Using long-term data for a reintroduced population to empirically estimate future consequences of inbreeding

Inbreeding depression is an important long-term threat to reintroduced populations. However, the strength of inbreeding depression is difficult to estimate in wild populations because pedigree data are inevitably incomplete and because good data are needed on survival and reproduction. Predicting future population consequences is especially difficult because this also requires projecting future inbreeding levels and their impacts on long-term population dynamics, which are subject to many uncertainties. We illustrate how such projections can be derived through Bayesian state-space modeling methods based on a 26-year data set for North Island Robins (Petroica longipes) reintroduced to Tiritiri Matangi Island in 1992. We used pedigree data to model increases in the average inbreeding level (F ) over time based on kinship of possible breeding pairs and to estimate empirically N_e/N (effective/census population size). We used multiple imputation to model the unknown components of inbreeding coefficients, which allowed us to estimate effects of inbreeding on survival for all 1458 birds in the data set while modeling density dependence and environmental stochasticity. This modeling indicated that inbreeding reduced juvenile survival (1.83 lethal equivalents [SE 0.81]) and may have reduced subsequent adult survival (0.44 lethal equivalents [0.81]) but had no apparent effect on numbers of fledglings produced. Average inbreeding level increased to 0.10 (SE 0.001) as the population grew from 33 (0.3) to 160 (6) individuals over the 25 years, giving a ratio of 0.56 (0.01). Based on a model that also incorporated habitat regeneration, the population was projected to reach a maximum of 331–1144 birds (median 726) in 2130, then to begin a slow decline. Without inbreeding, the population would be expected stabilize at 887–1465 birds (median 1131). Such analysis, therefore, makes it possible to empirically derive the information needed for rational decisions about inbreeding management while accounting for multiple sources of uncertainty.     

Applying 3DCE to environmentally responsible manufacturing practices

A review of recent literature in the fields of operations, supply chain, and management indicates there is on-going interest in improving new product development (NPD) performance. Three-dimensional concurrent engineering (3DCE), the simultaneous design of product, process and supply chain have been proposed as a way to improve traditional NPD outcomes, such as reduced time to market, lower costs, and improved customer acceptance. There appears to be a lesser concern associated with the environmental impacts of new products. Environmentally responsible manufacturing (ERM) on new product development focuses on reduced emissions, hazardous materials elimination, and lower product weight without sacrificing functionality. This paper explores the following issue: will employing 3DCE to integrate NPD and ERM yield better benefits than the separate and uncoordinated application of environmental goals and NPD initiatives?     

A hierarchical Bayesian model for forecasting state-level corn yield

Historically, the National Agricultural Statistics Service crop forecasts and estimates have been determined by a group of commodity experts called the Agricultural Statistics Board (ASB). The corn yield forecasts for the “speculative region,” ten states that account for approximately 85 % of corn production, are based on two sets of monthly surveys, a farmer interview survey and a field measurement survey. The members of the ASB subjectively determine a forecast on the basis of a discussion of the survey data and auxiliary information about weather, average planting dates, and crop maturity. The ASB uses an iterative procedure, where initial state estimates are adjusted so that the weighted sum of the final state estimates is equal to a previously-determined estimate for the speculative region. Deficiencies of the highly subjective ASB process are lack of reproducibility and a measure of uncertainty. This paper describes the use of Bayesian methods to model the ASB process in a way that leads to objective forecasts and estimates of the corn yield. First, we use small area estimation techniques to obtain state-level forecasts. Second, we describe a way to adjust the state forecasts so that the weighted sum of the state forecasts is equal to a previously-determined regional forecast. We use several diagnostic techniques to assess the goodness of fit of various models and their competitors. We use Markov chain Monte Carlo methods to fit the models to both historic and current data from the two monthly surveys. Our results show that our methodology can provide reasonable and objective forecasts of corn yields for states in the speculative region.     

Patterns,correlates, and paternity consequences of extraterritorial foray behavior in the field sparrow (Spizella pusilla): an automated telemetry approach

Behavioral Ecology and Sociobiology - ᅟMales of fiddler crabs (genus: Uca) construct courtship structures using mud or sand to attract mate-searching females for underground mating. A sensory...     

A comparison of storm-based and annual-based indices of hydrologic variability: a case study in Fort Benning, Georgia

The magnitude, frequency, duration, timing, and rate of change of hydrologic conditions regulate ecological processes in aquatic ecosystems. Conditions are typically characterized using annual-based hydrologic indices derived from daily and/or monthly stream flow data. In this study, we present an alternative approach to identify hydrologic indices based on storm hydrographs. Hydrologic indices derived from long-term daily flow data were compared to those from storm events for two headwater watersheds in Fort Benning, Georgia. Five hydrologic indices derived from daily flow data and storm events shared common features. Storm-based magnitude of mean peak discharge and mean response factor, frequency of bankfull discharge, rate of change in mean slopes of rising, and falling limb of the hydrograph were consistent with the results from long-term daily flow data. The annual flow increases and decreases were well matched by stormflow rising and falling. Both indicators showed one watershed having three times the response rates as compared to the other. Results suggested that select storm-based indices may be used as surrogates to the indices derived from long-term data.     

Resident Motivations and Willingness-to-Pay for Urban Biodiversity Conservation in Guangzhou (China)

The monetary assessment of biodiversity measures the welfare damages brought by biodiversity losses and the cost-benefit analysis of conservation projects in a socio-economic context. The contingent valuation method could include motivational factors to strengthen economic analysis of nature conservation. This study analyzed Guangzhou residents’ motivations and willingness-to-pay (WTP) for an urban biodiversity conservation program in the National Baiyun Mountain Scenic Area (BMSA). The peri-urban natural site, offering refuge to some endemic species, is under increasing development pressures for recreational and residential use. A questionnaire survey was conducted in the Guangzhou metropolitan area during June to October 2007. We interviewed face-to-face 720 stratified sampled households to probe residents’ attitudes towards the city’s environmental issues, motivations for urban nature conservation, and WTP for biodiversity conservation. Principal component analysis identified five motivational factors, including environmental benefit, ecological diversity, nature-culture interaction, landscape-recreation function, and intergenerational sustainability, which illustrated the general economic values of urban nature. Logistic regression was applied to predict the probability of people being willing to pay for the urban biodiversity conservation in BMSA. The significant predictors of WTP included household income and the factor nature-culture interaction. The median WTP estimated RMB149/household (about US$19.5/household) per year and an aggregate of RMB291 million (approximately US$19.5/household) per year and an aggregate of RMB291 million (approximately US38.2 million) annually to support the urban conservation project. Including public motivations into contingent valuation presents a promising approach to conduct cost-benefit analysis of public projects in China.