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Upon publication of the original article [1], the authors noticed that the figure labelling for Fig. 4 in the online version was processed wrong. The top left panel should be panel a, with the panels to its right being b and c. d and e should be the panels on the lower row, and f is correct. The graphs themselves are all correct. It is simply the letter labels that are wrong.

Agricultural expansion has resulted in both land use and land cover change (LULCC) across the tropics. However, the spatial and temporal patterns of such change and their resulting impacts are poorly understood, particularly for the presatellite era. Here, we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo-referenced and digitized historical land cover maps (dated 1908, 1923, 1949 and 2000). Our time series from this biodiversity hotspot shows that forest and savanna area both declined, by 74% (2.8 million ha) and 10% (2.9 million ha), respectively, between 1908 and 2000. This vegetation was replaced by a fivefold increase in cropland, from 1.2 million ha to 6.7 million ha. This LULCC implies a committed release of 0.9 Pg C (95% CI: 0.4-1.5) across the watershed for the same period, equivalent to 0.3 Mg C ha(-1)  yr(-1) . This is at least threefold higher than previous estimates from global models for the same study area. We then used the LULCC data from before and after protected area creation, as well as from areas where no protection was established, to analyse the effectiveness of legal protection on land cover change despite the underlying spatial variation in protected areas. We found that, between 1949 and 2000, forest expanded within legally protected areas, resulting in carbon uptake of 4.8 (3.8-5.7) Mg C ha(-1) , compared to a committed loss of 11.9 (7.2-16.6) Mg C ha(-1) within areas lacking such protection. Furthermore, for nine protected areas where LULCC data are available prior to and following establishment, we show that protection reduces deforestation rates by 150% relative to unprotected portions of the watershed. Our results highlight that considerable LULCC occurred prior to the satellite era, thus other data sources are required to better understand long-term land cover trends in the tropics., (© 2016 John Wiley & Sons Ltd.)

Restoration of degraded land is recognized by the international community as an important way of enhancing both biodiversity and ecosystem services, but more information is needed about its costs and benefits. In Cambridgeshire, U.K., a long-term initiative to convert drained, intensively farmed arable land to a wetland habitat mosaic is driven by a desire both to prevent biodiversity loss from the nationally important Wicken Fen National Nature Reserve (Wicken Fen NNR) and to increase the provision of ecosystem services. We evaluated the changes in ecosystem service delivery resulting from this land conversion, using a new Toolkit for Ecosystem Service Site-based Assessment (TESSA) to estimate biophysical and monetary values of ecosystem services provided by the restored wetland mosaic compared with the former arable land. Overall results suggest that restoration is associated with a net gain to society as a whole of $199 ha(-1)y(-1), for a one-off investment in restoration of $2320 ha(-1). Restoration has led to an estimated loss of arable production of $2040 ha(-1)y(-1), but estimated gains of $671 ha(-1)y(-1) in nature-based recreation, $120 ha(-1)y(-1) from grazing, $48 ha(-1)y(-1) from flood protection, and a reduction in greenhouse gas (GHG) emissions worth an estimated $72 ha(-1)y(-1). Management costs have also declined by an estimated $1325 ha(-1)y(-1). Despite uncertainties associated with all measured values and the conservative assumptions used, we conclude that there was a substantial gain to society as a whole from this land-use conversion. The beneficiaries also changed from local arable farmers under arable production to graziers, countryside users from towns and villages, and the global community, under restoration. We emphasize that the values reported here are not necessarily transferable to other sites.

Background: The carbon stored in vegetation varies across tropical landscapes due to a complex mix of climatic and edaphic variables, as well as direct human interventions such as deforestation and forest degradation. Mapping and monitoring this variation is essential if policy developments such as REDD+ (Reducing Emissions from Deforestation and Forest Degradation) are to be known to have succeeded or failed., Results: We produce a map of carbon storage across the watershed of the Tanzanian Eastern Arc Mountains (33.9 million ha) using 1,611 forest inventory plots, and correlations with associated climate, soil and disturbance data. As expected, tropical forest stores more carbon per hectare (182 Mg C ha(-1)) than woody savanna (51 Mg C ha(-1)). However, woody savanna is the largest aggregate carbon store, with 0.49 Pg C over 9.6 million ha. We estimate the whole landscape stores 1.3 Pg C, significantly higher than most previous estimates for the region. The 95% Confidence Interval for this method (0.9 to 3.2 Pg C) is larger than simpler look-up table methods (1.5 to 1.6 Pg C), suggesting simpler methods may underestimate uncertainty. Using a small number of inventory plots with two censuses (n = 43) to assess changes in carbon storage, and applying the same mapping procedures, we found that carbon storage in the tree-dominated ecosystems has decreased, though not significantly, at a mean rate of 1.47 Mg C ha(-1) yr(-1) (c. 2% of the stocks of carbon per year)., Conclusions: The most influential variables on carbon storage in the region are anthropogenic, particularly historical logging, as noted by the largest coefficient of explanatory variable on the response variable. Of the non-anthropogenic factors, a negative correlation with air temperature and a positive correlation with water availability dominate, having smaller p-values than historical logging but also smaller influence. High carbon storage is typically found far from the commercial capital, in locations with a low monthly temperature range, without a strong dry season, and in areas that have not suffered from historical logging. The results imply that policy interventions could retain carbon stored in vegetation and likely successfully slow or reverse carbon emissions.

Monitoring landscape carbon storage is critical for supporting and validating climate change mitigation policies. These may be aimed at reducing deforestation and degradation, or increasing terrestrial carbon storage at local, regional and global levels. However, due to data-deficiencies, default global carbon storage values for given land cover types such as 'lowland tropical forest' are often used, termed 'Tier 1 type' analyses by the Intergovernmental Panel on Climate Change (IPCC). Such estimates may be erroneous when used at regional scales. Furthermore uncertainty assessments are rarely provided leading to estimates of land cover change carbon fluxes of unknown precision which may undermine efforts to properly evaluate land cover policies aimed at altering land cover dynamics. Here, we present a repeatable method to estimate carbon storage values and associated 95% confidence intervals (CI) for all five IPCC carbon pools (aboveground live carbon, litter, coarse woody debris, belowground live carbon and soil carbon) for data-deficient regions, using a combination of existing inventory data and systematic literature searches, weighted to ensure the final values are regionally specific. The method meets the IPCC 'Tier 2' reporting standard. We use this method to estimate carbon storage over an area of33.9 million hectares of eastern Tanzania, reporting values for 30 land cover types. We estimate that this area stored 6.33 (5.92-6.74) Pg C in the year 2000. Carbon storage estimates for the same study area extracted from five published Africa-wide or global studies show a mean carbon storage value of ∼50% of that reported using our regional values, with four of the five studies reporting lower carbon storage values. This suggests that carbon storage may have been underestimated for this region of Africa. Our study demonstrates the importance of obtaining regionally appropriate carbon storage estimates, and shows how such values can be produced for a relatively low investment.

In East Africa, human population growth and demands for natural resources cause forest loss contributing to increased carbon emissions and reduced biodiversity. Protected Areas (PAs) are intended to conserve habitats and species. Variability in PA effectiveness and 'leakage' (here defined as displacement of deforestation) may lead to different trends in forest loss within, and adjacent to, existing PAs. Here, we quantify spatial variation in trends of evergreen forest coverage in East Africa between 2001 and 2009, and test for correlations with forest accessibility and environmental drivers. We investigate PA effectiveness at local, landscape and national scales, comparing rates of deforestation within park boundaries with those detected in park buffer zones and in unprotected land more generally. Background forest loss (BFL) was estimated at -9.3% (17,167 km(2)), but varied between countries (range: -0.9% to -85.7%; note: no BFL in South Sudan). We document high variability in PA effectiveness within and between PA categories. The most successful PAs were National Parks, although only 26 out of 48 parks increased or maintained their forest area (i.e. Effective parks). Forest Reserves (Ineffective parks, i.e. parks that lose forest from within boundaries: 204 out of 337), Nature Reserves (six out of 12) and Game Parks (24 out of 26) were more likely to lose forest cover. Forest loss in buffer zones around PAs exceeded background forest loss, in some areas indicating leakage driven by Effective National Parks. Human pressure, forest accessibility, protection status, distance to fires and long-term annual rainfall were highly significant drivers of forest loss in East Africa. Some of these factors can be addressed by adjusting park management. However, addressing close links between livelihoods, natural capital and poverty remains a fundamental challenge in East Africa's forest conservation efforts.

We present a GIS method to interpret qualitatively expressed socio-economic scenarios in quantitative map-based terms. (i) We built scenarios using local stakeholders and experts to define how major land cover classes may change under different sets of drivers; (ii) we formalized these as spatially explicit rules, for example agriculture can only occur on certain soil types; (iii) we created a future land cover map which can then be used to model ecosystem services. We illustrate this for carbon storage in the Eastern Arc Mountains of Tanzania using two scenarios: the first based on sustainable development, the second based on 'business as usual' with continued forest-woodland degradation and poor protection of existing forest reserves. Between 2000 and 2025 4% of carbon stocks were lost under the first scenario compared to a loss of 41% of carbon stocks under the second scenario. Quantifying the impacts of differing future scenarios using the method we document here will be important if payments for ecosystem services are to be used to change policy in order to maintain critical ecosystem services., (Copyright © 2010 Elsevier Ltd. All rights reserved.)

A key assumption underlying any management practice implemented to aid wildlife conservation is that it will have similar effects on target species across the range it is applied. However, this basic assumption is rarely tested. We show that predictors [nearly all associated with agri-environment scheme (AES) options known to affect European birds] had similar effects for 11 bird species on sites with differing farming practice (pastoral vs. mixed farming) or which differed in the density at which the species was found. However, predictors from sites in one geographical region tended to have different effects in other areas suggesting that AES options targeted at a regional scale are more likely to yield beneficial results for farmland birds than options applied uniformly in national schemes. Our study has broad implications for designing conservation strategies at an appropriate scale, which we discuss.

The Urban Regeneration and the Environment Research Programme (URGENT) required a system for cataloguing its datasets and enabling its scientific community to discover what data were available to it. This community was multidisciplinary in nature and therefore needed a range of facilities for searching. Of particular importance were facilities to help those unfamiliar with specialist terminology. To meet these needs, four applications were designed and developed: a Metadata Capture Tool for describing datasets in compliance with the National Geospatial Data Framework (NGDF) standard, a Term Entry Tool for creating an ISO compliant thesaurus, a Thesaurus Builder for merging thesauri and a Search Tool. To encourage users to help in cataloguing data, the capture tools were written as stand alone applications, which users could keep and use to build their own metadatabases. The tools contained export and import facilities that allowed the URGENT Data Centre to build a central database and publish it upon the web. During the development work, it was found necessary to extend the NGDF standard as it could not adequately describe time variant or 3-D atmospheric datasets. The four applications met their design objectives. However, a number of ergonomic issues will need to be addressed if the system is to meet the needs of the much larger up coming programmes. The main challenges will be moving from the NGDF standard to the ISO standard, hence bringing the work into line with the recommendations of the INSPIRE Project, and merging the metadatabase with the scientific database, which enable metadata maintenance to be semi-automated.

This paper explores whether the introduction of an agri-environmental scheme has altered the course of long-term trends in plant species abundance in the Somerset Levels and Moors Environmentally Sensitive Area (ESA), UK. A semi-quantitative approach has been taken which integrates disparate but important historical datasets relating to flora and land management with more contemporary digital information. Species datasets from four time periods throughout the 20th century have been collated within a Geographic Information System and analysed with respect to ancillary data relating to elevation, under-drainage and ESA designation. Qualitative reconstruction of the historical ecology of this internationally important area of lowland wet grassland showed that a steady decline in abundance and extent of key components of the flora had already started by 1900. Analysis of historical under-drainage records dating from 1940s to 1980s showed a clear link between the length of time an area had been under-drained and the subsequent diversity of flora recorded in later surveys. In addition, the relative persistence of the rarer components of the wetland flora between surveys in 1980 and 1997 was related to the spatial pattern of under-drainage on the site since 1940. When overall species diversity was compared before and after ESA designation (1980-1997) there was some evidence of an increase in the number of species present and their spatial extent. The historical dataset provided useful contextual information with respect to species trends and allowed the interpretation of contemporary datasets to be placed within a longer timeframe. This pilot study using 18 species gives some evidence that long-established trends in species decline in the Somerset Levels and Moors ESA are starting to be reversed.