A scientific synthesis of marine protected areas in the United States: status and recommendations

Marine protected areas (MPAs) are a key tool for achieving goals for biodiversity conservation and human well-being, including improving climate resilience and equitable access to nature. At a national level, they are central components in the U.S. commitment to conserve at least 30% of U.S. waters by 2030. By definition, the primary goal of an MPA is the long-term conservation of nature; however, not all MPAs provide the same ecological and social benefits. A U.S. system of MPAs that is equitable, well-managed, representative and connected, and includes areas at a level of protection that can deliver desired outcomes is best positioned to support national goals. We used a new MPA framework, The MPA Guide, to assess the level of protection and stage of establishment of the 50 largest U.S. MPAs, which make up 99.7% of the total U.S. MPA area (3.19 million km2). Over 96% of this area, including 99% of that which is fully or highly protected against extractive or destructive human activities, is in the central Pacific ocean. Total MPA area in other regions is sparse – only 1.9% of the U.S. ocean excluding the central Pacific is protected in any kind of MPA (120,976 km2). Over three quarters of the non-central Pacific MPA area is lightly or minimally protected against extractive or destructive human activities. These results highlight an urgent need to improve the quality, quantity, and representativeness of MPA protection in U.S. waters to bring benefits to human and marine communities. We identify and review the state of the science, including focal areas for achieving desired MPA outcomes and lessons learned from places where sound ecological and social design principles come together in MPAs that are set up to achieve national goals for equity, climate resilience, and biodiversity conservation. We recommend key opportunities for action specific to the U.S. context, including increasing funding, research, equity, and protection level for new and existing U.S. MPAs

Landscape ecosystems of the University of Michigan Biological Station: Ecosystem diversity and ground-cover diversity.

To provide a comprehensive ecological framework and baseline of data for research and education, the landscape ecosystems of the University of Michigan Biological Station were identified, classified, described, and mapped. This framework served as the basis for a study of the diversity of landscape ecosystems (the number and kinds of ecosystem types, their spatial patterns, and degree of similarity) and ground-cover vegetation. Recognizing the lack of approaches to measuring ecosystem diversity, ecosystem diversity was described and compared among landforms. A set of alpha indices was used, and for the first time a beta-level index, the information dimension (a scale-specific, location-specific, multi-factor index), was used with ecosystems. Large landforms had high total ecosystem richness; small landforms with complex patterns of substrate deposition at fine scales had greatest ecosystem richness per hectare and beta diversity. The information dimension revealed scales of grouping among ecosystem types in several landforms. Alpha diversity of ground-cover (richness, heterogeneity, and evenness) was greatest in moraine ecosystems for uplands. Wetlands in outwash plains had greatest diversity of ground-cover. For the first time, the relationship of ground-cover diversity to ecosystem diversity was tested. Beta diversity of ground-cover was positively related to ecosystem richness on a per-unit area basis, but the test for a link to beta ecosystem diversity was inconclusive. To examine the effect of differing light levels on ground-cover richness, ecosystems on two landforms differing in overstory coverage were compared. Richness declined as canopy coverage increased from moderate to high, but increased directly with soil pH and silt+clay content in ecosystems with low to moderate canopy coverage. To explore differences in ecosystem diversity among areas of different regions, three landscapes were compared. The Biological Station (125 ecosystem types) exceeded the Sylvania Wilderness Area (25) the McCormick Experimental Forest (21) in ecosystem richness. Beta diversity of ecosystems was greatest at Sylvania, followed by McCormick. The ice-contact landforms at Sylvania and the bedrock-ridges at McCormick are characterized by steep slopes that end abruptly, leading to sharp contrasts between ecosystems high values for the information dimension.Ph.D.Biological SciencesEcologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/129722/2/9610219.pd

Multidecadal shifts in forest plant diversity and community composition across glacial landforms in northern lower Michigan, USA

Understanding how plant community assemblage is affected by spatial and temporal patterns is crucial to understanding forest ecosystem responses to disturbance, including future climate change. Here we tracked how diversity and composition are distributed through space and time in a mid-successional mixed hardwood forest in northern lower Michigan, USA. This regionâ s geographically and abiotically distinct glacial landforms influence both the spatial and temporal dynamics of its forest communities. Vegetation sampling plots (n=87) were established at the University of Michigan Biological Station in 1990 and resampled in 2015. Vegetation in the overstory, sapling, and groundcover layers was censused. Abiotic variables, including elevation, pH, and soil nutrients, were measured in a subset of plots (n=40). There were strong differences in diversity and community composition among glacial landforms, with the Moraine (MOR) having a 31% greater species richness in the groundcover layer than the other glacial landforms. Surprisingly, plant communities across all three vegetation layers showed little change over the twenty-five-year period and we found no evidence of differences in successional rates between landforms. Our findings indicate a large influence of glacial landforms on the production and maintenance of local plant diversity and community composition in this area and also suggest that successional dynamics may manifest themselves over much longer time periods in these northern biomes.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Designing coastal conservation to deliver ecosystem and human well-being benefits

<div><p>Conservation scientists increasingly recognize that incorporating human values into conservation planning increases the chances for success by garnering broader project acceptance. However, methods for defining quantitative targets for the spatial representation of human well-being priorities are less developed. In this study we employ an approach for identifying regionally important human values and establishing specific spatial targets for their representation based on stakeholder outreach. Our primary objective was to develop a spatially-explicit conservation plan that identifies the most efficient locations for conservation actions to meet ecological goals while sustaining or enhancing human well-being values within the coastal and nearshore areas of the western Lake Erie basin (WLEB). We conducted an optimization analysis using 26 features representing ecological and human well-being priorities (13 of each), and included seven cost layers. The influence that including human well-being had on project results was tested by running five scenarios and setting targets for human well-being at different levels in each scenario. The most important areas for conservation to achieve multiple goals are clustered along the coast, reflecting a concentration of existing or potentially restorable coastal wetlands, coastal landbird stopover habitat and terrestrial biodiversity, as well as important recreational activities. Inland important areas tended to cluster around trails and high quality inland landbird stopover habitat. Most concentrated areas of importance also are centered on lands that are already conserved, reflecting the lower costs and higher benefits of enlarging these conserved areas rather than conserving isolated, dispersed areas. Including human well-being features in the analysis only influenced the solution at the highest target levels.</p></div

Results for Scenario 1.

<p>Targets based on workshop survey scores normalized to 100. Darker colors represent higher priority areas for conservation or restoration. Data credits: States/Provinces from U.S. States and Canada Provinces, Tele Atlas North America, Inc.; Cities from U.S. Cities, Data and maps for ArcGIS, ESRI; U.S. and Canada City points, Tele Atlas North America, Inc.; Lakes from Great Lakes GIS, Institute for Fisheries Research, Michigan Department of Natural Resources Fisheries Division and University of Michigan, School of Natural Resources.</p

Hectares of terrestrial and important aquatic area in the resulting priority area (top 10%).

<p>Hectares of terrestrial and important aquatic area in the resulting priority area (top 10%).</p

Human well-being priorities, corresponding conservation features, and targets used in the WLECCV analysis, with corresponding domain(s) of human well-being (adapted from Smith et al. 2013 [29]).

<p>Only the target for Scenario 1 (highest level) is shown.</p

Showing 10-ha hexagon spatial planning units used in the WLECCV optimization analysis.

<p>Framework is shown here overlaid on the northern reach of the Detroit River, including portions of Michigan U.S.A. and Ontario, Canada. Data credits: States/Provinces from U.S. States and Canada Provinces, Tele Atlas North America, Inc.; Cities from U.S. Cities, Data and maps for ArcGIS, ESRI; U.S. and Canada City points, Tele Atlas North America, Inc.; Lakes from Great Lakes GIS, Institute for Fisheries Research, Michigan Department of Natural Resources Fisheries Division and University of Michigan, School of Natural Resources; Great Lakes Basin from Great Lakes GIS, Institute for Fisheries Research, Michigan Department of Natural Resources Fisheries Division and University of Michigan, School of Natural Resources; Roads from U.S. and Canada Major Roads, Tele Atlas North America, Inc.</p