Improving inferences about private land conservation by accounting for incomplete reporting

Private lands provide key habitat for imperiled species and are core components of function protectected area networks; yet, their incorporation into national and regional conservation planning has been challenging. Identifying locations where private landowners are likely to participate in conservation initiatives can help avoid conflict and clarify trade-offs between ecological benefits and sociopolitical costs. Empirical, spatially explicit assessment of the factors associated with conservation on private land is an emerging tool for identifying future conservation opportunities. However, most data on private land conservation are voluntarily reported and incomplete, which complicates these assessments. We used a novel application of occupancy models to analyze the occurrence of conservation easements on private land. We compared multiple formulations of occupancy models with a logistic regression model to predict the locations of conservation easements based on a spatially explicit social–ecological systems framework. We combined a simulation experiment with a case study of easement data in Idaho and Montana (United States) to illustrate the utility of the occupancy framework for modeling conservation on private land. Occupancy models that explicitly accounted for variation in reporting produced estimates of predictors that were substantially less biased than estimates produced by logistic regression under all simulated conditions. Occupancy models produced estimates for the 6 predictors we evaluated in our case study that were larger in magnitude, but less certain than those produced by logistic regression. These results suggest that occupancy models result in qualitatively different inferences regarding the effects of predictors on conservation easement occurrence than logistic regression and highlight the importance of integrating variable and incomplete reporting of participation in empirical analysis of conservation initiatives. Failure to do so can lead to emphasizing the wrong social, institutional, and environmental factors that enable conservation and underestimating conservation opportunities in landscapes where social norms or institutional constraints inhibit reporting.     

A Bayesian hierarchical approach to quantifying stakeholder attitudes toward conservation in the presence of reporting error

Stakeholder support is vital for achieving conservation success, yet there are few reliable mechanisms to monitor stakeholder attitudes toward conservation. Approaches used to assess attitudes rarely account for bias arising from reporting error, which can lead to falsely reporting a positive attitude toward conservation (false-positive error) or not reporting a positive attitude when the respondent has a positive attitude toward conservation (false-negative error). Borrowing from developments in applied conservation science, we used a Bayesian hierarchical model to quantify stakeholder attitudes as the probability of having a positive attitude toward wildlife notionally (or in abstract terms) and at localized scales while accounting for reporting error. We compared estimates from our model, Likert scores, and naïve estimates (i.e., proportion of respondents reporting a positive attitude in at least 1 question that was only susceptible to false-negative error) with true stakeholder attitudes through simulations. We then applied the model in a survey of tea estate staff on their attitudes toward Asian elephants (Elephas maximus) in the Kaziranga–Karbi Anglong landscape of northeast India. In simulations, Bayesian model estimates of stakeholder attitudes toward wildlife were less biased than naïve estimates or Likert scores. After accounting for reporting errors, we estimated the probability of having a positive attitude toward elephants notionally as 0.85 in the Kaziranga landscape, whereas the proportion of respondents who had positive attitudes toward elephants at a localized scale was 0.50. In comparison, without accounting for reporting errors, naïve estimates of proportions of respondents with positive attitudes toward elephants were 0.69 and 0.23 notionally and at local scales, respectively. False (positive and negative) reporting probabilities were consistently not 0 (0.22–0.68). Regular and reliable assessment of stakeholder attitudes–combined with inference on drivers of positive attitudes–can help assess the success of initiatives aimed at facilitating human behavioral change and inform conservation decision making.     

Gender and career success: A typology and analysis of dual paradigms

Despite women's advancements in the workplace, gender inequality persists. We classify and test two frameworks used to explain gender differences in career success: unequal attributes and unequal effects. The unequal attributes framework suggests that gender is related to other attributes, which result in unequal career outcomes for men and women (i.e., a mediated effect). The unequal effects framework suggests that even when men and women share the same attribute or circumstances, they are rewarded differently, such that individual attributes have unequal effects on career outcomes for men and women (i.e., a moderated effect). We collected survey data from a gender‐balanced sample of 394 business school alumni. Using structural equation modeling to test the unequal attributes framework, we found that work hours, career orientation, having a nonemployed spouse, and working in a predominantly female job were unequal attributes that explained gender differences in career success. Using multigroup path analysis to examine unequal effects, we found that being agentic, married, having children at home, and working in a predominantly female workplace had unequal effects in relation to career success for men and women. We find support for both models across three categories of career success antecedents (i.e., personal, family, and job attributes).     

Using the bootstrap with two-phase adaptive stratified samples from multiple populations at multiple locations

Recently the two-phase adaptive stratified sampling design proposed by Francis (1984) has been extended by Manly et al. (2002) for situations where several biological populations are sampled simultaneously, and where this is done at several different geographical locations in order to estimate population totals or means. The method uses the results from a first phase sample to decide how best to allocate a second phase sample to locations and strata, in order to maximise a criterion (based on estimated coefficients of variation) that measures the accuracy of estimation for population totals, for all variables at all locations. One potential problem with this method is bias in the estimators of the population totals and means. In this paper bootstrapping is considered as a means of overcoming these biases. It is shown using model populations of Pacific walrus and shellfish, based on real data, that bootstrapping is a useful tool for removing about half of the bias. This is also confirmed from some simulations using artificial data.     

Resampling methods for estimating dispersion indices in random and adaptive designs

In many surveys in environmental and natural phenomena the aim is to evaluate the heterogeneity, and the skewness of the distribution of the number point-objects in the study area opportunely partitioned in sub-regions. For this purpose, in this paper the estimation of dispersion indices is considered by using simple random sampling and adaptive sampling with initial simple random sampling selected with replacement or without replacement. The jackknife and the bootstrap procedures are proposed in both cases for reducing bias. Finally, both a simulation study and a case study on biological population referred to a Oidium tuckeri contamination in a growing vineyard is performed to assess the accuracy of the proposed estimators.     

Use of heterospecific cues by the lizard Platysaurus broadleyi for food location

Flat lizards (Platysaurus broadleyi) at Augrabies Falls National Park, South Africa, are restricted to rocky terrain where the predominant tree is the Namaqua fig (Ficus cordata cordata). P. broadleyi readily feeds on Namaqua figs when they are available, and the lizards sometimes form large (maximum recorded=134) congregations under fruiting fig trees. The distance lizards travel to fruiting trees also exceed normal daily foraging distances. Location of fruiting fig trees by a lizard can have a high pay-off because figs are energetically rich and trees fruit irregularly and asynchronously, resulting in a resource that is available, but unpredictable in time and space. The prediction that bird activity in fig trees provides a cue to the presence of ripe figs was tested experimentally. By placing cages containing birds and empty control cages in trees devoid of fruit, we demonstrated that P. broadleyi are drawn to fig trees with high bird congregations. We also tested if the presence of a fig tree was necessary to draw lizards to bird congregations by placing cages containing birds and empty control cages in a matched-pairs design on rock away from trees. Namaqua fig trees were not necessary to draw lizards to bird congregations. Received: 12 May 1998 / Accepted after revision: 30 November 1998     

Does the African social spider Stegodyphus dumicola control the sex of individual offspring?

By scoring the chromosome number of developing embryos, we show that the sex ratio bias of the African social spider Stegodyphus dumicola Pocock is the result of an overproduction of female embryos. Only 17% of 585 embryos sexed from 14 egg sacs were male, a significant departure from a 1:1 sex ratio. We also explored the possibility of direct control of the sex of individual offspring in this species by examining the variance in the number of males per sac and the spatial distribution of male and female embryos within the sacs. We postulated that a variance in the number of males per sac lower than binomial (i.e., underdispersed or precise sex ratios) or a non-random distribution of male embryos within the sacs would suggest direct control of the sex of individual offspring. We found that the variance in the number of males per sac was indistinguishable from binomial and significantly larger than expected under exact ratios. Likewise, the spatial distribution of male embryos within three sacs examined was no more clustered than expected by chance. The sex ratio biasing mechanism in this species, therefore, apparently only allows control of the mean sex ratio but not of its variance. We present randomization and Monte Carlo methods that can be applied to test for departures from a random spatial arrangement of male and female embryos in an egg mass and for departures from binomial or exact ratios when not all members of a clutch have been sexed. Received: 21 October 1998 / Received in revised form: 23 March 1999 / Accepted: 26 April 1999     

Effects of site-selection bias on estimates of biodiversity change

Estimates of biodiversity change are essential for the management and conservation of ecosystems. Accurate estimates rely on selecting representative sites, but monitoring often focuses on sites of special interest. How such site-selection biases influence estimates of biodiversity change is largely unknown. Site-selection bias potentially occurs across four major sources of biodiversity data, decreasing in likelihood from citizen science, museums, national park monitoring, and academic research. We defined site-selection bias as a preference for sites that are either densely populated (i.e., abundance bias) or species rich (i.e., richness bias). We simulated biodiversity change in a virtual landscape and tracked the observed biodiversity at a sampled site. The site was selected either randomly or with a site-selection bias. We used a simple spatially resolved, individual-based model to predict the movement or dispersal of individuals in and out of the chosen sampling site. Site-selection bias exaggerated estimates of biodiversity loss in sites selected with a bias by on average 300–400% compared with randomly selected sites. Based on our simulations, site-selection bias resulted in positive trends being estimated as negative trends: richness increase was estimated as 0.1 in randomly selected sites, whereas sites selected with a bias showed a richness change of −0.1 to −0.2 on average. Thus, site-selection bias may falsely indicate decreases in biodiversity. We varied sampling design and characteristics of the species and found that site-selection biases were strongest in short time series, for small grains, organisms with low dispersal ability, large regional species pools, and strong spatial aggregation. Based on these findings, to minimize site-selection bias, we recommend use of systematic site-selection schemes; maximizing sampling area; calculating biodiversity measures cumulatively across plots; and use of biodiversity measures that are less sensitive to rare species, such as the effective number of species. Awareness of the potential impact of site-selection bias is needed for biodiversity monitoring, the design of new studies on biodiversity change, and the interpretation of existing data.     

Eliciting expert knowledge in conservation science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.     

环境DNA(eDNA)宏条形码技术对枝角类浮游动物物种鉴定及其生物量监测研究

环境DNA(eDNA)宏条形码(Metabarcoding)技术越来越多地被应用于环境中物种定性识别,但如何定量监测物种在环境中的丰度尚未得到解决。本研究以太湖流域常见的5种浮游动物拟同形溞、大型溞、蚤状溞、多刺裸腹溞、老年低额溞为研究对象,建立了一种基于eDNA宏条形码技术的物种定量方法,并与实时荧光定量PCR(qPCR)相比较,研究了eDNA宏条形码技术多物种定量的准确性。结果表明,PCR引物对eDNA宏条形码的物种检测和定量影响显著。313 bp COI313引物对浮游动物物种覆盖度高,但是物种间DNA扩增的偏好性大,不适用于eDNA宏条形码定量检测。基于COI序列重新设计的短COI116引物能够同时检测出所有5个物种。荧光定量PCR(qPCR)物种拷贝数与物种相对占比呈正相关。eDNA宏条形码所检出每个物种的序列数与qPCR定量拷贝数高度一致。综上,eDNA宏条形码技术可实现对浮游动物物种的半定量检测,在生物多样性监测和生物完整性评价有显著的应用价值。