Landlocked sockeye salmon (Oncorhynchus nerka), ranging in fork length (FL) from 105 to 313 mm, were captured in fine‐mesh gill nets set in the limnetic zone of the Waitaki hydro lakes (44° 30′ S, 170° 10’ E) in the South Island, New Zealand. A total of 443 stomachs was examined and the frequency of occurrence, volume and weight of prey items calculated. In the Ahuriri Arm of Lake Benmore the principal food (54% by weight) was zooplankton (Boeckella dilatata) whereas in the Haldon Arm of Lake Benmore it was larval and juvenile common bullies (Gobiomorphus cotidi‐anus) (73% by volume). In Lake Waitaki in winter, salmon had eaten insects (43% by volume) with smaller amounts of snails (Potamopyrgus antipo‐darum, 23%) and bullies (24%). In Lake Ohau adult insects may be an important food. There were also variations in diet with season and fish size. The stomachs of 147 brown trout (Salmo trutta) and 181 rainbow trout (S. gairdnerii) caught in the same gill nets were also examined. In contrast to sockeye salmon stomachs they contained negligible amounts of zooplankton (< 1% by weight) and large amounts of aquatic insects (50–58% by weight in the Ahuriri Arm of Lake Benmore). Comparisons with juvenile sockeye salmon and kokanee in North American lakes are made. The impact of introductions of sockeye salmon into other New Zealand lakes is discussed. 相似文献
Social Network Analysis offers powerful tools to analyze the structure of relationships between a set of people. However, the addition of spatial information poses new challenges, as nodes are embedded simultaneously in network space and Euclidean space. While nearby nodes may not form social ties, ties may exist at a distance, a configuration ill-suited for traditional spatial metrics that assume adjacent objects are related. As such, there are relatively few metrics to describe these nuanced situations. We advance the burgeoning field of spatial social network analysis by introducing a set of new metrics. Specifically, we introduce the spatial social network schema, tuning parameter and the flattening ratio, each of which leverages the notion of ‘distance’ to augment insights obtained by relying on topology alone. These methods are used to answer the questions: What is the social and spatial structure of the network? Who are the key individuals at different spatial scales? We use two synthetic networks with properties mimicking the ones reported in the literature as validation datasets and a case study of employer–employee network. The methods characterize the employer–employee as spatially loose with predominantly local connections and identify key individuals responsible for keeping the network connected at different spatial scales. 相似文献
Today, online social media outlets provide new and plentiful sources of data on social networks (SNs) and location-based social networks (LBSNs), i.e., geolocated evidence of connections between individuals. While SNs have been used to show how the magnitude of social connectivity decreases with distance, there are few examples of how to include SNs as layers in a GISystem. If SNs, and thus, interpersonal relationships, could be analyzed in a geographic information system (GIS) setting, we could better model how humans socialize, share information, and form social groups within the complex geographic landscape.
Our goal is to facilitate a guide for analyzing SNs (as derived from online social media, telecommunications, surveys, etc.) within geographic space by combining the mature fields of social network analysis (SNA) and GISystems. First, we describe why modeling socialization in geographic space is essential for understanding human behavior. We then outline best practices and techniques for embedding SN nodes and edges in GISystems by introducing terms like ‘social flow’ and ‘anthrospace’, and categorizations for data and spatial aggregation types. Finally, we explore case study vignettes of SNA within GISystems from diverse regions located in Bolivia, China, Côte d’Ivoire, Singapore, the United Kingdom, and the United States, using concepts such as geolocated dyads, ego–alter relationships, node feature roles, modularity, and network transitivity. 相似文献
A function having some properties of a wavelet and being harmonic around a given point in R3 is defined, and three models showing the local relationships between the disturbing density, the disturbing potential and
the disturbing gravity are established by using the function as the kernel function of the integrals in the models. The local
relationship has two meanings. One is that we can evaluate with a high accuracy the integrals in the models by using mainly
high-accuracy and high-resolution data in a local area. The other is that we can obtain a stable solution with high resolution
when we invert the integrals in the models because of the rapid decrease of the kernel function of the integrals. As a result,
with these models we evaluate one quantity with high resolution, in a band limited by the maximum degree of a set of geopotential
coefficients or by the resolution (spacing) of the local data, from another quantity (or quantities) in a local area, and
the resulting solution is stable.
Received: 6 April 1998 / Accepted: 16 June 1999 相似文献
This paper attempts to open up discussion about interconnectionsbetween psychotherapeutic practice and human geography. I offer brief “here and now” observations to introduce the importance of personal experience and interpersonal relationships. I then construct an autobiographical narrative to elaborate the themes of separation and connection. This frames my preliminary explorations of tensions and convergences between ideas flowing from psychotherapeutic practice and human geography. I conclude by stressing limits to knowledge. 相似文献