Protected areas as frontiers for human migration

Causes of human population growth near protected areas have been much debated. We conducted 821 interviews in 16 villages around Budongo Forest Reserve, Masindi district, Uganda, to explore the causes of human migration to protected areas and to identify differences in forest use between migrant and nonmigrant communities. We asked subjects for information about birthplace, migration, household assets, household activities, and forest use. Interview subjects were categorized as nonmigrants (born in one of the interview villages), socioeconomic migrants (chose to emigrate for economic or social reasons) from within Masindi district (i.e., local migrants) and from outside the Masindi district (i.e., regional migrants), or forced migrants (i.e., refugees or internally displaced individuals who emigrated as a result of conflict, human rights abuses, or natural disaster). Only 198 respondents were born in interview villages, indicating high rates of migration between 1998 and 2008. Migrants were drawn to Budongo Forest because they thought land was available (268 individuals) or had family in the area (161 individuals). A greater number of regional migrants settled in villages near Lake Albert than did forced and local migrants. Migration category was also associated with differences in sources of livelihood. Of forced migrants 40.5% earned wages through labor, whereas 25.5% of local and 14.5% of regional migrants engaged in wage labor. Migrant groups appeared to have different effects on the environment. Of respondents that hunted, 72.7% were regional migrants. Principal component analyses indicated households of regional migrants were more likely to be associated with deforestation. Our results revealed gaps in current models of human population growth around protected areas. By highlighting the importance of social networks and livelihood choices, our results contribute to a more nuanced understanding of causes of migration and of the environmental effects of different migrant groups.     

Use of linkage mapping and centrality analysis across habitat gradients to conserve connectivity of gray wolf populations in western North America

Centrality metrics evaluate paths between all possible pairwise combinations of sites on a landscape to rank the contribution of each site to facilitating ecological flows across the network of sites. Computational advances now allow application of centrality metrics to landscapes represented as continuous gradients of habitat quality. This avoids the binary classification of landscapes into patch and matrix required by patch-based graph analyses of connectivity. It also avoids the focus on delineating paths between individual pairs of core areas characteristic of most corridor- or linkage-mapping methods of connectivity analysis. Conservation of regional habitat connectivity has the potential to facilitate recovery of the gray wolf (Canis lupus), a species currently recolonizing portions of its historic range in the western United States. We applied 3 contrasting linkage-mapping methods (shortest path, current flow, and minimum-cost-maximum-flow) to spatial data representing wolf habitat to analyze connectivity between wolf populations in central Idaho and Yellowstone National Park (Wyoming). We then applied 3 analogous betweenness centrality metrics to analyze connectivity of wolf habitat throughout the northwestern United States and southwestern Canada to determine where it might be possible to facilitate range expansion and interpopulation dispersal. We developed software to facilitate application of centrality metrics. Shortest-path betweenness centrality identified a minimal network of linkages analogous to those identified by least-cost-path corridor mapping. Current flow and minimum-cost-maximum-flow betweenness centrality identified diffuse networks that included alternative linkages, which will allow greater flexibility in planning. Minimum-cost-maximum-flow betweenness centrality, by integrating both land cost and habitat capacity, allows connectivity to be considered within planning processes that seek to maximize species protection at minimum cost. Centrality analysis is relevant to conservation and landscape genetics at a range of spatial extents, but it may be most broadly applicable within single- and multispecies planning efforts to conserve regional habitat connectivity.     

Challenges to interdisciplinary research in ecosystem-based management

Despite its necessity, integration of natural and social sciences to inform conservation efforts has been difficult. We examined the views of 63 scientists and practitioners involved in marine management in Mexico's Gulf of California, the central California coast, and the western Pacific on the challenges associated with integrating social science into research efforts that support ecosystem-based management (EBM) in marine systems. We used a semistructured interview format. Questions focused on how EBM was developed for these sites and how contextual factors affected its development and outcomes. Many of the traditional challenges linked with interdisciplinary research were present in the EBM projects we studied. However, a number of contextual elements affected how mandates to include social science were interpreted and implemented as well as how easily challenges could be addressed. For example, a common challenge is that conservation organizations are often dominated by natural scientists, but for some projects it was easier to address this imbalance than for others. We also found that the management and institutional histories that came before EBM in specific cases were important features of local context. Because challenges differed among cases, we believe resolving challenges to interdisciplinary research should be context specific.     

Use of an Airborne Lidar System to Model Plant Species Composition and Diversity of Mediterranean Oak Forests

Abstract: Airborne lidar is a remote‐sensing tool of increasing importance in ecological and conservation research due to its ability to characterize three‐dimensional vegetation structure. If different aspects of plant species diversity and composition can be related to vegetation structure, landscape‐level assessments of plant communities may be possible. We examined this possibility for Mediterranean oak forests in southern Portugal, which are rich in biological diversity but also threatened. We compared data from a discrete, first‐and‐last return lidar data set collected for 31 plots of cork oak (Quercus suber) and Algerian oak (Quercus canariensis) forest with field data to test whether lidar can be used to predict the vertical structure of vegetation, diversity of plant species, and community type. Lidar‐ and field‐measured structural data were significantly correlated (up to r= 0.85). Diversity of forest species was significantly associated with lidar‐measured vegetation height (R²= 0.50, p < 0.001). Clustering and ordination of the species data pointed to the presence of 2 main forest classes that could be discriminated with an accuracy of 89% on the basis of lidar data. Lidar can be applied widely for mapping of habitat and assessments of habitat condition (e.g., in support of the European Species and Habitats Directive [92/43/EEC]). However, particular attention needs to be paid to issues of survey design: density of lidar points and geospatial accuracy of ground‐truthing and its timing relative to acquisition of lidar data.     

Defining trade-offs among conservation, profitability, and food security in the California current bottom-trawl fishery

Although it is recognized that marine wild-capture fisheries are an important source of food for much of the world, the cost of sustainable capture fisheries to species diversity is uncertain, and it is often questioned whether industrial fisheries can be managed sustainably. We evaluated the trade-off among sustainable food production, profitability, and conservation objectives in the groundfish bottom-trawl fishery off the U.S. West Coast, where depletion (i.e., reduction in abundance) of six rockfish species (Sebastes) is of particular concern. Trade-offs are inherent in this multispecies fishery because there is limited capacity to target species individually. From population models and catch of 34 stocks of bottom fish, we calculated the relation between harvest rate, long-term yield (i.e., total weight of fish caught), profit, and depletion of each species. In our models, annual ecosystem-wide yield from all 34 stocks was maximized with an overall 5.4% harvest rate, but profit was maximized at a 2.8% harvest rate. When we reduced harvest rates to the level (2.2% harvest rate) at which no stocks collapsed (<10% of unfished levels), biomass harvested was 76% of the maximum sustainable yield and profit 89% of maximum. A harvest rate under which no stocks fell below the biomass that produced maximum sustainable yield (1% harvest rate), resulted in 45% of potential yield and 67% of potential profit. Major reductions in catch in the late 1990s led to increase in the biomass of the most depleted stocks, but this rebuilding resulted in the loss of >30% of total sustainable yield, whereas yield lost from stock depletion was 3% of total sustainable yield. There are clear conservation benefits to lower harvest rates, but avoiding overfishing of all stocks in a multispecies fishery carries a substantial cost in terms of lost yield and profit.     

Assessing citizen contributions to butterfly monitoring in two large cities

Citizen science may be especially effective in urban landscapes due to the large pool of potential volunteers. However, there have been few evaluations of the contributions of citizen scientists to knowledge of biological communities in and around cities. To assess the effectiveness of citizen scientists' monitoring of species in urban areas, we compared butterfly data collected over 10 years in Chicago, Illinois (U.S.A.), and New York City, New York (U.S.A.). The dates, locations, and methods of data collection in Chicago were standardized, whereas data from New York were collected at any location at any time. For each city, we evaluated whether the number of observers, observation days (days on which observations were reported), and sampling locations were associated with the reported proportion of the estimated regional pool of butterfly species. We also compared the number of volunteers, duration of volunteer involvement, and consistency of sampling efforts at individual locations within each city over time. From 2001 to 2010, there were 73 volunteers in Chicago and 89 in New York. During this period, volunteers observed 86% and 89% of the estimated number of butterfly species present in Chicago and New York, respectively. Volunteers in New York reported a greater proportion of the estimated pool of butterfly species per year. In addition, more species were observed per volunteer and observation day in New York, largely due to the unrestricted sampling season in New York. Chicago volunteers were active for more years and monitored individual locations more consistently over time than volunteers in New York. Differences in monitoring protocol--especially length of sampling season and selection protocol for monitoring locations--influenced the relationship between species accrual and sampling effort, which suggests these factors are important in volunteer-based species-monitoring programs.     

Eliciting expert knowledge in conservation science

Expert knowledge is used widely in the science and practice of conservation because of the complexity of problems, relative lack of data, and the imminent nature of many conservation decisions. Expert knowledge is substantive information on a particular topic that is not widely known by others. An expert is someone who holds this knowledge and who is often deferred to in its interpretation. We refer to predictions by experts of what may happen in a particular context as expert judgments. In general, an expert-elicitation approach consists of five steps: deciding how information will be used, determining what to elicit, designing the elicitation process, performing the elicitation, and translating the elicited information into quantitative statements that can be used in a model or directly to make decisions. This last step is known as encoding. Some of the considerations in eliciting expert knowledge include determining how to work with multiple experts and how to combine multiple judgments, minimizing bias in the elicited information, and verifying the accuracy of expert information. We highlight structured elicitation techniques that, if adopted, will improve the accuracy and information content of expert judgment and ensure uncertainty is captured accurately. We suggest four aspects of an expert elicitation exercise be examined to determine its comprehensiveness and effectiveness: study design and context, elicitation design, elicitation method, and elicitation output. Just as the reliability of empirical data depends on the rigor with which it was acquired so too does that of expert knowledge.     

一株中度嗜盐菌的分离及生物学特性

从我国内蒙古吉兰泰盐湖的样品中分离得到一株中度嗜盐细菌菌株JLT-01,研究了其形态和特性.结果显示:该菌株为杆状,革兰氏阴性,无芽孢,无荚膜,无鞭毛;最适培养温度为30℃,最适生长pH值7.5,最适生长盐度10%~12%(m/V),最适生长Mg2+浓度3.0%(m/V);能利用葡萄糖、蔗糖、半乳糖作为唯一碳源生长.脂肪酸成分分析表明在JLT-01中主要脂肪酸为C16:0与C18:1ω9c,含量分别为26.39%和20.30%.Tm法测定该菌的(G+C)含量(摩尔分数)为52.3%.以该菌的16S rRNA基因序列为基础构建了系统发育树;16S rRNA基因序列的序列同源性比对表明该菌与海杆菌属Marinobacter lipolyticus SM19T的同源性为98.0%,与Marinobacter属内其它菌株的同源性在96.0%~99.0%之间.DNA-DNA杂交实验分析显示:JLT-01与M.lipolyticus DSM15157的杂交率小于70%.结果表明,菌株JLT-01是海杆菌属的一个新菌株.     

珠江三角洲城市雨水的化学组成及其成因探讨

于2005—2007年间,基于降水过程监测分析了广州市和珠海市雨水的化学组成。结果表明,广州市雨水的pH值变化于3.32~7.03之间,平均值为4.35,众数约为4.15。珠海市雨水的pH值变化于3.38~6.49之间,平均值为4.51。雨水pH值随降水强度的减弱而降低,这决定于大气中水汽与酸性气体的接触时间。珠江三角洲城市雨水中所含主要离子依次是SO42-、NO3-、NH4＋、Ca2＋、Cl-。雨水的酸化与降水过程密切相关。降雨初期雨水比中后期雨水的pH值高,揭示降雨初期大气中的粉尘颗粒有效中和雨水的酸度。多天连续降水天气对大气尘埃的清洗作用明显,但是持续的SO2和NOx排放更容易使雨水酸化。滨海城市降水初期雨水的电导率上升较快（可以从小于1μS.cm-1上升到20~30μS.cm-1）,随着降水时间的延长雨水的电导率以较慢的速率上升。     

厦门近海沉积物中高分子有机质的来源初探

采用多步连续-湿法-化学方法,分离提纯了于2010年7月和12月在厦门近海采集的沉积物样品,获得3类高分子有机质,即腐殖酸（HA）、干酪根和碳黑（KB）和碳黑（BC）。以扫描电镜（SEM）作为有效的辅助手段,观察沉积物原样及高分子有机质的形貌特征,结合稳定碳同位素（δ13C）的分析,初步探讨了厦门近海沉积物中高分子有机质的来源。扫描电镜观察发现,在原样沉积物中存在多种海源物质（如钙质硅藻和圆筛藻/冠盘藻）;而在KB样品中同时发现类似于陆地植物的木质碎片以及来自海洋的藻胶鞘,暗示了其来源是海源与陆源共同作用的结果。稳定碳同位素研究表明厦门湾近海海域沉积物中有机质以陆源影响占优势,其比例在58.32%至84.45%之间;δ13C值整体上显示为夏季的贫于冬季的,这与研究区域的生态系统中陆源C3植被和海源水生植物的繁殖生长有关,同时还有排海污水及化石燃料煤燃烧后或者运煤船只洒落的碎屑的贡献。