The lemur diversity of the Fiherenana-Manombo Complex, southwest Madagascar

We conducted the first comprehensive lemur survey of the Fiherenana - Manombo Complex (Atsimo-Andrefana Region), site of PK32-Ranobe, a new protected area within the Madagascar Protected Area System. Our cross-seasonal surveys of three sites revealed the presence of eight lemur species representing seven genera and four families, of which three are diurnal and five are nocturnal species. Six species were only recorded in the riparian and transitional forests of the Fiherenana and Manombo river valleys, while the spiny thicket at Ranobe contains only Microcebus (two species), all larger species having been extirpated by hunting in recent years. Two of our records (Mirza coquereli and Cheirogaleus sp.) represent new locality records or range extensions, but we failed to record one species (Phaner pallescens) expected to occur in the area, and question the literature supporting its presence south of the Manombo river. Our findings highlight the importance of the Fiherenana-Manombo Complex for the conservation of lemurs in southwest Madagascar, but also show that PK32 - Ranobe fails to protect the full lemur diversity of the Complex. The protected area does not include the riparian forests of the Manombo and Fiherenana rivers, and at least three lemur species are therefore unprotected. We strongly support the proposed extension of the protected area to include these riparian forests as well as other important habitats for locally endemic bird and reptile taxa.RÉSUMÉ La zone du Complexe Fiherenana - Manombo (Région d’Atsimo- Andrefana), site de PK32-Ranobe, une nouvelle aire protégée dans le Système des Aires Protégées de Madagascar (SAPM), a fait l’objet d’un premier inventaire de lémuriens. Nos prospections dans trois sites à différentes saisons ont révélé la présence de huit espèces de lémuriens représentés dans sept genres et trois familles, dont trois sont des espèces diurnes et cinq sont des espèces nocturnes. Nous n’avons pas pu identifier l’espèce du genre Lepilemur ni celle du genre Cheirogaleus à défaut de disposer de spécimens. Six espèces ne se trouvaient que dans les forêts riveraines et les forêts de transition des vallées des fleuves Fiherenana et Manombo. Le fourré épineux de Ranobe n’abrite que des Microcebus (deux espèces), toutes les espèces plus grandes ayant déjà été exterminées par la chasse au cours des dernières années. Nos estimations de densité indiquent que la population des Microcebus est deux fois plus importante dans le fourré épineux que dans la forêt riveraine (1,078 individus / km² vs. 546 individus / km²). Nous avons estimé la densité d’Eulemur rufus à 40 groupes / km² dans la vallée du Fiherenana, mais nos transects ne nous ont pas permis d’obtenir des estimations fiables pour les densités de Lemur catta et de Propithecus verreauxi. Deux des espèces répertoriées (Mirza coquereli et Cheirogaleus sp.) représentent de nouvelles observations pour la zone ou des extensions de leurs aires de répartition connues, mais nous n’avons pas pu trouver l’espèce Phaner pallescens qui devait être présente dans la zone et nous émettons des doutes portant sur les références publiées rapportant la présence de l’espèce au sud du fleuve Manombo. Nos résultats mettent en exergue l’importance du Complexe Fiherenana - Manombo pour la conservation des lémuriens dans le sud-ouest de Madagascar, mais ils indiquent que l’aire protégée de PK32 - Ranobe ne protège pas la diversité complète des lémuriens du Complexe. Les forêts riveraines des fleuves Fiherenana et Manombo ne sont pas incluses dans l’aire protégée de sorte qu’au moins trois espèces de lémuriens ne bénéficient alors d’aucune protection. Compte tenu des objectifs du SAPM et plus particulièrement de l’Objectif 1, à savoir ‘Conserver l’ensemble de la biodiversité unique de Madagascar’, nous estimons que la nouvelle aire protégée du PK32-Ranobe n’atteint pas ces objectifs et nous appuyons les efforts des promoteurs afin de re-délimiter l’aire protégée pour inclure les forêts riveraines ainsi que d’autres habitats importants pour la conservation des oiseaux et des reptiles localement endémiques

Land cover change and carbon emissions over 100 years in an African biodiversity hotspot

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 pre-satellite era. Here we quantify the LULCC history across the 33.9 million ha watershed of Tanzania's Eastern Arc Mountains, using geo-referenced and digitised 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 five-fold 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 three-fold 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 is 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. This article is protected by copyright. All rights reserved

Correction to: Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot

Abstract 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

Observations of sea turtles nesting on Misali islan, Pemba

A nest-recording programme has collected data over five years from turtles nesting on Misali Island, off the West coast of Pemba, Tanzania. Five species of sea turtle are known to occur in Zanzibar waters, two of these species nested regularly on the island, with green turtle nests outnumbering hawksbill turtle nests by a factor of roughly 3 to 1. The highest number of nests in one year was recorded in 1999 (66) with as few as 8 in 2001. Most green turtles nested in April whilst most hawksbills nested in March. 58% of nests were found on a single beach (Mpapaini). The hatching success of nests over the study period exceeded 70%. Data indicate that Misali Island is an important nesting site within Zanzibar and also suggest that it may be of East African regional importance.Journal of East African Natural History Vol. 92 (1&2) 2003: pp. 127-13

Can distribution models help refine inventory-based estimates of conservation priority? : A case study in the Eastern Arc forests of Tanzania and Kenya

Aim Data shortages mean that conservation priorities can be highly sensitive to historical patterns of exploration. Here, we investigate the potential of regionally focussed species distribution models to elucidate fine-scale patterns of richness, rarity and endemism. Location Eastern Arc Mountains, Tanzania and Kenya. Methods Generalized additive models and land cover data are used to estimate the distributions of 452 forest plant taxa (trees, lianas, shrubs and herbs). Presence records from a newly compiled database are regressed against environmental variables in a stepwise multimodel. Estimates of occurrence in forest patches are collated across target groups and analysed alongside inventory-based estimates of conservation priority. Results Predicted richness is higher than observed richness, with the biggest disparities in regions that have had the least research. North Pare and Nguu in particular are predicted to be more important than the inventory data suggest. Environmental conditions in parts of Nguru could support as many range-restricted and endemic taxa as Uluguru, although realized niches are subject to unknown colonization histories. Concentrations of rare plants are especially high in the Usambaras, a pattern mediated in models by moisture indices, whilst overall richness is better explained by temperature gradients. Tree data dominate the botanical inventory; we find that priorities based on other growth forms might favour the mountains in a different order. Main conclusions Distribution models can provide conservation planning with high-resolution estimates of richness in well-researched areas, and predictive estimates of conservation importance elsewhere. Spatial and taxonomic biases in the data are essential considerations, as is the spatial scale used for models. We caution that predictive estimates are most uncertain for the species of highest conservation concern, and advocate using models and targeted field assessments iteratively to refine our understanding of which areas should be prioritised for conservation

Towards regional, error-bounded landscape carbon storage estimates for data-deficient areas of the world

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.<br/

Conservation and the botanist effect

Over the last few decades, resources for descriptive taxonomy and biodiversity inventories have substantially declined, and they are also globally unequally distributed. This could result in an overall decline in the quality of biodiversity data as well as geographic biases, reducing the utility and reliability of inventories. We tested this hypothesis with tropical tree records (n = 24,024) collected from the Eastern Arc Mountains, Tanzania, between 1980 and 2007 by 13 botanists, whose collections represent 80% of the total plant records for this region. Our results show that botanists with practical training in tropical plant identification record both more species and more species of conservation concern (20 more species, two more endemic and one more threatened species per 250 specimens) than untrained botanists. Training and the number of person-days in the field explained 96% of the variation in the numbers of species found, and training was the most important predictor for explaining recorded numbers of threatened and endemic species. Data quality was related to available facilities, with good herbarium access significantly reducing the proportions of misidentifications and misspellings. Our analysis suggests that it may be necessary to account for recorder training when comparing diversity across sites, particularly when assessing numbers of rare and endemic species, and for global data portals to provide such information. We also suggest that greater investment in the training of botanists and in the provisioning of good facilities would substantially increase recording efficiency and data reliability, thereby improving conservation planning and implementation on the ground

Quantifying and understanding carbon storage and sequestration within the Eastern Arc Mountains of Tanzania, a tropical biodiversity hotspot

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