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Dana M. Infante

Publications and source records attributed to Dana M. Infante.

24 records · Page 2Linked to original sources

Applications of genetic data to improve management and conservation of river fishes and their habitats

Environmental variation and landscape features affect ecological processes in fluvial systems; however, assessing effects at management-relevant temporal and spatial scales is challenging. Genetic data can be used with landscape models and traditional ecological assessment data to identify biodiversity hotspots, predict ecosystem responses to anthropogenic effects, and detect impairments to underlying processes. We show that by combining taxonomic, demographic, and genetic data of species in complex riverscapes, managers can better understand the spatial and temporal scales over which environmental processes and disturbance influence biodiversity. We describe how population genetic models using empirical or simulated genetic data quantify effects of environmental processes affecting species diversity and distribution. Our summary shows that aquatic assessment initiatives that use standardized data sets to direct management actions can benefit from integration of genetic data to improve the predictability of disturbance–response relationships of river fishes and their habitats over a broad range of spatial and temporal scales.

Fisheries↗

Development and assessment of indices to determine stream fish vulnerability to climate change and habitat alteration

Understanding the future impacts of climate and land use change are critical for long-term biodiversity conservation. We developed and compared two indices to assess the vulnerability of stream fish in Missouri, USA based on species environmental tolerances, rarity, range size, dispersal ability and on the average connectivity of the streams occupied by each species. These two indices differed in how environmental tolerance was classified (i.e., vulnerability to habitat alteration, changes in stream temperature, and changes to flow regimes). Environmental tolerance was classified based on measured species responses to habitat alteration, and extremes in stream temperatures and flow conditions for one index, while environmental tolerance for the second index was based on species’ traits. The indices were compared to determine if vulnerability scores differed by index or state listing status. We also evaluated the spatial distribution of species classified as vulnerable to habitat alteration, changes in stream temperature, and change in flow regimes. Vulnerability scores were calculated for all 133 species with the trait association index, while only 101 species were evaluated using the species response index, because 32 species lacked data to analyze for a response. Scores from the trait association index were greater than the species response index. This is likely due to the species response index's inability to evaluate many rare species, which generally had high vulnerability scores for the trait association index. The indices were consistent in classifying vulnerability to habitat alteration, but varied in their classification of vulnerability due to increases in stream temperature and alterations to flow regimes, likely because extremes in current climate may not fully capture future conditions and their influence on stream fish communities. Both indices showed higher mean vulnerability scores for listed species than unlisted species, which provided a coarse measure of validation. Our indices classified species identified as being in need of conservation by the state of Missouri as highly vulnerable. The distribution of vulnerable species in Missouri showed consistent patterns between indices, with the more forest-dominated, groundwater fed streams in the Ozark subregion generally having higher numbers and proportions of vulnerable species per site than subregions that were agriculturally dominated with more overland flow. These results suggest that both indices will identify similar habitats as conservation action targets despite discrepancies in the classification of vulnerable species. Our vulnerability assessment provides a framework that can be refined and used in other regions.

Ecological Indicators↗

Through a fish's eye: The status of fish habitats in the United States 2015

This report updates and revises the 2010 “ Status of Fish Habitats in the United States” that summarized initial results of a comprehensive national assessment of aquatic habitats at an unprecedented scale and level of detail. This 2015 report provides even greater detail and improves our knowledge of the condition of fish habitat in the United States. The 2010 inland streams assessment characterized fish habitat condition using stream fish data from more than 26,000 stream reaches, while the 2015 assessment was based on fish data from more than 39,000 stream reaches nationally. To increase accuracy, the 2015 inland stream assessment incorporated 12 additional human disturbance variables into the fish analysis when compared to the 2010 assessment. Associations between all human disturbance variables summarized in both catchments as well as stream buffers were tested against stream fish metrics to develop assessment scores. Additional variables incorporated into the 2015 assessment and their summary within catchments and buffers allowed for more explicit characterization of the diverse set of disturbances to stream fish habitats occurring across the Nation than what occurred in 2010, and this was made possible due in part to advances in available GIS layers. With the incorporation of these additional disturbances, managers and decision makers can use assessment results to more explicitly identify limits to stream fish habitats. Even with the additional disturbances incorporated into 2015 assessment, results may overestimate fish habitat condition, as localized and regionally-specific disturbances are still not available in some cases.

Report↗

A spatial classification and database for management, research, and policy making: The Great Lakes aquatic habitat framework

Managing the world's largest and most complex freshwater ecosystem, the Laurentian Great Lakes, requires a spatially hierarchical basin-wide database of ecological and socioeconomic information that is comparable across the region. To meet such a need, we developed a spatial classification framework and database — Great Lakes Aquatic Habitat Framework (GLAHF). GLAHF consists of catchments, coastal terrestrial, coastal margin, nearshore, and offshore zones that encompass the entire Great Lakes Basin. The catchments captured in the database as river pour points or coastline segments are attributed with data known to influence physicochemical and biological characteristics of the lakes from the catchments. The coastal terrestrial zone consists of 30-m grid cells attributed with data from the terrestrial region that has direct connection with the lakes. The coastal margin and nearshore zones consist of 30-m grid cells attributed with data describing the coastline conditions, coastal human disturbances, and moderately to highly variable physicochemical and biological characteristics. The offshore zone consists of 1.8-km grid cells attributed with data that are spatially less variable compared with the other aquatic zones. These spatial classification zones and their associated data are nested within lake sub-basins and political boundaries and allow the synthesis of information from grid cells to classification zones, within and among political boundaries, lake sub-basins, Great Lakes, or within the entire Great Lakes Basin. This spatially structured database could help the development of basin-wide management plans, prioritize locations for funding and specific management actions, track protection and restoration progress, and conduct research for science-based decision making.

Great Lakes↗

Importance of understanding landscape biases in USGS gage locations: Implications and solutions for managers

Flow and water temperature are fundamental properties of stream ecosystems upon which many freshwater resource management decisions are based. U.S. Geological Survey (USGS) gages are the most important source of streamflow and water temperature data available nationwide, but the degree to which gages represent landscape attributes of the larger population of streams has not been thoroughly evaluated. We identified substantial biases for seven landscape attributes in one or more regions across the conterminous United States. Streams with small watersheds (<10 km 2 ) and at high elevations were often underrepresented, and biases were greater for water temperature gages and in arid regions. Biases can fundamentally alter management decisions and at a minimum this potential for error must be acknowledged accurately and transparently. We highlight three strategies that seek to reduce bias or limit errors arising from bias and illustrate how one strategy, supplementing USGS data, can greatly reduce bias.

Fisheries↗

Effects of dams in river networks on fish assemblages in non-impoundment sections of rivers in Michigan and Wisconsin, USA

Regional assessment of cumulative impacts of dams on riverine fish assemblages provides resource managers essential information for dam operation, potential dam removal, river health assessment and overall ecosystem management. Such an assessment is challenging because characteristics of fish assemblages are not only affected by dams, but also influenced by natural variation and human-induced modification (in addition to dams) in thermal and flow regimes, physicochemical habitats and biological assemblages. This study evaluated the impacts of dams on river fish assemblages in the non-impoundment sections of rivers in the states of Michigan and Wisconsin using multiple fish assemblage indicators and multiple approaches to distinguish the influences of dams from those of other natural and human-induced factors. We found that environmental factors that influence fish assemblages in addition to dams should be incorporated when evaluating regional effects of dams on fish assemblages. Without considering such co-influential factors, the evaluation is inadequate and potentially misleading. The role of dams alone in determining fish assemblages at a regional spatial scale is relatively small (explained less than 20% of variance) compared with the other environmental factors, such as river size, flow and thermal regimes and land uses jointly. However, our results do demonstrate that downstream and upstream dams can substantially modify fish assemblages in the non-impoundment sections of rivers. After excluding river size and land-use influences, our results clearly demonstrate that dams have significant impacts on fish biotic-integrity and habitat-and-social-preference indicators. The influences of the upstream dams, downstream dams, distance to dams, and dam density differ among the fish indicators, which have different implications for maintaining river biotic integrity, protecting biodiversity and managing fisheries.

Wisconsin and Michigan↗