Simple rules can guide whether land or ocean based conservation will best benefit marine ecosystems

Coastal marine ecosystems can be managed by actions undertaken both on the land and in the ocean. Quantifying and comparing the costs and benefits of actions in both realms is therefore necessary for efficient management. Here, we quantify the link between terrestrial sediment run-off and a downstream coastal marine ecosystem, and contrast the cost-effectiveness of marine and land-based conservation actions. We use a dynamic land- and sea-scape model to determine whether limited funds should be directed to one of four alternative conservation actions – protection on land, protection in the ocean, restoration on land, or restoration in the ocean – to maximise the extent of light-dependent marine benthic habitats, across decadal time-scales. We apply the model to a case study seagrass meadow in Australia. We find that marine restoration is the most cost-effective action over decadal time-scales in this system, based on a conservative estimate of the rate at which seagrass can expand into new habitat. The optimal decision will vary in different social-ecological contexts, but some basic information can guide optimal investments to counteract land and ocean based stressors: (1) marine restoration should be prioritised if the rates of marine ecosystem decline and expansion are similar and low; (2) marine protection should take precedence if the rate of marine ecosystem decline is high, or if the adjacent catchment is relatively intact and has a low rate of vegetation decline; (3) land-based actions are optimal when the ratio of marine ecosystem expansion to decline is >1.4, with terrestrial restoration typically the most cost effective; and (4) land protection should be prioritised if the catchment is relatively intact, but the rate of vegetation decline is high. These rules-of-thumb illustrate how cost-effective conservation outcomes for connected land-ocean systems can proceed without complex modelling

The power of information for targeting cost-effective conservation investments in multifunctional farmlands

Decisions about which places to conserve are based upon the geographic heterogeneity of three types of information: public goods or benefits, their vulnerability to threats, and the costs to avert those threats. The choice of public goods depends on the mission of the conservation organization (e.g., biodiversity, open space, cultural values, or farmland). For spatial targeting of conservation at the regional scale, practitioners must estimate the values of these types of information. The quality of the estimations will vary by the primary data used, the assumptions made, and the practitioner's technical ability to analyze complex data. This paper contributes to the growing literature by presenting a systematic evaluation of effect of the quality of the estimation on the cost-effectiveness of the set of sites selected for conservation based upon those estimates. The specific case study targets farmland for preservation from urban development in California's Central Valley where a new land trust was recently established to purchase conservation easements. In one analysis, we compared the cost-effectiveness of farmland benefits using our most sophisticated estimation procedures to those that ignored costs and/or potential loss (i.e., assumed they were equal among sites). Excluding information about the potential loss of resources caused only a slight decrease in cost-effectiveness. On the other hand, ignoring cost information was extremely inefficient. The second analysis compared the performance of the sophisticated estimate to increasingly simpler estimates, such as those that are representative of the methods used by many American farmland preservation programs. The simplification of the estimates caused a 5- to 20-fold decline in the benefits that could be retained for a given budget. To make more cost-effective targeting strategies accessible to farmland preservation programs, we recommend that researchers develop new spatial targeting tools to overcome obstacles in data processing. © 2010 Elsevier Ltd

Siting solar energy development to minimize biological impacts

After solar and other renewable energy developers select generally suitable sites for exploration, they frequently encounter conflict over biodiversity conservation values that were not factored into the initial suitability rating methods. This paper presents a spatial multicriteria analysis method for modeling risk of conflict with biological resources and applies the model in the California deserts where such conflicts are rapidly rising. The premise of the model is that the least conflict will occur on sites that are the most ecologically degraded with low conservation value and that would engender low off-site impacts when connecting to existing transmission infrastructure. Model results suggest sufficient compatible land exists in flat, non-urban areas to meet state solar energy targets of 8.7 GW of installed capacity in the California deserts for 2040. The model is a promising tool to fill the gap between site suitability analysis for renewable energy and regional biodiversity conservation planning to identify areas where rapid impact assessment and permitting will generate the least regrets. © 2013 Elsevier Ltd

Siting solar energy development to minimize biological impacts

After solar and other renewable energy developers select generally suitable sites for exploration, they frequently encounter conflict over biodiversity conservation values that were not factored into the initial suitability rating methods. This paper presents a spatial multicriteria analysis method for modeling risk of conflict with biological resources and applies the model in the California deserts where such conflicts are rapidly rising. The premise of the model is that the least conflict will occur on sites that are the most ecologically degraded with low conservation value and that would engender low off-site impacts when connecting to existing transmission infrastructure. Model results suggest sufficient compatible land exists in flat, non-urban areas to meet state solar energy targets of 8.7 GW of installed capacity in the California deserts for 2040. The model is a promising tool to fill the gap between site suitability analysis for renewable energy and regional biodiversity conservation planning to identify areas where rapid impact assessment and permitting will generate the least regrets. © 2013 Elsevier Ltd

The power of information for targeting cost-effective conservation investments in multifunctional farmlands

Decisions about which places to conserve are based upon the geographic heterogeneity of three types of information: public goods or benefits, their vulnerability to threats, and the costs to avert those threats. The choice of public goods depends on the mission of the conservation organization (e.g., biodiversity, open space, cultural values, or farmland). For spatial targeting of conservation at the regional scale, practitioners must estimate the values of these types of information. The quality of the estimations will vary by the primary data used, the assumptions made, and the practitioner's technical ability to analyze complex data. This paper contributes to the growing literature by presenting a systematic evaluation of effect of the quality of the estimation on the cost-effectiveness of the set of sites selected for conservation based upon those estimates. The specific case study targets farmland for preservation from urban development in California's Central Valley where a new land trust was recently established to purchase conservation easements. In one analysis, we compared the cost-effectiveness of farmland benefits using our most sophisticated estimation procedures to those that ignored costs and/or potential loss (i.e., assumed they were equal among sites). Excluding information about the potential loss of resources caused only a slight decrease in cost-effectiveness. On the other hand, ignoring cost information was extremely inefficient. The second analysis compared the performance of the sophisticated estimate to increasingly simpler estimates, such as those that are representative of the methods used by many American farmland preservation programs. The simplification of the estimates caused a 5- to 20-fold decline in the benefits that could be retained for a given budget. To make more cost-effective targeting strategies accessible to farmland preservation programs, we recommend that researchers develop new spatial targeting tools to overcome obstacles in data processing. © 2010 Elsevier Ltd

Spatial Patterns of Endemic Plants in California

California endemic vascular plant range patterns were quantified using a flora-based geodatabase technique that defined species range by geographic area and elevation band. Resulting species spatial patterns are reported for 228 geographic units. Over 60% of the endemic species range size distributions were found to have range sizes less than 10,000 km2. The largest endemic taxon range was 275,749 km2, or 67% of the state. California endemic plant richness distribution patterns are summarized by 228 geographic units, and reported by various criteria. California's Central Coast Ranges, Sierra Nevada foothills, high elevation Sierra Nevada Mountains, Channel Islands, San Jacinto Mountains, Napa and Lake Counties, Inyo Mountains, sections of the Mojave Desert, and San Bernardino Mountains were all identified as areas with unique endemic plant attributes. We compared endemic species richness between map units in zones containing similar topography and climate, and found that area only weakly correlated with species richness, suggesting other factors have stronger influence on endemism in continental California. The findings have implications for developing conservation plans that target endemic species. In particular, we identify areas of the state, previously de-emphasized, that deserve greater recognition based on the characteristics of their restricted endemic plants. This analysis underestimates the level of endemism near the borders with Oregon and Baja California because of the artificial limitation of the database to the boundaries of the state of California. However, range distribution estimates produced from digital renditions of floral keys proved effective in this study, an inexpensive approach that could be implemented in other regions of the world for which floras have been published

Modeling wildlife and other trade-offs with biofuel crop production

Biofuels from agricultural sources are an important part of California's strategy to reduce greenhouse gas emissions and dependence on foreign oil. Land conversion for agricultural and urban uses has already imperiled many animal species in the state. This study investigated the potential impacts on wildlife of shifts in agricultural activity to increase biomass production for transportation fuels. We applied knowledge of the suitability of California's agricultural landscapes for wildlife species to evaluate wildlife effects associated with plausible scenarios of expanded production of three potential biofuel crops (sugar beets, bermudagrass, and canola). We also generated alternative, spatially explicit scenarios that minimized loss of habitat for the same level of biofuel production. We explored trade-offs to compare the marginal changes per unit of energy for transportation costs, wildlife, land and water-use, and total energy produced, and found that all five factors were influenced by crop choice. Sugar beet scenarios require the least land area: 3.5 times less land per liter of gasoline equivalent than bermudagrass and five times less than canola. Canola scenarios had the largest impacts on wildlife but the greatest reduction in water use. Bermudagrass scenarios resulted in a slight overall improvement for wildlife over the current situation. Relatively minor redistribution of lands converted to biofuel crops could produce the same energy yield with much less impact on wildlife and very small increases in transportation costs. This framework provides a means to systematically evaluate potential wildlife impacts of alternative production scenarios and could be a useful complement to other frameworks that assess impacts on ecosystem services and greenhouse gas emissions. © 2011 Blackwell Publishing Ltd