Description: The ability of management strategies to achieve the fishery management goals are impacted by environmental variation and, therefore, also by global climate change. Management strategies can be modified to use environmental data using the "dynamic B 0 " concept, and changing the set of years used to define biomass reference points. Two approaches have been developed to apply management strategy evaluation to evaluate the impact of environmental variation on the performance of management strategies. The "mechanistic approach" estimates the relationship between the environment and elements of the population dynamics of the fished species and makes predictions for population trends using the outputs from global climate models. In contrast, the "empirical approach" examines possible broad scenarios without explicitly identifying mechanisms. Many reviewed studies have found that modifying management strategies to include environmental factors does not improve the ability to achieve management goals much, if at all, and only if the manner in which these factors drive the system is well known. As such, until the skill of stock projection models improves, it seems more appropriate to consider the implications of plausible broad forecasts related to how biological parameters may change in the future as a way to assess the robustness of management strategies, rather than attempting specific predictions per se .

Description: Welcomme, R. L. 2011. An overview of global catch statistics for inland fish. – ICES Journal of Marine Science, 68: 1751–1756. The reported global inland fish catch passed 10 million tonnes in 2008, after almost linear growth from the early 1950s. The rise coincides with an increasing number of reports of falling catches resulting from environmental degradation. It is thought that catches from inland waters were underreported in the past because of constraints on collecting the relevant data. National approaches to data collection are not generally comparable and their accuracy not usually assessed. National data processing and reporting should be audited, and training undertaken to harmonize these activities. The apparently bigger catches probably result from better reporting of actual catches rather than any increase in the amount of fish landed. Current data are sufficient only for a general overview of global inland catches of fish, rather than for the detailed analysis needed for management, policy formulation, and the valuation of inland fisheries. There is a need for improved approaches to data collection and for historical catches to be corrected to account for changes in methodologies and reporting procedures.

Description:    Gross primary productivity (GPP) is a major component of carbon exchange between the atmosphere and terrestrial ecosystems and a key component of the terrestrial carbon cycle. Because of the large spatial heterogeneity and temporal dynamics of ecosystems, it is a challenge to estimate GPP accurately at global or regional scales. The 8-day MODerate resolution Imaging Spectroradiometer (MODIS) GPP product provides a near real time estimate of global GPP. However, previous studies indicated that MODIS GPP has large uncertainties, partly caused by biases in parameterization and forcing data. In this study, MODIS GPP was validated using GPP derived from the eddy covariance flux measurements at five typical forest sites in East Asia. The validation indicated that MODIS GPP was seriously underestimated in these forest ecosystems of East Asia, especially at northern sites. With observed meteorological data, fraction of photosynthetically active radiation absorbed by the plant canopy (fPAR) calculated using smoothed MODIS leaf area index, and optimized maximum light use efficiency ( ε max ) to force the MOD17 algorithm, the agreement between predicted GPP and tower-based GPP was significantly improved. The errors of MODIS GPP in these forest ecosystems of East Asia were mainly caused by uncertainties in ε max , followed by those in fPAR and meteorological data. The separation of canopy into sunlit and shaded leaves, for which GPP is individually calculated, can improve GPP simulation significantly. Content Type Journal Article Category Special Feature: Original Article Pages 1-10 DOI 10.1007/s10310-012-0369-7 Authors Mingzhu He, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Yanlian Zhou, School of Geographic and Oceanographic Sciences, Nanjing University, Nanjing, 210093 China Weimin Ju, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Jingming Chen, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Li Zhang, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China Shaoqiang Wang, Qianyanzhou Ecological Experimental Station, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101 China Nobuko Saigusa, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506 Japan Ryuichi Hirata, Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, 305-8506 Japan Shohei Murayama, Research Institute for Environmental Management Technology, National Institute of Advanced Industrial Science and Technology (AIST), AIST Tsukuba West, 16-1 Onogawa, Tsukuba, 305-8569 Japan Yibo Liu, Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, International Institute for Earth System Science, Nanjing University, 901 Mengminwei Building, 22 Hankou Road, Nanjing, 210093 China Journal Journal of Forest Research Online ISSN 1610-7403 Print ISSN 1341-6979

Description:    In the last decades, due to climate changes, soil deterioration, and Land Use/Land Cover Changes (LULCCs), land degradation risk has become one of the most important ecological issues at the global level. Land degradation involves two interlocking systems: the natural ecosystem and the socio-economic system. The complexity of land degradation processes should be addressed using a multidisciplinary approach. Therefore, the aim of this work is to assess diachronically land degradation dynamics under changing land covers. This paper analyzes LULCCs and the parallel increase in the level of land sensitivity to degradation along the coastal belt of Sardinia (Italy), a typical Mediterranean region where human pressure affects the landscape characteristics through fires, intensive agricultural practices, land abandonment, urban sprawl, and tourism concentration. Results reveal that two factors mainly affect the level of land sensitivity to degradation in the study area: (i) land abandonment and (ii) unsustainable use of rural and peri-urban areas. Taken together, these factors represent the primary cause of the LULCCs observed in coastal Sardinia. By linking the structural features of the Mediterranean landscape with its functional land degradation dynamics over time, these results contribute to orienting policies for sustainable land management in Mediterranean coastal areas. Content Type Journal Article Pages 1-10 DOI 10.1007/s00267-012-9831-8 Authors S. Bajocco, Unit for Climatology and Meteorology in Agriculture (CRA-CMA), Italian National Agricultural Research Council, Via del Caravita 7a, 00186 Rome, RM, Italy A. De Angelis, Unit for Climatology and Meteorology in Agriculture (CRA-CMA), Italian National Agricultural Research Council, Via del Caravita 7a, 00186 Rome, RM, Italy L. Perini, Unit for Climatology and Meteorology in Agriculture (CRA-CMA), Italian National Agricultural Research Council, Via del Caravita 7a, 00186 Rome, RM, Italy A. Ferrara, Department of Crop Science, University of Basilicata, Via dell’Ateneo Lucano, Potenza, PZ, Italy L. Salvati, Centre for Soil-Plant Relationships (CRA-RPS), Italian National Agricultural Research Council, Via della Navicella 2-4, 00184 Rome, RM, Italy Journal Environmental Management Online ISSN 1432-1009 Print ISSN 0364-152X

Description:    Recent studies have demonstrated the geomorphic complexity and wide range of hydrologic regimes found in alpine headwater channels that provide complex habitats for aquatic taxa. These geohydrologic elements are fundamental to better understand patterns in species assemblages and indicator taxa and are necessary to aquatic monitoring protocols that aim to track changes in physical conditions. Complex physical variables shape many biological and ecological traits, including life history strategies, but these mechanisms can only be understood if critical physical variables are adequately represented within the sampling framework. To better align sampling design protocols with current geohydrologic knowledge, we present a conceptual framework that incorporates regional-scale conditions, basin-scale longitudinal profiles, valley-scale glacial macroform structure, valley segment-scale (i.e., colluvial, alluvial, and bedrock), and reach-scale channel types. At the valley segment- and reach-scales, these hierarchical levels are associated with differences in streamflow and sediment regime, water source contribution and water temperature. Examples of linked physical-ecological hypotheses placed in a landscape context and a case study using the proposed framework are presented to demonstrate the usefulness of this approach for monitoring complex temporal and spatial patterns and processes in glaciated basins. This approach is meant to aid in comparisons between mountain regions on a global scale and to improve management of potentially endangered alpine species affected by climate change and other stressors. Content Type Journal Article Pages 1-16 DOI 10.1007/s00267-012-9957-8 Authors Anne A. Weekes, Natural Systems Design, Seattle, WA, USA Christian E. Torgersen, U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, University of Washington, Seattle, WA, USA David R. Montgomery, Department of Earth and Space Sciences, Quaternary Research Center, University of Washington, Seattle, WA, USA Andrea Woodward, U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, Seattle, WA, USA Susan M. Bolton, School of Environmental and Forest Resources, University of Washington, Seattle, WA, USA Journal Environmental Management Online ISSN 1432-1009 Print ISSN 0364-152X

Description:    A method for obtaining a relative deer population density index with low cost and effort is urgently needed in wildlife protection areas that need their own deer management guidelines. We recorded the number of deer sighted during our daily trips on forest roads by car in Ashiu Forest at Kyoto University, Japan, beginning in 2006. We used generalized additive mixed models (GAMMs) to estimate among-year trends in the number of deer sighted. We applied models for the total number of deer (TND), number of adults (NA), and number of fawns (NF) sighted, which included both current-year and 1-year-old fawns. Full models included the terms of year (2007, 2008, 2009, and 2010), weather (fine, cloudy, and rain/snow), and nonlinear effects of season (date) and time (time). The optimal GAMMs for TND, NA, and NF did not include the effect of weather but included those of time, date, and year. The detected among-year trends in deer population may be influenced by differences in snow environments among the years. The modeling of road count data using GAMM quantitatively determined among-year variation in the number of deer sighted. This trend was similar to that of the population density estimated using a block count survey conducted in Ashiu Forest. Content Type Journal Article Category Original Article Pages 1-7 DOI 10.1007/s10310-012-0379-5 Authors Inoue Mizuki, Laboratory of Forest Science, Faculty of Bioresource Sciences, Akita Prefectural University, Akita, 010-0195 Japan Shota Sakaguchi, Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan Keitaro Fukushima, Field Science Education and Research Center, Kyoto University, Kyoto, Japan Masaru Sakai, Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan Atsushi Takayanagi, Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan Daisuke Fujiki, Institute of Natural and Environment Science, University of Hyogo, Tanba, Japan Michimasa Yamasaki, Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan Journal Journal of Forest Research Online ISSN 1610-7403 Print ISSN 1341-6979

Description: Wigand, L. A., Klinger, T., and Logsdon, M. G. 2013. Patterns in groundfish abundance along the Eastern Bering Sea outer continental margin. – ICES Journal of Marine Science, 70: 1181–1197. Place-based management approaches require understanding the spatial arrangement and interaction of elements. To address this need, we explored the utility of spatial-pattern analysis to understand the distribution of groundfish in the Eastern Bering Sea outer continental margin. We divided this region into discrete geomorphological units to explore spatial pattern on a range of scales. We used groundfish catch per unit effort (cpue) trawl survey data collected in four years to quantify spatial autocorrelation. Global statistics indicated that groundfish cpue was dominated by clusters of low values in all years. Local statistics showed that clusters of low values in groundfish cpue were confined to the southern portion of the study area, while clusters of high values varied across the study area. Outliers were most commonly found in close proximity to the shelf–slope break. Our results reveal the existence of spatial dependency in groundfish abundance and demonstrate that spatial analysis can be used to better understand spatial arrangements of these and other living marine resources, and to quantify and validate the local ecological knowledge of resource users. Our results indicate the feasibility of using spatially explicit tools to improve integration and visualization of marine environmental data for purposes of management and conservation.