The work reported here aimed to provide a comprehensive database of core information to support the development and validation of process-based models of resource capture and growth in the semi-arid overstorey agroforestry systems. Intensive field studies were carried out in Kenya over a 30 month period and the results obtained were combined with data from a previous project to produce a dataset spanning a 4.5 year period. This dataset was then used to verify output from the HyPAR model. Allometric procedures developed from the pipe model theory (Lott et al., 1998) were used to estimate tree growth non-destructively throughout the observation period. Significant differences in tree size between the sole (Td) and dispersed agroforestry (CTd) treatments were established during the first 130 days after planting, probably because of competition with the associated crops. The above-ground biomass and trunk length and taper characteristics of the CTd trees remained inferior to those of Td trees throughout the observation period, seriously undermining the economic potential of this agroforestry system. Comparison of output from the HyPAR model against the observed results provided information pertinent to future model development. The model proved to be insufficiently flexible for end-users wishing to simulate the growth of different crops during the same simulation cycle, or to use model output to aid management decisions such as the timing of pruning. The allometric procedures used by the model to estimate canopy size from trunk diameter at breast height also proved incapable of accounting for reductions in canopy size resulting from pruning. Estimates of tree height are rounded to the nearest metre within the model, representing a potentially serious loss of resolution when annual increments often do not exceed 2 m. In addition, the numerous parameters required by the model would force most end-users to rely heavily on published information, potentially undermining the reliability of simulations.
Tag: data collection
Timber yield from smallholder agroforestry systems in Nicaragua and Honduras
The importance of tropical timber is increasing worldwide. However, the timber supply of tropical forests has been greatly impacted by growing deforestation associated with complex and restrictive timber harvest laws. In Central America, as well as in other developing regions, reforestation programs have often fallen short of expectations. In these cases, agroforestry proves to be a useful strategy for providing tropical timber supplies for smallholder farmers, rural development and environmental services. Timber yields and their potential revenues in four types of agroforestry systems (silvopastoral, coffee, cocoa and living fences) were researched in Nicaragua and Honduras. The results suggest that smallholder timber production in agroforestry systems is a profitable activity despite lower market prices than commanded by timber from forests. The net value from timber sales represents 11–49 % of the total revenue from agroforestry systems. However, this amount could be 58 % higher if farmers were able to improve management practices. Encouraging the knowledge and adoption of silvicultural practices in agroforestry systems is important to increasing timber revenues among smallholder farmers in Central America. © 2015, Springer Science+Business Media Dordrecht.
Willingness to pay for market information received by mobile phone among smallholder pineapple farmers in Benin
Access to up-to-date information on market prices and quality requirements remains a key issue for smallholder farmers’ access to high income markets. The aim of this chapter is to explore the problem of information asymmetry between farmers and buyers in the pineapple supply chain in Benin, and to assess strategies using mobile phones to overcome this problem. Data was collected from an exploratory case study in Ghana and a survey with 285 farmers in Benin. Results show that farmers face market information asymmetry leading to lower prices and income. In Ghana, market price alerts through mobile phones messaging allowed decreasing transaction costs for farmers. In Benin, farmers expressed a willingness to pay a premium of up to US$ 2.5 per month to get market price and quality information. Econometric analysis showed that decisive factors for the size of the premium include farm location, market channel, profit margin, contact with agricultural extension services, and technical support from buyers.
Assessing the adoption potential of agroforestry practices: ICRAF’s experiences in sub-saharan African
This paper describes the participatory approach and methods that ICRAF and partner-institutions use of assessing the adoption potential of agroforestry practices, that is, their biophysical performance, profitability, and acceptability to farmers. The information required for assessing adoption potential is presented. Three types of on-farm trials– researcher-designed and managed, researcher-designed and farmer-managed, and farmer-designed and managed — are examined and their relative suitability for different objectives is assessed. Next, methods for assessing adoption potential are presented, using seven case studies from four study areas in sub-Saharan Africa. Finally, an example is presented of comparing the adoption potential of improved tree fallows across sites for assessing the boundary conditions of the practice, that is, the circumstances that determine whether the practice is likely to be adopted. Assessments of adoption potential improve the efficiency of the technology development and dissemination process, help document the progress made in disseminating new practices, demonstrate the impact of investing in technology development, facilitate inter-institutional cooperation, and help to identify the factors contributing to successful technology development programs as well as the constraints limiting the achievements.
Using n-dimensional hypervolumes for species distribution modelling: A response to Qiao et al. (†)
Hypervolume approaches are used to quantify functional diversity and quantify environmental niches for species distribution modelling. Recently, Qiao et al. (2016) criticized our geometrical kernel density estimation (KDE) method for measuring hypervolumes. They used a simulation analysis to argue that the method yields high error rates and makes biased estimates of fundamental niches. Here, we show that (a) KDE output depends in useful ways on dataset size and bias, (b) other species distribution modelling methods make equally stringent but different assumptions about dataset bias, (c) simulation results presented by Qiao et al. (2016) were incorrect, with revised analyses showing performance comparable to other methods, and (d) hypervolume methods are more general than KDE and have other benefits for niche modelling. As a result, our KDE method remains a promising tool for species distribution modelling.
Digital knowledge of Kenyan succulent flora and priorities for future inventory and documentation
Biodiversity inventory in Kenya has been ongoing for about a century and a half, coinciding with the arrival of naturalists from Europe, America, and elsewhere outside Africa. Since the first collections in the mid-to-late 1800s, there has been a steady increase of plant surveys, frequency of inventory, and discovery of new species that have considerably increased knowledge of faunal and floristic elements. However, as in all other countries, such historical biological collection activities are more often than not, ad hoc, resulting in gaps in knowledge of species and their habitats. While Kenya is relatively rich botanically, with a succulent flora of about 428 taxa, it is apparent that the list is understated owing to, among other factors, difficulty of preparing herbarium material and restricted access to some sites. This study investigated completeness of geographic knowledge of succulent plants in Kenya, with the aim of establishing species distribution patterns and identifying gaps that will guide and justify priority setting for future work on the group. Species data were filtered from the general BRAHMS database at the East African Herbarium and cleaned via an iterative series of inspections and visualizations designed to detect and document inconsistencies in taxonomic concepts, geographic coordinates, and dates of collection. Eight grid squares fulfilled criteria for completeness of inventory: one in the city of Mombasa, one in the Kulal–Nyiro complex, one in Garissa, one in Baringo, and four grid squares in the Nairobi–Nakuru–Laikipia area. Poorly-known areas, mostly in the west, north, and north-eastern regions of the country, were extremely isolated from well-known sites, both geographically and environmentally. These localities should be prioritised for future inventory as they are likely to yield species new to science, species new to the national flora, and/or contribute new knowledge on habitats. To avoid inconsistencies and data leakage, biodiversity inventory and documentation needs streamlining to generate standardised metadata that should be digitised to enhance access and synthesis.
Community-based monitoring, assessment and management of data-limited inland fish stocks in North Rupununi, Guyana
Inland fisheries are important for food security in communities around the world, especially in developing countries. In North Rupununi, Guyana, the state of exploited stocks is poorly understood, and fishery monitoring and assessment are challenging because diverse fishing gears and target species are distributed across a heterogeneous landscape. This complexity created an opportunity for community-based monitoring (CBM) to support data-limited assessment. Standardised CBM was established for the North Rupununi as part of a new inland fisheries management plan initiated by indigenous community groups with support from the government. Quantitative length-based assessments undertaken for target stocks suggested moderate levels of exploitation consistent with local perception. Our study highlights that local experts and community participants with different levels of training can collect accurate biodiversity data. Further development of CBM is important in North Rupununi. We recommend using local ecological knowledge indicators to track spatial and temporal patterns in exploitation and fish stock status.
Citizen science and scaling the use of the Regreening App
This brief shares key learnings and insights into the success of the Regreening App through citizen science and stakeholder engagement.
Manual on general management principles for breeding seed orchards (BSOs). Part I: Data collection and assessment of traits
Breeding seed orchards (BSOs) or seedling seed orchards (SSOs) comprise seedlings from selected trees in different provenances, but could also include seed lots from provenances. A family from a selected tree is known as an open pollinated family (OP-family). BSOs aim to provide improved germplasm after selection, but also serve as test sites of different seed sources.
Glasgow forest declaration needs new modes of data ownership
Commitments made at COP26 in Glasgow shine a spotlight on how changes in global tree cover are defined, monitored and accounted for. Signed by 141 countries, the Glasgow Leaders’ Declaration on Forests and Land Use1 commits signatories to collectively “halt and reverse forest loss and land degradation by 2030 while delivering sustainable development”. This declaration recognizes that land use and land management are responsible for an estimated 23% of global anthropogenic greenhouse gas emissions and that any plausible scenario to limit global warming to 1.5 °C by 2100 must maintain and expand tree cover2. It also recognizes that sustainable land use requires transformative international-to-local action covering relevant global production and consumption systems while simultaneously empowering smallholders, Indigenous peoples and local communities2. However, timely and effective monitoring of such transformative actions requires improved, open and shared data and new collective modes of ownership for forest information.