Living with the Sea: Local Efforts Buffer Effects of Global Change

Living with the Sea examines the role of MMAs (Marine Managed Areas) in restoring and sustaining healthy oceans, particularly the importance of local management efforts. This document draws on MMA experiences worldwide by synthesizing results from over 25 natural science studies conducted over the past five years in 18 tropical countries in 48 MMAs. The analysis focuses on the role of MMAs in maintaining healthy oceans, showing that MMAs can be used to enhance fisheries outside their borders and safeguard threatened species. Conserving multiple habitats using MMAs can also protect diverse livelihoods and increase fisheries yields. Local protection of marine resources through the MMA process can provide strong local benefits to species, habitats, and people. Local protection buffers against global climate change impacts while maintaining the richness of marine life. Finally, MMAs benefit by using new scientific approaches and engaging citizen scientists

Marine Managed Areas: What, Why, and Where

This paper, which focuses on ocean and coastal areas, explores the challenge of public participation by discussing the role of communities in IM. It draws on a decade of collaboration between academics and community partners to outline the community perspective on both the limiting factors and the opportunities, and a state-of-the-art survey of community involvement in IM, parti-cularly in the Canadian Maritimes. The paper highlights the importance of linking communities and governments, and the need to overcome the growing disconnect between the two. It also illustrates the varied experiences of local coastal communities with IM through three concrete examples. These practical examples lead to two specific out-puts: a set of fundamental IM values and attributes from a community perspective, and a four-step process for facilitating and enabling community-focused IM.The conclusion summarizes key outcomes in terms of inclusivity and active involvement of communities

The caribbean coastal marine productivity program (CARICOMP)

CARICOMP is a regional scientific program to study land-sea interaction processes in the Caribbean coastal zone. It has been collecting data since 1992, when a Data Management Centre was established at the University of the West Indies in Jamaica. Initially it focuses on documenting the structure and productivity of major coastal communities (mangrove forests, seagrass meadows and coral reefs) at relatively undisturbed sites in diverse physical settings. Second, by regular recording of physical and biological parameters, it monitors for change, seeking to distinguish natural from anthropogenic disturbance. Third, it constitutes a regional network of observers, able to collaborate on studies of region-wide events. Examples are presented of the diverse data sets collected by the Program.Fil: Alcolado, Pedro M.. Instituto de Oceanología; CubaFil: Alleng, Gerard. No especifíca;Fil: Bonair, Kurt. No especifíca;Fil: Bone, David. Universidad Simón Bolívar; VenezuelaFil: Buchan, Kenneth. No especifíca;Fil: Bush, Phillippe G.. Protection and Conservation Unit; Islas CaimánFil: De Meyer, Kalli. No especifíca;Fil: Garcia, Jorge R.. Universidad de Puerto Rico; Puerto RicoFil: Garzón Ferreira, Jaime. Instituto de Investigaciones Marinas y Costeras; ColombiaFil: Gayle, Peter M. H.. Discovery Bay Marine Laboratory; JamaicaFil: Gerace, Donald T.. Bahamian Field Station; BahamasFil: Geraldes, Francisco X.. Universidad Autonoma de Santo Domingo.; República DominicanaFil: Dahlgren, Eric Jordán. Universidad Nacional Autónoma de México; MéxicoFil: Kjferve, Björn. University of South Carolina; Estados UnidosFil: Klein, Eduardo. Universidad Simón Bolívar; VenezuelaFil: Koltes, Karen. Smithsonian Institution; Estados UnidosFil: Laydoo, Richard S.. No especifíca;Fil: Linton, Dulcie M.. University of the West Indies ; JamaicaFil: Ogden, John C.. Florida Institute of Oceanography; Estados UnidosFil: Oxenford, Hazel A.. McGill University; BarbadosFil: Parker, Christoph. McGill University; BarbadosFil: Penchaszadeh, Pablo Enrique. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Museo Argentino de Ciencias Naturales "Bernardino Rivadavia"; ArgentinaFil: Pors, Leon P. P. J.. Universidad Simón Bolívar; VenezuelaFil: Ramírez Ramírez, Javier. Instituto Politécnico Nacional. Centro de Investigación y de Estudios Avanzados. Departamento de Física; MéxicoFil: Ruiz Rentería, Francisco. Universidad Nacional Autónoma de México; MéxicoFil: Ryan, Joseph D.. Centro de Investigación y Documentación de la Costa Atlántica; NicaraguaFil: Smith, Struan R.. Bermuda Biological Station for Research; BermudasFil: Tschirky, John. Latin American and Caribbean Division; Estados UnidosFil: Varela, Ramon. Estación de Investigaciones Marinas de Margarita; VenezuelaFil: Walker, Susan. No especifíca;Fil: Weil, Ernesto. Universidad de Puerto Rico; Puerto RicoFil: Wiebe, William J.. University of Georgia; Estados UnidosFil: Woodley, Jeremy D.. University of the West Indies; JamaicaFil: Zieman, Joseph C.. University of Virginia; Estados Unido

Caribbean-Wide, Long-Term Study of Seagrass Beds Reveals Local Variations, Shifts in Community Structure and Occasional Collapse

The CARICOMP monitoring network gathered standardized data from 52 seagrass sampling stations at 22 sites (mostly Thalassia testudinum-dominated beds in reef systems) across the Wider Caribbean twice a year over the period 1993 to 2007 (and in some cases up to 2012). Wide variations in community total biomass (285 to >2000 g dry m−2) and annual foliar productivity of the dominant seagrass T. testudinum (2000 g dry m−2) were found among sites. Solar-cycle related intra-annual variations in T. testudinum leaf productivity were detected at latitudes > 16°N. Hurricanes had little to no long-term effects on these well-developed seagrass communities, except for 1 station, where the vegetation was lost by burial below ∼1 m sand. At two sites (5 stations), the seagrass beds collapsed due to excessive grazing by turtles or sea-urchins (the latter in combination with human impact and storms). The low-cost methods of this regional-scale monitoring program were sufficient to detect long-term shifts in the communities, and fifteen (43%) out of 35 long-term monitoring stations (at 17 sites) showed trends in seagrass communities consistent with expected changes under environmental deterioration.UCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro de Investigación en Ciencias del Mar y Limnología (CIMAR

Deviations from general mean leaf productivity (ΔP) of <i>Thalassia testudinum</i> per station during High growth season (May-September at site 1 and 2, March –August at all other sites) and Low growth season (October-April at sites 1 and 2, September-February at all other sites).

<p>See <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0090600#pone.0090600.s006" target="_blank">Table S4</a> for significance differences of ΔP. Only stations with at least 10 sampling events were included. Numbers above the X-axis indicate site number, and the minor ticks indicate the different sampling stations at those sites.</p

Map of CARICOMP seagrass sites, ordered according to latitude.

<p>1. Bermuda, 2. USA-Long Key, 3. Bahamas-San Salvador, 4. Cuba-Cayo Coco, 5. Mexico-Puerto Morelos, 6. Mexico-Celestun, 7. Cayman Islands-Grand Cayman, 8. Jamaica-Discovery Bay, 9. Dominican Republic-Parque Nacional Este, 10. Puerto Rico-La Parguera, 11. Belize-Turneffe Island, 12. Belize-Twin Cays/Carrie Bow Cay, 13. Colombia-Isla Providencia, 14. Barbados-St. Lawrence, 15. Colombia-Isla San Andres, 16. Curaçao-Spaanse Water, 17. Colombia-Chengue Bay, 18. Tobago-Bon Accord Lagoon, 19. Venezuela-Isla de Margarita, 20. Venezuela-Morrocoy, 21. Costa Rica-Cahuita, 22. Panama-Isla de Colon.</p

Annual leaf productivity of <i>Thalassia testudinum</i> per sampling station.

<p>The stations are grouped per site (underlined, 1–6 stations per site), and stations only sampled during one season are excluded. The boxes and vertical bars represent inter-annual variation. The horizontal lines correspond with the median values, 50% of the cases are within the box limits and the vertical bars indicate the smallest or largest values that are not outliers, • represent values more than 1.5 box lengths from lower/upper box limit, and * represent values more than 3 box-lengths from lower/upper box limit. The digits above the bars indicate N (the number of sampling years). Grey bars represent stations that were not included in the long-term analysis.</p