Encounter Rates From Road-Based Surveys of Rio Grande Wild Turkeys in Texas

ABSTRACT Traditional index-based techniques have indicated declines in Rio Grande wild turkey (Meleagris gallopavo intermedia; hereafter, wild turkey) populations across much of Texas, USA. However, population indices can be unreliable. Research has indicated that road-based surveys may be an efficacious technique for monitoring wild turkey populations on an ecoregion level. Therefore, our goal was to evaluate applicability of road-based distance sampling in the Cross Timbers, Edwards Plateau, Rolling Plains, and South Texas ecoregions of Texas. We conducted road-based surveys in each ecoregion during December 2007—March 2008 to estimate wild turkey flock encounter rates and to determine survey effort (i.e., km of roads) required to obtain adequate sample sizes for distance sampling in each ecoregion. With simulations using inflatable turkey decoys, we also evaluated effects of distance to a flock, flock size, and vegetative cover on turkey flock detectability. Encounter rates of wild turkey flocks from road-based surveys varied from 0.1 (95% CI = 0.0–0.6) to 2.2 (95% CI = 0.8–6.0) flocks/100 km surveyed. Encounter rates from surveys restricted to riparian communities (i.e., areas ≤1 km from a river or stream) varied from 0.2 (95% CI = 0.1–0.6) to 2.9 (95% CI = 1.5–6.7) flocks/100 km surveyed. Flock detection probabilities from field simulations ranged from 22.5% (95% CI = 16.3–29.8%) to 25.0% (95% CI = 13.6–39.6%). Flock detection probabilities were lower than expected in all 4 ecoregions, which resulted in low encounter rates. Estimated survey effort required to obtain adequate sample sizes for distance sampling ranged from 2,765 km (95% CI = 2,597–2,956 km) in the Edwards Plateau to 37,153 km (95% CI = 12,861–107,329 km) in South Texas. When we restricted road-based surveys to riparian communities, estimated survey effort ranged from 2,222 km (95% CI = 2,092–2,370 km) in the Edwards Plateau to 22,222 km (95% CI = 19,782–25,349 km) in South Texas.     

“城-郊-乡”森林生态样带植被变化梯度分析

沿纽约市“市区－郊区－农区”１４０ｋｍ森林生态样带,对９个样地１９个样方的森林植被进行了研究。植被组成和结构沿样带变化明显,分异出城区森林、郊区森林和农区森林等不同类型,优势种替代明显,植物种类也形成了不同的生态类型。植被的梯度变化与人类活动密切相关,城市化对植被有重要影响。森林生态样带是研究人类活动对植被影响的好手段。     

鼎湖山植物群落α多样性与环境的关系

用样带取样法,来研究不同取样尺度和不同取样尺度条件下的多个环境因子与鼎湖山植物群落α多样性的关系.取样尺度分别为10、20、40、80m和160m.涵盖鼎湖山主要的植被类型：季风常绿阔叶林、针阔混交林、沟谷常绿阔叶林和针叶林.相关分析和主成分分析结果表明,环境因子对各层次的α多样性的影响程度各不相同,达到显著相关性的取样尺度也不一样,表现出较大的复杂性,同时也表明样带上的环境异质性较高.因此,用海拔梯度作为主要的环境梯度来研究鼎湖山植物群落多样性具有合理性.海拔高度与乔木层多样性的关系在所有取样尺度上都较密切,这说明海拔高度可能是影响乔木层α多样性的最重要环境因子.     

Long-term research sites as refugia for threatened and over-harvested species

The presence of researchers, ecotourists or rangers inside protected areas is generally assumed to provide a protective effect for wildlife populations, mainly by reducing poaching pressure. However, this assumption has rarely been empirically tested. Here, we evaluate and quantify the conservation benefits of the presence of a long-term research area in Taï National Park, Côte d''Ivoire. A wildlife survey following 225 km of line transects revealed considerably higher primate and duiker encounter rates within the research area when compared with adjacent areas. This positive effect was particularly pronounced for threatened and over-harvested species, such as the endangered red colobus monkey (Procolobus badius). This pattern was clearly mirrored by a reversed gradient in signs of poaching, which decreased towards and inside the research area, a trend that was also supported with park-wide data. This study demonstrates that even relatively simple evidence-based analytical approaches can bridge the gap between conservation theory and practice. In addition, it emphasizes the value of establishing long-term research sites as an integral part of protected area management.     

中国东部陆地农业生态系统南北样带的自然概况

介绍了中国东部陆地农业生态系统南北样带的自然情况,包括地理范围、地貌、气候、土壤、植被资源等。通过对东部样带内气候与植被相关分析发现,降水量与温度是影响东部样带内植被分布的重要因素。     

Predicting and correcting bias caused by measurement error in line transect sampling using multiplicative error models

Line transect sampling is one of the most widely used methods for animal abundance assessment. Standard estimation methods assume certain detection on the transect, no animal movement, and no measurement errors. Failure of the assumptions can cause substantial bias. In this work, the effect of error measurement on line transect estimators is investigated. Based on considerations of the process generating the errors, a multiplicative error model is presented and a simple way of correcting estimates based on knowledge of the error distribution is proposed. Using beta models for the error distribution, the effect of errors and of the proposed correction is assessed by simulation. Adequate confidence intervals for the corrected estimates are obtained using a bootstrap variance estimate for the correction and the delta method. As noted by Chen (1998, Biometrics 54, 899-908), even unbiased estimators of the distances might lead to biased density estimators, depending on the actual error distribution. In contrast with the findings of Chen, who used an additive model, unbiased estimation of distances, given a multiplicative model, lead to overestimation of density. Some error distributions result in observed distance distributions that make efficient estimation impossible, by removing the shoulder present in the original detection function. This indicates the need to improve field methods to reduce measurement error. An application of the new methods to a real data set is presented.     

Estimating elephant densities from wells and droppings in dried out riverbeds

In this paper, we present a new method for estimating elephant densities by counting elephant wells and dung boli within dry seasonal flooding rivers. A combination of aerial and ground counts of elephant wells and dung boli in the Ewaso Ngiro River were related to elephant numbers, obtained from an on‐going monitoring program of individually identified elephants in Samburu and Buffalo Spring National Reserves, Kenya. The total number of elephant observations was highly correlated with both densities of wells and dung boli at a spatial resolution of 4‐km river‐section. This indicates that both wells and droppings can be used for estimating relative densities at such spatial resolution. The method can be used as a quick and reliable way of estimating relative elephant densities in semiarid regions but is sensitive to differences in the time when different parts of the river dry out and will be unreliable in areas with secondary un‐censused water sources. A short 4‐week period between the river dry out and the count is recommended, because of an error induced by a level of well reuse and the difficulties in counting areas of high well densities from the air.     

How to monitor elusive lizards: comparison of capture–recapture methods on giant day geckos (Gekkonidae, Phelsuma madagascariensis grandis) in the Masoala rainforest exhibit, Zurich Zoo

Rapid and reliable estimation of population size is needed for the efficient monitoring of animal populations of conservation concern. Unfortunately, technical advances in this area have not been paralleled in uptake in conservation, which may be due to difficulties in implementation or the lack of general guidelines for application. Here we tested five different methods used to estimate population size [capture–mark–recapture (CMR), finite-mixture models, model averaging of finite-mixture models, accumulation curve methods (ACM), and the line transect method (LT)] using extensive capture–recapture data of the giant day gecko (Gekkonidae, Phelsuma madagascariensis grandis, Gray 1870) at the Masoala rainforest exhibit, Zurich Zoo. When the complete data were analyzed [30 sessions (and 27 sessions for the LT)], all methods except the LT produced similar estimates of population size. The simple ACM gave a small coefficient of variation (CV), but did not cover the most likely value of population size at moderate sampling effort. Nevertheless, the ACM was the only method that showed a reasonable convergence when subsets of data were used. CMR and Pledger models included the reference value in their confidence intervals (CI) after 25 and 30 sessions, respectively. Although model averaging did slightly improve the estimate, the CV was still high for the full dataset. Our method of using subsets of data to test the robustness of estimates is simple to apply and could be adopted more widely in such analyzes to evaluate sensitivity to method of evaluation. In conclusion, simple accumulation methods showed similar efficiency to more complex statistical models, and are likely to be sufficiently precise for most conservation monitoring purposes. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

基于样带的唐古特白刺灌丛沙包空间格局尺度研究

黄河河岸与库布齐沙漠之间生态过渡带上的唐古特白刺(Nitraria Tangutorum)灌丛沙包由于遭受到不同程度的破坏而表现出一定程度的退化,空间格局尺度从一定程度上表征了其破碎化程度。我们分别应用样方方差法,小波分析,分维,谱分析以及空隙度分析等方法对鄂尔多斯高原北缘唐古特白刺灌丛沙包的空间格局尺度进行了比较研究,旨在选出适合分析干旱半干旱区白刺灌丛沙包空间格局尺度的方法,并确定研究区内唐古特白刺灌丛沙包的空间格局尺度,为保护唐古特白刺灌丛沙包提供科学依据。结果表明:(1)TTLQV法得到的格局尺度过大,而小波分析得到的格局尺度过小,分维分析得到的格局尺度除了相对较小之外,趋势也不明显,因此都不适合分析干旱半干旱区白刺灌丛沙包的空间格局尺度;(2)而3TLQV,tQV,谱分析和空隙度分析所得到的结果则相对容易接受,其大小顺序是:3TLQV>tQV>空隙度分析>谱分析;(3)独贵塔拉、呼和木独和巴拉贡唐古特白刺灌丛沙包的空间格局尺度分别为16.7～27.1m,10.2～25.0m和8.8～17.0m,这一结果将有助于在今后的研究中合理地确定研究范围和尺度。