oomycete Aphanomyces astaci, which causes crayfish plague. This lethal disease currently represents one of the major threats to native European crayfishes. We used molecular methods—species-specific amplification and sequencing of the pathogen DNA—to investigate the prevalence of individuals latently infected with A. astaci in 28 populations of two invasive American crayfish species (6 of the signal crayfish [ Pacifastacus leniusculus ] and 22 of the spiny-cheek crayfish [ Orconectes limosus ]) in the Czech Republic. The pathogen occurred in 17 investigated populations. We recorded a high variation in positive reactions, ranging from 0% to 100%, in populations of O. limosus . In P. leniusculus, however, only one individual out of 124 tested positive for the pathogen. There was a clear relationship between the water body type and pathogen prevalence in O. limosus . Infection ratios in isolated standing waters were usually low, whereas in running waters, pathogen prevalence often exceeded 50%. Other evaluated characteristics of potential plague pathogen carriers (size, sex, and the presence of melanized spots in the cuticle) seemed to be unrelated to infection. Our data suggest that in contrast to other European countries, O. limosus seems to be the primary reservoir of crayfish plague in the Czech Republic. Although all populations of alien American crayfishes may be potential sources of infections and should be managed as such, knowledge on the prevalence of the plague pathogen at various localities may allow managers to focus conservation efforts on the most directly endangered populations of native crayfishes.     

Biodiversity Conservation and Indigenous Land Management in the Era of Self‐Determination

Abstract: Indigenous people inhabit approximately 85% of areas designated for biodiversity conservation worldwide. They also continue to struggle for recognition and preservation of cultural identities, lifestyles, and livelihoods—a struggle contingent on control and protection of traditional lands and associated natural resources (hereafter, self‐determination). Indigenous lands and the biodiversity they support are increasingly threatened because of human population growth and per capita consumption. Application of the Endangered Species Act (ESA) to tribal lands in the United States provides a rich example of the articulation between biodiversity conservation and indigenous peoples' struggle for self‐determination. We found a paradoxical relationship whereby tribal governments are simultaneously and contradictorily sovereign nations; yet their communities depend on the U.S. government for protection through the federal‐trust doctrine. The unique legal status of tribal lands, their importance for conserving federally protected species, and federal environmental regulations' failure to define applicability to tribal lands creates conflict between tribal sovereignty, self‐determination, and constitutional authority. We reviewed Secretarial Order 3206, the U.S. policy on “American Indian tribal rights, federal–tribal trust responsibilities, and the ESA,” and evaluated how it influences ESA implementation on tribal lands. We found improved biodiversity conservation and tribal self‐determination requires revision of the fiduciary relationship between the federal government and the tribes to establish clear, legal definitions regarding land rights, applicability of environmental laws, and financial responsibilities. Such actions will allow provision of adequate funding and training to tribal leaders and resource managers, government agency personnel responsible for biodiversity conservation and land management, and environmental policy makers. Increased capacity, cooperation, and knowledge transfer among tribes and conservationists will improve biodiversity conservation and indigenous self‐determination.