Decision support tools that predict fish distribution over broad spatial scales are needed to assist in planning watershed management and endangered species recovery. We developed a geographical information system model with multivariate logistic regression to rank valley segments for probable occurrence of the endangered Topeka shiner (Notropis topeka) using stream condition variables (stream size, groundwater potential, channel slope, streamflow, network position) and land-cover variables (percent pasture, percent trees) in streams characteristic of the North American Great Plains. The stream condition and land-cover models correctly classified 89% and 68% of outcomes (i.e., presence or absence), respectively. Field tests of maps of predicted species distribution resulted in more species occurrences than expected in valley segments classified as high potential for presence and less than expected in low-potential valley segments. Gaps between high-priority segments and protected land parcels were found in all basins. In 37 basins with Topeka shiners, protected land coverage was <1% in 17 basins, 1-5% in 10 basins, and 5-21.8% in 10 basins. Conservation activities in gaps are long-term conservation measures, but maps of predicted species distribution have many immediate applications.Résumé : La planification de la gestion des bassins versants et du rétablissement des espèces menacées requiert la mise au point d'outils d'aide à la décision afin de prédire la répartition des poissons sur de grandes échelles spatiales. Nous avons conçu un modèle basé sur le système d'information géographique et la régression logistique multidimensionnelle pour coder des sections de vallées quant la probabilité de la présence du méné de Topeka (Notropis topeka), une espèce menacée, à partir de variables des conditions hydrographiques (taille du cours d'eau, apport potentiel d'eau phréatique, pente du chenal, débit, position dans le réseau) et du couvert végétal (pourcentage de pâturages, pourcentage d'arbres) dans des cours d'eau typiques de la région des grandes plaines de l'Amérique du Nord. Les modèles basés sur les conditions hydrographiques et le couvert végétal prédisent correctement les répartitions (i.e., présence ou absence) dans respectivement 89 % et 68 % des cas. La vérification sur le terrain des cartes de la répartition prédite de l'espèce indique plus de présences que prévu dans les sections classifiées comme possédant un bon potentiel de pré-sence et moins que prévu dans les sections à faible potentiel. Il existe dans tous les bassins des zones de discontinuité entre les sections de cours d'eau de priorité élevée et les parcelles de terres protégées. Dans 37 bassins qui abritent le méné de Topeka, la surface couverte par les terres protégées représente <1 % dans 17 bassins, 1-5 % dans dix bassins et 5-21,8 % dans dix bassins. Les activités de conservation dans les zones de discontinuité sont des mesures à long terme; néanmoins, les cartes de prédiction de la répartition des espèces possèdent de multiples usages immédi...

We summarized historic and recent fish distributions in South Dakota and analyzed fish faunal similarity at 2 spatial scales (geomorphic province and river drainage) for both historic (native) and recent (post-1990) faunas. We quantified zoogeographic patterns between geomorphic provinces and among neighboring river drainages for historic and recent faunas. We also quantified faunal change (species losses and additions) between provinces and among drainages. Ninety-seven fishes were native to South Dakota, but 111 fishes were present in recent collections because 8 native species were missing, and 22 nonnatives were present. There was high β diversity among historic and recent river drainage fish faunas, but there was between 22% and 56% faunal change between periods. Recent faunas were homogenized compared to historic faunas at both provincial and river drainage spatial scales. Patterns of nonnative species establishment were geographically distinct from patterns of native species loss. Most nonnative species additions were in cold-water or human-made habitats of the Great Plains. Most native species declines stemmed from warm water streams of the Central Lowlands and Missouri River valley. Conservation of rare and declining native species and containment of nonnatives are both necessary to preserve historical patterns of fish biodiversity in South Dakota.

Predictive fish distribution models have utility in planning conservation measures for rare fish species. However, species rarity creates sampling and modeling difficulties that require an understanding of model accuracy. We evaluated existing distribution models for 10 rare fishes based on 2,026 community fish samples and associated riverine habitat. Our fieldwork provided an independent fish species inventory for 143 sample sites. This inventory was used to quantify species detectability for use as a weighting factor with which to correct false-negative modeling errors. Presence/absence data were compared with predictions to evaluate model accuracy as determined by Cohen's kappa and correct classification rates. Detection probabilities were generally small but ranged from 0 to 0.68. The models predicted species occurrence with relatively high success (average kappa ¼ 45.6% and average correct classification rate ¼ 74.1%). The habitat variables for predicting species occurrence varied among species; however, stream size and streamflow were the most influential. All distribution models had adequate predictive abilities and improved our understanding of fish distributions and the factors determining those distributions. Model accuracy statistics can provide managers with a measure of confidence when they are directing conservation activities. a Species with one asterisk are listed as threatened in South Dakota, species with two asterisks as endangered (SDGFP 2007). 1262HAYER ET AL.

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Texture and small-scale surface details are widely recognised as playing an important role in the haptic identification of objects. In order to simulate realistic textures in haptic virtual environments, it has become increasingly necessary to identify a robust technique for modelling of surface profiles. This paper describes a method whereby Fourier series spectral analysis is employed in order to describe the measured surface profiles of several characteristic surfaces. The results presented suggest that a bandlimited Fourier series can be used to provide a realistic approximation to surface amplitude profiles.