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- 1. To conserve biodiversity in a human‐dominated landscape, a science‐based inventory and monitoring plan is needed that quantifies existing resources, isolates drivers that maintain natural communities, determines harmful stressors, and links ecological drivers and human stressors. A tactical approach is proposed for conservation planning using freshwater fish at the Cape Cod National Seashore.
- 2. Freshwater fish are well studied and occur across environmental gradients. The lentic systems at the national park are relatively pristine yet are enveloped by a region of high population density. Using fish community data, three steps were taken for tracking anthropogenic impacts in a human dominated landscape. First, fish and potential drivers were sampled intensively along a gradient to determine which fish metrics reflect natural communities and which abiotic and biotic factors structure them. Second, emerging and existing regional human threats were identified. Third, these human threats were linked to the potential drivers that maintain natural communities to identify the most informative metrics to monitor and track change.
- 3. Fish communities, water quality, habitat, and food resources were sampled concurrently in 18 ponds in 1999 and 2000. Three common fish species explained 98% of variation in numbers across systems. Based on ecological relationships, pH, depth, vegetation, prey, and community complexity were determined to maintain biodiversity of freshwater fish communities.
- 4. The primary human threats here included: development‐related, land‐use changes; non‐point source pollution; eutrophication from septic systems; and introduced species that are a byproduct of high human visitation. These are common threats in many rapidly urbanized areas and are likely to have relevance to many sites.
- 5. To track the impact of emerging threats to freshwater ponds related to increased human population, monitoring changes in water quality, vegetated habitat, fish diversity, and trophic interactions are recommended.
A project aiming to develop sorting and counting technologies for ornamental fish growers included development and testing of image-processing algorithms for sorting guppy fish (Poecilia reticulata) by gender. The algorithms are derived from shape and color differences between female and male guppies. An algorithm for the determination of landmarks on fish contours was developed and found to be accurate in accordance with human judgment, enabling extraction of specific shape and color features of the tail and the body.
The algorithms were applied to three sets of images of guppies of the “Red-Blond” strain. Gender identification accuracy was approximately 90% using shape features, approximately 96% using color features and was slightly improved when both color and shape features were used.
Some of the components used are essential for future development of a computer vision based system for sorting and grading ornamental fish by strain and quality. 相似文献