Can trail spatial attributes predict trail use level in urban forest park? An examination integrating GPS data and space syntax theory

Understanding users’ spatial distribution in forest park is crucial for providing visitors with quality recreation experiences and for park planning and management. Utilizing users’ spatial distribution data, this study aims at investigating associations between trail use level and trail spatial attributes, through examining two large urban forest parks (Gongqing forest park and Paotaiwan forest park) in Shanghai, China. Users’ spatial distribution was measured utilizing GPS trackers with the interval of 10 seconds. This study conceptualizes trail spatial attributes as trail metric attributes and trail configurational attributes. Trail metric attributes include trail mean distance to gates, length, width and level of enclosure, which are calculated based on park map and on-site observation. We computed trail configurational attributes utilizing space syntax theory, which comprise measures of global integration, control, and connectivity. Trail connection with features/facilities, visual connection with water and shading are included as covariate variables. In total, we obtained 134 valid samples in Gongqing forest park and 210 valid samples in Paotaiwan forest park for analysis. Multivariate regression analyses indicate that when involving covariate variables, consistently in both parks, a greater trail usage is significantly related to trail shorter mean distance to park gate, trail width wider than 3 meters, higher global integration and higher control values. Collectively, these four trail spatial attributes explained 31.7 % (p < 0.001) and 27.3 % (p < 0.001) of the variances in trail use level in Gongqing forest park and Paotaiwan forest park. These findings provide direct implications to park designers and managers for providing visitors with different desirable social conditions, and ultimately improve users’ experiences and satisfactions.     

A context for recruitment correlations: why marine fisheries biologists should still look for them

In many cases when ecologists want to investigate a process, they often look for the best system on which to conduct the research, "best" meaning that the possibility of discovering mechanisms is optimized or made easier in some way. In fisheries we do it backwards. The species and system are given to us by economics, and we then fly in the face of the difficult circumstances to find mechanisms that are elusive anyway. These difficult circumstances constitute in some sense the first set of statistical problems. Using examples from the Northeast Pacific, I review the characteristics of cohort time series that make some species more tractable; propose a conscious process of conceptualization to assist in the formulation of clear, germane hypotheses; highlight the contrast between modeling in the sense of statistical fitting versus simulation models of processes; explore how the first round of models integrates with the second round of planning for new data collection at sea and in the lab; and, finally, propose how to judge success in terms of an operational approach.     

Evaluation of two N cycle models for the prediction of N mineralization from grassland soils in the UK

Abstract. The ability of two nitrogen cycle models, of contrasting complexity, to predict N mineralization from a range of grassland soils in the UK, was evaluated. These were NCYCLE, a simple mass balance model of the N cycle in UK grasslands, and CENTURY, a more complex model simulating long-term C, N, P & S dynamics in grassland ecosystems. The models were tested using field measurements of net N mineralization from a range of grassland soils (differing in soil type, history & management practice), obtained over a 2 year period using a soil core incubation technique. This method was considered to measure the total net release of mineral N from the soil organic matter over a specified time, including N which may have been recycled several times. NCYCLE consistently under-estimated mineralization rates at all sites. By contrast, there was some correlation between CENTURY predictions of net N mineralization and field measurements. This may have reflected the different abilities of the two models to simulate N recycling. Neither model, however, was able to predict adequately the effect of cultivation and reseeding on net N mineralization.     

DYNAMIC MODELS OF AQUIFEROUS CONTENT OF LIVING FUELS

RESEARCHSITELivingfue1splayedanimportantroleinheatconcentrationactionorinheatsourceofforestfire.Whenitshumiditydecreasestoacertainlevel,theybecameaheatsourcewhenthelivingcombustibl-eswerecombinedwithfire.Thus,itwasessentialhowtodeterminethemoisturesituationandthefOrestfiredangerdegreetobeforecastedaccurately.Thedynamicmodelspresentedinthispaperwereusefultosolvethisproblem.Everyyear,-therewerealotofforestfires,especiallythefireoccurrenceinDaxinganMountains,inthespringofl987.Itwasveryimpo…     

刺槐单株生物量动态研究

本文依据420株刺槐生物量及23株树干解析资料,应用灰色Verhulst模型,对太行山坡地刺槐林单株干、枝、叶、根生物量动态进行了研究,分别建立了预测模型,预测了各器官生长的速生期和停止生长林龄,为实现刺槐林的多目标经营提供决策依据。     

Spatial epidemiology of the Asian honey bee mite (Varroa destructor) in the North Island of New Zealand

We describe the spatial epidemiology of Varroa destructor infestation among honey bee apiaries in the greater Auckland area of the North Island of New Zealand. The study population was comprised of 641 apiaries located within the boundaries of the study area on 11 April 2000. Cases were those members of the study population declared Varroa-infested on the basis of testing conducted between April and June 2000. The odds of Varroa was highest in apiaries in the area surrounding transport and storage facilities in the vicinity of Auckland International Airport. A mixed-effects geostatistical model, accounting for spatial extra-binomial variation in Varroa prevalence, showed a 17% reduction in the odds of an apiary being Varroa infested for each kilometre increase in the squared distance from the likely site of incursion (95% Bayesian credible interval 7–28%). The pattern of spatially autocorrelated risk that remained after controlling for the effect of distance from the likely incursion site identified areas thought to be ‘secondary’ foci of Varroa infestation initiated by beekeeper-assisted movement of infested bees. Targeted investigations within these identified areas indicated that the maximum rate of local spread of Varroa was in the order of 12 km/year (interquartile range 10–15 km/year).     

The influence of sampling scheme and interpolation method on the power to detect spatial effects of forest birds in Ontario (Canada)

Spatial ecology is becoming an increasingly important component of resource management, and the general monitoring of how human activities affect the distribution and abundance of wildlife. Yet most work on the reliability of sampling strategies is based on a non-spatial analysis of variance paradigm, and little work has been done assessing the power of alternative spatial methods for creating reliable maps of animal abundance. Such a map forms a critical response variable for multiple scale studies relating landscape structure to biotic function. The power to reconstruct patterns of distribution and abundance is influenced by sample placement strategy and density, the nature of spatial auto-correlation among points, and by the technique used to extrapolate points into an animal abundance map. Faced with uncertainty concerning the influence of these factors, we chose to first synthesize a model reference system of known properties and then evaluate the relative performance of alternative sampling and mapping procedures using it. We used published habitat associations of tree nesting boreal neo-tropical birds, a classified habitat map from the Manitou Lakes area of northwestern Ontario, and point count means and variances determined from field studies in boreal Canada to create 4 simulated models of avian abundance to function as reference maps. Four point sampling strategies were evaluated by 4 spatial mapping methods. We found mixed-cluster sampling to be an effective point sampling strategy, particularly when high habitat fragmentation was avoided by restricting samples to habitat patches >10 ha in size. We also found that of the 4 mapping methods, only stratified ordinary point kriging (OPK) was able to generate maps that reproduced an embedded landscape-scale spatial effect that reduced nesting bird abundance in areas of higher forest age-class fragmentation. Global OPK was effective only for detecting broader, regional-scale differences. This revised version was published online in July 2006 with corrections to the Cover Date.     

Predicting the spatial distribution of ground flora on large domains using a hierarchical Bayesian model

Accomodation of important sources of uncertainty in ecological models is essential to realistically predicting ecological processes. The purpose of this project is to develop a robust methodology for modeling natural processes on a landscape while accounting for the variability in a process by utilizing environmental and spatial random effects. A hierarchical Bayesian framework has allowed the simultaneous integration of these effects. This framework naturally assumes variables to be random and the posterior distribution of the model provides probabilistic information about the process. Two species in the genus Desmodium were used as examples to illustrate the utility of the model in Southeast Missouri, USA. In addition, two validation techniques were applied to evaluate the qualitative and quantitative characteristics of the predictions.This revised version was published online in May 2005 with corrections to the Cover Date.     

A leakiness index for assessing landscape function using remote sensing

The cover, number, size, shape, spatial arrangement and orientation of vegetation patches are attributes that have been used to indicate how well landscapes function to retain, not ‘leak’, vital system resources such as rainwater and soil. We derived and tested a directional leakiness index (DLI) for this resource retention function. We used simulated landscape maps where resource flows over map surfaces were directional and where landscape patch attributes were known. Although DLI was most strongly related to patch cover, it also logically related to patch number, size, shape, arrangement and orientation. If the direction of resource flow is multi-directional, a variant of DLI, the multi-directional leakiness index (MDLI) can be used. The utility of DLI and MDLI was demonstrated by applying these indices to three Australian savanna landscapes differing in their remotely sensed vegetation patch attributes. These leakiness indices clearly positioned these three landscapes along a function-dysfunction continuum, where dysfunctional landscapes are leaky (poorly retain resources). This revised version was published online in July 2006 with corrections to the Cover Date.     

Landscape patterns as habitat predictors: building and testing models for cavity-nesting birds in the Uinta Mountains of Utah,USA

The ability to predict species occurrences quickly is often crucial for managers and conservation biologists with limited time and funds. We used measured associations with landscape patterns to build accurate predictive habitat models that were quickly and easily applied (i.e., required no additional data collection in the field to make predictions). We used classification trees (a nonparametric alternative to discriminant function analysis, logistic regression, and other generalized linear models) to model nesting habitat of red-naped sapsuckers (Sphyrapicus nuchalis), northern flickers (Colaptes auratus),tree swallows (Tachycineta bicolor), and mountain chickadees (Parus gambeli) in the Uinta Mountains of northeastern Utah, USA. We then tested the predictive capability of the models with independent data collected in the field the following year. The models built for the northern flicker, red-naped sapsucker, and tree swallow were relatively accurate (84%, 80%, and 75% nests correctly classified,respectively)compared to the models for the mountain chickadee (50% nests correctly classified). All four models were more selective than a null model that predicted habitat based solely on a gross association with aspen forests. We conclude that associations with landscape patterns can be used to build relatively accurate, easy to use, predictive models for some species. Our results stress, however, that both selecting the proper scale at which to assess landscape associations and empirically testing the models derived from those associations are crucial for building useful predictive models. This revised version was published online in July 2006 with corrections to the Cover Date.