title: Can large taonga bivalves speed up recovery in degraded estuaries?

authors: Prinz, Natalie

abstract: THE QUESTION:
Will there introduction of adult, long-lived bivalves with differing functional traits speed up recovery of degraded soft sediment habitats in estuaries?
RESULTS:
Average bivalve survival after one year was 18% in + tuangi plot sand 59% in + hanikura plots. Sediment oxygen consumption (SOC) after one month was enhanced by 116% in treatments containing tuangi compared to control treatments. After one year those were similar to ambient levels, still showed higher SOC than control plots.

text: Can large taonga bivalves speed up recovery in degraded estuaries? THE QUESTION:
Will there introduction of adult, long-lived bivalves with differing functional traits speed up recovery of degraded soft sediment habitats in estuaries?
RESULTS:
Average bivalve survival after one year was 18% in + tuangi plot sand 59% in + hanikura plots. Sediment oxygen consumption (SOC) after one month was enhanced by 116% in treatments containing tuangi compared to control treatments. After one year those were similar to ambient levels, still showed higher SOC than control plots.

year: 2023

title: Wāhine Māori engagement with literacies

authors: Masters-Awatere, Bridgette

subjects: Literacy

abstract: Wāhine Māori engagement with literacies (2023) is a case study report in collaboration with Te Whakaruruhau. It has been undertaken as part of a larger project, The expression, experience and transcendence of low skills in Aotearoa New Zealand (2019–2024), the aim of which is to provide policy recommendations to improve life-course trajectories and socio-economic outcomes for adults with low literacy and numeracy skills in Aotearoa New Zealand. Broadly speaking, Wāhine Māori engagement with literacy examines the framing and application of literacy measures in contemporary New Zealand culture. More specifically, it is about the lives and learning of wāhine (women) Māori (the indigenous peoples of Aotearoa New Zealand) within that culture and their attitudes towards, and complex relationships with, literacy as it is defined in their own lives and in the current setting. The study aims for a holistic understanding of lived literacies in driving the development of educational policies by public institutions and private groups. Reframing literacy as literacies is posited as a means to empower marginalised groups and to challenge the dominance of the Eurocentric education paradigm. Formal learning in English-language schools cannot be the extent of national literacy standards as it disregards Māori epistemological and ontological realities and can discount wāhine, many of whom may prioritise other modes of literacy. Centring their perspectives will bring about a more culturally inclusive future, one that makes space for the development of emotional and cultural literacies—as well as other forms such as digital, media, visual, financial, and health literacies—alongside the conventional version of literacy that has a monopoly in the present system.

text: Wāhine Māori engagement with literacies Wāhine Māori engagement with literacies (2023) is a case study report in collaboration with Te Whakaruruhau. It has been undertaken as part of a larger project, The expression, experience and transcendence of low skills in Aotearoa New Zealand (2019–2024), the aim of which is to provide policy recommendations to improve life-course trajectories and socio-economic outcomes for adults with low literacy and numeracy skills in Aotearoa New Zealand. Broadly speaking, Wāhine Māori engagement with literacy examines the framing and application of literacy measures in contemporary New Zealand culture. More specifically, it is about the lives and learning of wāhine (women) Māori (the indigenous peoples of Aotearoa New Zealand) within that culture and their attitudes towards, and complex relationships with, literacy as it is defined in their own lives and in the current setting. The study aims for a holistic understanding of lived literacies in driving the development of educational policies by public institutions and private groups. Reframing literacy as literacies is posited as a means to empower marginalised groups and to challenge the dominance of the Eurocentric education paradigm. Formal learning in English-language schools cannot be the extent of national literacy standards as it disregards Māori epistemological and ontological realities and can discount wāhine, many of whom may prioritise other modes of literacy. Centring their perspectives will bring about a more culturally inclusive future, one that makes space for the development of emotional and cultural literacies—as well as other forms such as digital, media, visual, financial, and health literacies—alongside the conventional version of literacy that has a monopoly in the present system.

year: 2023-09-28

title: Forest change mapping using remote sensing and Google Earth Engine

authors: Walawe Durage, Kalpanie Vimarshana Nandasena

subjects: Google Earth Engine

abstract: With advancements in data sources, software, and image analysis techniques, remote sensing has become an efficient method for forest classification. However, access to this technology has been limited for developing countries due to the high cost of high resolution images and analysis software. A potential solution is that NASA and the European Space Agency provide free access to mid-low resolution satellite images. In addition, Google Earth Engine (GEE), a free cloud-based geospatial analysis platform, has allowed researchers from developing countries to conduct research without relying on costly remote sensing software. This study evaluates the suitability of the freely available images and the GEE platform for different forest management applications in Sri Lanka. The research focused on three different scenarios in vegetation mapping: identifying home gardens, monitoring invasive pines, and forest cover mapping in a tropical montane region.
Home garden is an agroforestry class seen in tropical countries often overshadowed by global land cover classifications. This study used a random forest classification algorithm to classify the home garden, utilizing terrain data and Sentinel-2A images as the dataset. The results confirmed that the red band of Sentinel-2 and textural metrics derived from grey-level co-occurrence matrix analysis are effective in identifying home gardens from other forestry classes.
Monitoring the spread of invasive pines is important for forest management in Sri Lanka. This study used Landsat satellite images for the years 2000 and 2021 to detect the exotic Pinus caribaea species invasion of native habitats. By using an image difference technique, this research identified that the extent of these invasive pines had an overall decline over the past 21 years. Further, results showed that broadleaved forests and grasslands located within 100m of the pine plantations’ borders were susceptible to invasion.

In tropical regions, analysing forests can be difficult due to cloud cover. This research also focused on methods to enhance classification accuracy using multiple data sources: Sentinel-1, Sentinel-2, PALSAR-2, and elevation. Six different methods were tested. It was found that combining radar data with optical and topographical data improved vegetation classification accuracy. In addition, feature importance analysis using the random forest algorithm indicated that radar data plays a significant role in tropical land use classification.
The three case studies used in this research demonstrate that GEE and the freely available mid-low resolution satellite images make the application of remote sensing in Sri Lanka a viable solution for the monitoring and mapping of landcover.

text: Forest change mapping using remote sensing and Google Earth Engine With advancements in data sources, software, and image analysis techniques, remote sensing has become an efficient method for forest classification. However, access to this technology has been limited for developing countries due to the high cost of high resolution images and analysis software. A potential solution is that NASA and the European Space Agency provide free access to mid-low resolution satellite images. In addition, Google Earth Engine (GEE), a free cloud-based geospatial analysis platform, has allowed researchers from developing countries to conduct research without relying on costly remote sensing software. This study evaluates the suitability of the freely available images and the GEE platform for different forest management applications in Sri Lanka. The research focused on three different scenarios in vegetation mapping: identifying home gardens, monitoring invasive pines, and forest cover mapping in a tropical montane region.
Home garden is an agroforestry class seen in tropical countries often overshadowed by global land cover classifications. This study used a random forest classification algorithm to classify the home garden, utilizing terrain data and Sentinel-2A images as the dataset. The results confirmed that the red band of Sentinel-2 and textural metrics derived from grey-level co-occurrence matrix analysis are effective in identifying home gardens from other forestry classes.
Monitoring the spread of invasive pines is important for forest management in Sri Lanka. This study used Landsat satellite images for the years 2000 and 2021 to detect the exotic Pinus caribaea species invasion of native habitats. By using an image difference technique, this research identified that the extent of these invasive pines had an overall decline over the past 21 years. Further, results showed that broadleaved forests and grasslands located within 100m of the pine plantations’ borders were susceptible to invasion.

In tropical regions, analysing forests can be difficult due to cloud cover. This research also focused on methods to enhance classification accuracy using multiple data sources: Sentinel-1, Sentinel-2, PALSAR-2, and elevation. Six different methods were tested. It was found that combining radar data with optical and topographical data improved vegetation classification accuracy. In addition, feature importance analysis using the random forest algorithm indicated that radar data plays a significant role in tropical land use classification.
The three case studies used in this research demonstrate that GEE and the freely available mid-low resolution satellite images make the application of remote sensing in Sri Lanka a viable solution for the monitoring and mapping of landcover.

year: 2023