Trevor G. Jones

Madagascar’s Mangroves: Quantifying Nation-Wide and Ecosystem Specific Dynamics, and Detailed Contemporary Mapping of Distinct Ecosystems

Mangrove ecosystems help mitigate climate change, are highly biodiverse, and provide critical goods and services to coastal communities. Despite their importance, anthropogenic activities are rapidly degrading and deforesting mangroves world-wide. Madagascar contains 2% of the world’s mangroves, many of which have undergone or are starting to exhibit signs of widespread degradation and deforestation. Remotely sensed data can be used to quantify mangrove loss and characterize remaining distributions, providing detailed, accurate, timely and updateable information. We use USGS maps produced from Landsat data to calculate nation-wide dynamics for Madagascar’s mangroves from 1990 to 2010, and examine change more closely by partitioning the national distribution in to primary (i.e., >1000 ha) ecosystems; with focus on four Areas of Interest (AOIs): Ambaro-Ambanja Bays (AAB), Mahajamba Bay (MHJ), Tsiribihina Manombolo Delta (TMD) and Bay des Assassins (BdA). Results indicate a nation–wide net-loss of 21% (i.e., 57,359 ha) from 1990 to 2010, with dynamics varying considerably among primary mangrove ecosystems. Given the limitations of national-level maps for certain localized applications (e.g., carbon stock inventories), building on two previous studies for AAB and MHJ, we employ Landsat data to produce detailed, contemporary mangrove maps for TMD and BdA. These contemporary, AOI-specific maps provide improved detail and accuracy over the USGS national-level maps, and are being applied to conservation and restoration initiatives through the Blue Ventures’ Blue Forests programme and WWF Madagascar West Indian Ocean Programme Office’s work in the region.

Assessing the utility of LiDAR to differentiate among vegetation structural classes

Representations of vegetation structure are critical for effective forest ecosystem management. Structure is conventionally characterized using aerial photographs and field measurements; however, such methods are time-consuming and subjective, yielding results that cannot be easily updated and lack the detail required for many management initiatives. In contrast, light detection and ranging data provide highly accurate and detailed height, cover and canopy structure estimates, offering an unparalleled information source for improving conventional methods. Although numerous metrics can be derived from light detection and ranging, three suites common to the literature include height percentiles, canopy height descriptors and canopy volume profiles. This study assessed these three metric types for differentiating among vegetation structural classes in the Southern Gulf Islands, Sidney, BC, Canada. Results indicate all metrics could significantly differentiate (i.e. p ≤ 0.01) between structural classes, but that the number of and types of metrics capable of differentiation decreased with increased structural age and complexity.

Object-Based Canopy Gap Segmentation and Classification: Quantifying the Pros and Cons of Integrating Optical and LiDAR Data

Delineating canopy gaps and quantifying gap characteristics (e.g., size, shape, and dynamics) are essential for understanding regeneration dynamics and understory species diversity in structurally complex forests. Both high spatial resolution optical and light detection and ranging (LiDAR) remote sensing data have been used to identify canopy gaps through object-based image analysis, but few studies have quantified the pros and cons of integrating optical and LiDAR for image segmentation and classification. In this study, we investigate whether the synergistic use of optical and LiDAR data improves segmentation quality and classification accuracy. The segmentation results indicate that the LiDAR-based segmentation best delineates canopy gaps, compared to segmentation with optical data alone, and even the integration of optical and LiDAR data. In contrast, the synergistic use of two datasets provides higher classification accuracy than the independent use of optical or LiDAR (overall accuracy of 80.28% ± 6.16% vs. 68.54% ± 9.03% and 64.51% ± 11.32%, separately). High correlations between segmentation quality and object-based classification accuracy indicate that classification accuracy is largely dependent on segmentation quality in the selected experimental area. The outcome of this study provides valuable insights of the usefulness of data integration into segmentation and classification not only for canopy gap identification but also for many other object-based applications.

Employing ground-based spectroscopy for tree-species differentiation in the Gulf Islands National Park Reserve

Airborne hyperspectral data is a promising tool to map species distribution; however, the large number of input bands can be highly correlated and potentially noisy. Ground-based spectrometer data can identify spectral regions that are optimal for species differentiation, and therefore provide a logical initial step for species mapping endeavours employing airborne hyperspectral data. This study used reflectance collected by an Analytical Spectral Devices (ASD) spectrometer to differentiate between tree species common to the Canadian Gulf Islands. Baseline ASD reflectance and its derivatives were used as input for forward stepwise discriminant analyses to identify wavelengths that minimize within-species variance while maximizing between-species variance. Identified wavelengths were then used as input for normal discriminant analyses, which confirmed through cross-validation classifications that, at the leaf scale, species could be differentiated with an overall accuracy > 98% and individual accuracies > 85% using 40 optimal wavelengths. Accuracies slightly decreased when using derivatives, but only for certain species. Results indicate that wavelengths in the ranges 501–550, 681–740 and 1401–1800 nm exhibited the most significance. The selected bands form the basis of ongoing mapping efforts using airborne hyperspectral imagery.

Describing avifaunal richness with functional and structural bioindicators derived from advanced airborne remotely sensed data

We investigate whether the richness of distinct avian guilds (species grouped together based on similar exploitation of environmental resources) can be described using indicators of ecosystem function and tree species diversity derived from hyperspectral data and/or aspects of vegetation structure derived from lidar. Bird surveys facilitated discriminant analyses to establish which variables best differentiated between guilds. Akaikes Information Criterion (AIC) and generalized linear models (GLMs) were then utilized to develop predictive models. Bioindicators representing foliar water content and tree species diversity were the most useful hyperspectrally derived variables for differentiating between guilds (p < 0.01) and were most often selected for describing richness. Using ecosystem function bioindicators alone, the adjusted coefficient of determination (R 2 adj) of GLMs ranged from 0.32 (generalist) to 0.58 (forest). In contrast, mean under-, mid-, and overstorey cover and mean surface elevation were the most useful structural bioindicators for guild differentiation (p < 0.05) and were most often selected for describing richness. R 2 adj of GLMs built from structural bioindicators alone ranged from 0.19 (generalist) to 0.64 (forest). Overall, structural bioindicators described more variance for open country and forest guilds, whereas functional bioindicators explained more variance for generalist bird species and all guilds considered concurrently. Simultaneously considering functional and structural bioindicators accounted for the most variance in richness (59%) for open country birds; however, combining bioindicator types did not improve upon the best models for generalist and/or forest guilds.

The Mangroves of Ambanja and Ambaro Bays, Northwest Madagascar: Historical Dynamics, Current Status and Deforestation Mitigation Strategy

Madagascar contains Africa’s fourth largest extent of mangroves, representing approximately 2% of the global distribution. Since 1990, more than 20% of Madagascar’s mangrove ecosystems have been heavily degraded or deforested due primarily to increased harvest for charcoal and timber and the expansion of agriculture and aquaculture. Anthropogenic-driven loss is particularly prominent in the north-western Ambanja and Ambaro Bays (AAB). At over 24,000 ha, AAB is one of Madagascar’s largest mangrove ecosystems, including prominent estuaries fed by rivers and streams originating in the country’s highest mountain range. Similar to the national rate, AAB has experienced approximately 20% loss since 1990, driven primarily by over-harvesting for charcoal and timber. Continued loss threatens the livelihoods and wellbeing of thousands of residents who rely on the many goods and services provided by a healthy, relatively intact mangrove ecosystem. To combat this loss, Blue Ventures (BV), in partnership with local communities and the University of Antananarivo, is working to protect, restore and encourage the sustainable use of mangroves. BVs’ Blue Forests project aims to help maintain and diversify local livelihoods and to sustainably manage mangroves and their associated biodiversity in AAB, as well as throughout western Madagascar. This chapter provides an overview of the biophysical characteristics, historic dynamics and current status of the AAB mangrove ecosystem, and mitigation strategies being implemented through BVs’ Blue Forests project.

Phosphorus uptake and availability and short-term seedling growth in three Ontario soils amended with ash and biochar

Abstract: Phosphorus (P) can be a limiting nutrient in terrestrial ecosystems and adding biochar or wood ash can increase plant-available P. We added wood ash and biochar to microcosms containing three acidic Ontario soils planted with red pine or sugar maple seedlings and observed seedling growth responses, as well as amendment-induced changes in soil P pools, microbial P, and enzyme activity. Neither ash nor biochar consistently increased seedling growth; instead sugar maple and red pine seedlings often had opposing responses to the same amendment–soil combination. Overall, these results indicate that it is important to carefully consider both the chemical and physical characteristics of the soil and the ash or biochar, as well as the nutrient requirements of the target tree species, to effectively use these amendments to reduce P limitation.

Rapid assessments and local knowledge reveal high bird diversity in mangroves of north-west Madagascar

Although the importance of regulating and provisioning services provided by mangroves is widely recognised, our understanding of their role in the maintenance of terrestrial biodiversity is patchy globally and largely lacking for many regions, including conservation priorities such as Madagascar. We carried out the first multi-site bird inventory of mangroves in Madagascar and complemented our data with assessments of local knowledge, in order to broaden our knowledge of which species use this habitat. We directly observed 73 species across three sites in Ambanja and Ambaro Bays, while local respondents indicated the presence of 18 additional species: four observed species are globally threatened, while 37 are endemic to Madagascar or the Malagasy region. Over half the species observed are typically terrestrial, of which 22 have not previously been recorded in mangrove habitats in Madagascar. Local knowledge provided a useful complement to our observed data but we are likely to have underestimated total richness; nevertheless, our findings greatly increased our knowledge of mangrove use by Madagascar’s birds. However, further research is required to investigate the functional role of mangroves in the ecology of the observed species and provide insights into the factors influencing mangrove use.