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Understanding the impacts of climate change is critical for improving the conservation and management of ecosystems worldwide. Ecosystems vary along a precipitation and temperature gradient, ranging from tropical jungles to arid deserts. The Great Basin is a semi-arid eco-region that is found within the western United States. Plant communities within the Great Basin range from sagebrush valleys to sub-alpine conifer forests found at high elevation areas. It is predicted that the Great Basin will experience prolonged periods of drought, more intense fires, and greater variability in average annual and monthly precipitation, all in response to changes in climate patterns. At the lower elevations, sagebrush communities are expected to experience less suitable habitat conditions, however, less is understood about vegetation response at upper elevations. Understanding forest composition and structure at these upper elevations within the Great Basin will help us better understand potential impacts from climate change. In chapter 1, we characterized Pinus longaeva (Great Basin bristlecone pine D.K. Bailey) forest structure and composition. We mapped this tree species distribution and characterized forest structure and composition using a sampling protocol that included both biophysical variables and individual tree characteristics. We collected data from 69 mixed and homogenous P. longaeva stands found within the Great Basin and Colorado Plateau. Results suggest that P. longaeva forest structure and composition exhibit high structural variability in tree characteristic measurements like density, basal area, growth rate, age, and in biophysical variables such as substrate type, slope, aspect, elevation, average monthly temperature and precipitation, latitude, and longitude. This study also found that variability in forest composition and structure in P. longaeva forests allows for greater flexibility in the breadth of life-history strategies and probable resiliency to climate change. In chapter 2 we used remote sensing images with high spatial resolution to identify 685 unique P. longaeva stands on 42 mountain ranges. Pinus longaeva was found on the White Mountains on the western edge of the Great Basin to the Colorado Plateau's Henry Mountain and West Tavaputs Plateau in the East, and from the Spring Mountains in the South to the Ruby and Spruce Mountains in the North. Stands covered 113,886 ha across the geographic distribution. A comparison between our maps and those produced by David Charlet found a total of 36% overlap of P. longaeva. We mapped 58 unique stands that the control dataset lacked and 11 stands that we did not include. We believe that this is the most comprehensive P. longaeva distribution map created to date.

Introdução: As diversas armadilhas apresentam rendimento diferenciado na captura, havendo a necessidade de buscar instrumentos que amostrem porções representativas das populações de mosquitos. Levanta-se a hipótese de que as armadilhas Mosquito Magnet Independence e CDC com CO2+Lurex3 sejam mais eficazes na captura de culicídeos do que a armadilha CDC luminosa. Objetivos: Avaliar a eficácia das armadilhas Mosquito Magnet Independence e CDC+CO2+Lurex3, em relação à CDC-luminosa, para a captura de culicídeos adultos em área agrícola na Fazenda Experimental em Pariquera-Açu, Vale do Ribeira, São Paulo, Brasil. Material e Métodos: Capturas mensais, das 15h00 às 21h00, por meio do delineamento em quadrado latino 3X3, no período de dezembro/2010 a novembro/2011. Perfis de diversidade de Rényi e índices de riqueza, dominância, diversidade, equabilidade e similaridade foram estimados para cada armadilha para compará-las. Resultados: Capturou-se 6.055 de 70 espécies e 12 gêneros. A CDC-luminosa amostrou 990 indivíduos de 42 espécies e 10 gêneros,a CDC+CO2+lurex31.419 indivíduos em 41 espécies e 10 gêneros e a Mosquito Magnet 3151 indivíduos de 46 espécies e 11 gêneros. A riqueza, pelo índice de Margalef e Perfil de Rényi, não apresentou diferença estatística para nenhuma armadilha no período dez/mai. A Mosquito Magnet obteve maior rendimento na mensuração da diversidade, segundos os índices de Shannon e Simpson, observados no perfil de Rényi. A dominância, pelo índice de Berger-Parker isolado,foi maior na Mosquito Magnet do que nas demais, nos dois períodos de capturas. O perfil de Rényi não apontou diferença significante para dominância. Índice de Pielou não mostrou significância em relação à CDC-luminosa para nenhuma das armadilhas nos dois períodos avaliados. Índices de Jaccard e Sorensen apontaram maior similaridade na composição de espécies entre a Mosquito Magnet e CDC+CO2+lurex3. Conclusões: A Mosquito Magnet Independence e CDC+CO2+Lurex3 apresentaram rendimento semelhante, nos meses mais frios e secos do ano. A utilização dessas armadilhas para a captura de determinados táxons pode ser importante ponto na estratégia de vigilância de espécies vetoras. Estudos com maior esforço amostral devem ser realizados para avaliar o rendimento das armadilhas Mosquito Magnet Independence e CDC+CO2 +lurex3 em áreas de ambiente alterado de Floresta Atlântica. / Introduction: The several traps have different performance in sampling mosquitoes,with the need to seek that capture representative portions of mosquito population. Formulate the hypothesis that the Mosquito Magnet trap and CDC+CO2+lurex3 are more effective in catching mosquitoes than the CDC light trap. Objectives: To evaluate the effectiveness the Mosquito Magnet Independence and CDC+CO2+lurex3 in relation to CDC light trap, to catching adult mosquitoes in the agricultural area at the Experimental Station in Pariquera-Açu, Vale do Ribeira, São Paulo, Brazil. Methods: Monthly captures, from 03:00pm-09:00pm, through the 3X3 Latin square from the December 2010 to November 2011. Rényi diversity profiles and indexes of the richness, dominance, diversity, evenness and similarity were estimated for each trap to compare them. Results: Were captured 6055 mosquitoes of the 70 species and 12 genera. CDC light traps sampled 990 specimens of 42 species and 10 genera, the CDC+CO2+lurex3 sampled 1419 specimens in 41 species and 10 genera and 3151 specimens were captured in the Mosquito Magnet belonging to 46 species and 11 genera. The richness, by the Margalef index on profile Rényi, showed no statistical difference for any trap in the period Dez/Mai. The Mosquito Magnet trap obtained higher yield in the measurement of diversity, according indexes of Shannon and Simpson, seen in profile Rényi. The dominance, by Berger-Parker index isolated, was higher in the Mosquito Magnet than in the other traps in both periods of captures. The profile Rényi showed no significant difference for dominance. Pielou index was not significant in relation to CDC light trap for any of the periods. Jaccard and Sorensen indexes showed greater similarity in composition of species between the CDC+CO2+lurex3 and Mosquito Magnet. Conclusions: The Mosquito Magnet Independence and CDC+CO2+ Lurex3 showed similar performance in colder and drier months of the year. The use of these traps to capture certain taxa can be important point in the surveillance approach vector species. Studies with greater sampling effort should be made to evaluate the performance of the Mosquito Magnet Independence and CDC+CO +lurex3 traps changed environment in areas of Atlantic Forest.

Submitted by Rosivalda Pereira (mrs.pereira@ufma.br) on 2017-08-14T19:19:25Z No. of bitstreams: 1 SimaraRocha.pdf: 3984461 bytes, checksum: 04243e2b6ab9b63b0b73e436ebc9fc23 (MD5) / Made available in DSpace on 2017-08-14T19:19:25Z (GMT). No. of bitstreams: 1 SimaraRocha.pdf: 3984461 bytes, checksum: 04243e2b6ab9b63b0b73e436ebc9fc23 (MD5) Previous issue date: 2014-05-22 / Breast cancer is the second most frequent type of cancer in the world, being more common among women, and representing 22% of the new cases every year. A precocious diagnosis improves the chances of a successful treatment. Mammography is one of the best ways to precocious detection of non-palpable tumor that could lead to a breast cancer. However, it is well known that this exam's sensibility may vary a lot. This is due to factors such as: the specialist's experience, patient's age and the quality of the exam image. The use of Image Processing and Machine Learning techniques has becoming a strong contribution to the specialist diagnosis task. Thes thesis proposes a methodology to discriminate patterns of malignancy and benignity of masses in mammographic images using texture analysis and machine learning. For this purpose, the methodology combines structural and statistical approaches for the analysis of texture regions extracted from mammograms. Furthermore, this research extends the concept of Diversity Index through the use of species co-occurrence information in order to increase the efficiency of extraction of texture features. The techniques used are Local Binary Pattern, Ripley's K function and diversity indexes (Shannon, Mcintosh, Simpson, Gleason and Menhinick indexes). The extracted texture is classified using a Support Vector Machine into benign and malignant classes. The best results obrained with Ripley's K function were 92,20% of accuracy, 92,96% of sensibility, 91,26% of specificity, 10.63 of likelihood positive ratio, 0,07 of likelihood negative ratio and an area under ROC curve Az of 0,92. / O câncer de mama é o segundo tipo de câncer mais frequente no mundo, sendo mais comum entre as mulheres, respondendo por 22% dos casos novos a cada ano. Quanto mais precocemente for diagnosticado, maiores serão as chances de se realizar um tratamento bem sucedido. A mamogra fia é uma das formas de detectar os tumores não palpáveis que causam câncer de mama. Todavia, sabe-se que a sensibilidade desse exame pode variar bastante, devido a fatores como: a experiência do especialista, a idade do paciente e a qualidade das imagens obtidas no exame. O uso de técnicas de Processamento de Imagens e Aprendizagem de Máquina tem contribuído, cada vez mais, para auxiliar os especialistas na realização de diagnósticos mais precisos. Esta tese propõe uma metodologia para discriminar padrões de malignidade e benignidade de massas em imagens de mamogra fias, utilizando análise de textura e aprendizado de máquina. Para tanto, a metodologia combina as abordagens estrutural e estatística para a análise de textura de regiões extraídas das mamogra fias. Além disso, esta pesquisa amplia o conceito de Índice de Diversidade, através do uso da informação de co-ocorrência de espécies, com o propósito de aumentar a e ficiência da extração de características de textura. Assim, são usadas as técnicas de Local Binary Pattern, Função K de Ripley e os Índices de Shannon, Mcintosh, Simpson, Gleason e de Menhinick. Por fi m, a textura extraída e classi ficada utilizando a Máquina de Vetores de Suporte, visando diferenciar as massas malignas das benignas. O melhor resultado foi obtido usando a função K de Ripley com 92,20% de acurácia, 92,96% de sensibilidade, 91,26% de especi cidade, 10,63 de razão de probabilidade positiva, 0,07% de razão de probabilidade negativa e uma área sob a curva ROC (Az) de 0,92.

Submitted by Maria Aparecida (cidazen@gmail.com) on 2017-08-21T14:59:23Z No. of bitstreams: 1 Andre Pereira.pdf: 3105574 bytes, checksum: 06e2fe68d48179a3c62a46e447b82513 (MD5) / Made available in DSpace on 2017-08-21T14:59:23Z (GMT). No. of bitstreams: 1 Andre Pereira.pdf: 3105574 bytes, checksum: 06e2fe68d48179a3c62a46e447b82513 (MD5) Previous issue date: 2009-02-20 / Breast cancer is one of the major causes of mortality among women throughout the world. Presently, the analysis of breast radiography is the most used method to early detection of this kind of cancer. It enables the identification of anomalies at their initial stage, which is a fundamental factor for success in the treatment. The sensitivity of this kind of exam, although, depends on several factors, such as the size and the location of the abnormalities, density of the breast tissue, quality of the technical resources and radiologist's ability. This work presents a methodology that uses the K-Means clustering algorithm and the Template Matching technique for segmentation of suspicious regions. Next, geometry and texture features are extracted from each of these regions, being the texture described by the Simpson's Diversity Index, a statistic used in Ecology to measure the biodiversity of an ecosystem. Finally, this information is submitted to a Support Vector Machine so that the suspicious regions are classified into masses and non-masses. The methodology was tested with 650 mammographic images from the DDSM database, achieving 83.94% of accuracy, 83.24% of sensibility and 84.14% of specificity in average. / O câncer de mama é uma das maiores causas de mortalidade entre as mulheres no mundo todo. Atualmente, a análise da radiografia da mama é o recurso mais utilizado na detecção precoce desse tipo de câncer, pois possibilita a identificação de anomalias em sua fase inicial, fator fundamental para o sucesso do tratamento. A sensibilidade desse tipo de exame, no entanto, depende de diversos fatores, tais como tamanho e localização das anomalias, densidade do tecido mamário, qualidade dos recursos técnicos e habilidade do radiologista. Este trabalho apresenta uma metodologia para detecção de massas em imagens digitais de mamografias que poderá auxiliar o especialista em sua análise. O método proposto utiliza o algoritmo de agrupamento K-Means e a técnica de Template Matching para segmentar as regiões suspeitas de conterem massas. Em seguida, medidas de geometria e textura são extraídas de cada uma dessas regiões, sendo a textura descrita através do Índice de Diversidade de Simpson, uma estatística usada na Ecologia para mensurar a biodiversidade de um ecossistema. Finalmente, essas informações são submetidas a uma Máquina de Vetores de Suporte para que as regiões suspeitas sejam classificadas em massas ou não massas. A metodologia foi testada com 650 imagens mamográficas obtidas da base de dados DDSM, atingindo 83,94% de acurácia, 83,24% de sensibilidade, e 84,14% de especificidade em média.

Introdução: As diversas armadilhas apresentam rendimento diferenciado na captura, havendo a necessidade de buscar instrumentos que amostrem porções representativas das populações de mosquitos. Levanta-se a hipótese de que as armadilhas Mosquito Magnet Independence e CDC com CO2+Lurex3 sejam mais eficazes na captura de culicídeos do que a armadilha CDC luminosa. Objetivos: Avaliar a eficácia das armadilhas Mosquito Magnet Independence e CDC+CO2+Lurex3, em relação à CDC-luminosa, para a captura de culicídeos adultos em área agrícola na Fazenda Experimental em Pariquera-Açu, Vale do Ribeira, São Paulo, Brasil. Material e Métodos: Capturas mensais, das 15h00 às 21h00, por meio do delineamento em quadrado latino 3X3, no período de dezembro/2010 a novembro/2011. Perfis de diversidade de Rényi e índices de riqueza, dominância, diversidade, equabilidade e similaridade foram estimados para cada armadilha para compará-las. Resultados: Capturou-se 6.055 de 70 espécies e 12 gêneros. A CDC-luminosa amostrou 990 indivíduos de 42 espécies e 10 gêneros,a CDC+CO2+lurex31.419 indivíduos em 41 espécies e 10 gêneros e a Mosquito Magnet 3151 indivíduos de 46 espécies e 11 gêneros. A riqueza, pelo índice de Margalef e Perfil de Rényi, não apresentou diferença estatística para nenhuma armadilha no período dez/mai. A Mosquito Magnet obteve maior rendimento na mensuração da diversidade, segundos os índices de Shannon e Simpson, observados no perfil de Rényi. A dominância, pelo índice de Berger-Parker isolado,foi maior na Mosquito Magnet do que nas demais, nos dois períodos de capturas. O perfil de Rényi não apontou diferença significante para dominância. Índice de Pielou não mostrou significância em relação à CDC-luminosa para nenhuma das armadilhas nos dois períodos avaliados. Índices de Jaccard e Sorensen apontaram maior similaridade na composição de espécies entre a Mosquito Magnet e CDC+CO2+lurex3. Conclusões: A Mosquito Magnet Independence e CDC+CO2+Lurex3 apresentaram rendimento semelhante, nos meses mais frios e secos do ano. A utilização dessas armadilhas para a captura de determinados táxons pode ser importante ponto na estratégia de vigilância de espécies vetoras. Estudos com maior esforço amostral devem ser realizados para avaliar o rendimento das armadilhas Mosquito Magnet Independence e CDC+CO2 +lurex3 em áreas de ambiente alterado de Floresta Atlântica. / Introduction: The several traps have different performance in sampling mosquitoes,with the need to seek that capture representative portions of mosquito population. Formulate the hypothesis that the Mosquito Magnet trap and CDC+CO2+lurex3 are more effective in catching mosquitoes than the CDC light trap. Objectives: To evaluate the effectiveness the Mosquito Magnet Independence and CDC+CO2+lurex3 in relation to CDC light trap, to catching adult mosquitoes in the agricultural area at the Experimental Station in Pariquera-Açu, Vale do Ribeira, São Paulo, Brazil. Methods: Monthly captures, from 03:00pm-09:00pm, through the 3X3 Latin square from the December 2010 to November 2011. Rényi diversity profiles and indexes of the richness, dominance, diversity, evenness and similarity were estimated for each trap to compare them. Results: Were captured 6055 mosquitoes of the 70 species and 12 genera. CDC light traps sampled 990 specimens of 42 species and 10 genera, the CDC+CO2+lurex3 sampled 1419 specimens in 41 species and 10 genera and 3151 specimens were captured in the Mosquito Magnet belonging to 46 species and 11 genera. The richness, by the Margalef index on profile Rényi, showed no statistical difference for any trap in the period Dez/Mai. The Mosquito Magnet trap obtained higher yield in the measurement of diversity, according indexes of Shannon and Simpson, seen in profile Rényi. The dominance, by Berger-Parker index isolated, was higher in the Mosquito Magnet than in the other traps in both periods of captures. The profile Rényi showed no significant difference for dominance. Pielou index was not significant in relation to CDC light trap for any of the periods. Jaccard and Sorensen indexes showed greater similarity in composition of species between the CDC+CO2+lurex3 and Mosquito Magnet. Conclusions: The Mosquito Magnet Independence and CDC+CO2+ Lurex3 showed similar performance in colder and drier months of the year. The use of these traps to capture certain taxa can be important point in the surveillance approach vector species. Studies with greater sampling effort should be made to evaluate the performance of the Mosquito Magnet Independence and CDC+CO +lurex3 traps changed environment in areas of Atlantic Forest.

Made available in DSpace on 2016-08-17T14:53:17Z (GMT). No. of bitstreams: 1 Ulysses Santos Sousa.pdf: 1410915 bytes, checksum: 88235f7f4a3bc07a4da1b27c23dc71ca (MD5) Previous issue date: 2011-05-13 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Cancer is one of the biggest health problems worldwide, and the breast cancer is the one that causes more deaths among women. Also it is the second most frequent type in the world. The chances of survival for a patient with breast cancer increases the sooner this disease is discovered. Several Computer Aided Detection/Diagnosis Systems has been used to assist health professionals. This work presents a methodology to discriminate and classify mammographic tissues regions in mass and non-mass. For this purpose the Shannon-Wiener‟s Diversity Index, which is applied to measure the biodiversity in ecosystem, is used to describe pattern of breast image region with four approaches: global, in circles, in rings and directional. After, a Support Vector Machine is used to classify the regions in mass and non-mass. The methodology presents promising results for classification of mammographic tissues regions in mass and non-mass, achieving 99.85% maximum accuracy. / O câncer é um dos maiores problemas de saúde mundial, sendo o câncer de mama o que mais causa óbito entre as mulheres e o segundo tipo mais freqüente no mundo. As chances de uma paciente sobreviver ao câncer de mama aumentam à medida que a doença é descoberta mais cedo. Diversos Sistemas de Detecção e Diagnóstico auxiliados por computador (Computer Aided Detection/Diagnosis) têm sido utilizados para auxiliar profissionais de saúde. Este trabalho apresenta uma metodologia de discriminação e classificação de regiões de tecidos de mamografias em massa e não massa. Para este propósito utiliza-se o Índice de Diversidade de Shannon-Wiener, comumente aplicado para medir a biodiversidade em um ecossistema, para descrever padrões de regiões de imagens de mama com quatro abordagens: global, em círculos, em anéis e direcional. Em seguida, utiliza-se o classificador Support Vector Machine para classificar estas regiões em massa e não massa. A metodologia apresenta resultados promissores para a classificação de regiões de tecidos de mamografia em massa e não massa, obtendo uma acurácia máxima de 99,85%.

Made available in DSpace on 2016-08-17T14:53:20Z (GMT). No. of bitstreams: 1 dissertacao Artur.pdf: 2614613 bytes, checksum: ccffca7646e98481fa69cd43bca77f03 (MD5) Previous issue date: 2012-04-13 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / This work purposes an investigation into the potential of characterization of textures of human faces in digital images using the diversity index. To this we developed a methodology that uses the retinex to normalization of lighting conditions, diversity indexes for feature extraction and Support Vector Machine as classifier. Several tests are performed using four bases of face images, each base with uniques characteristics that can be verified the usability of the indexes used. The results are very promising since in eighteen tests were reached accuracies over 95%. In addition, a sensitivity of 100% in a test case and false positive rate of 0.2%, indicating that the diversity index can be a good tool for describing textures of human faces. / O objeto de estudo deste trabalho é uma investigação sobre o potencial grau de caracterização de texturas de faces humanas em imagens digitais usando índices de diversidade. Para isto é desenvolvida uma metodologia que utiliza o retinex como técnica de normalização de iluminação, índices de diversidade para a extração de características e a Máquina de Vetores Suporte como classificador. Para isto são realizados vários testes utilizando quatro bases de imagens de faces, com várias características peculiares para que possa ser verificada a usabilidade dos índices utilizados. Os resultados obtidos são muito promissores, uma vez que em dezoito testes realizados, foram atingidas acurácias acima de 95%. Além disso, obtivemos sensibilidade de 100% em um caso de teste e taxa de falsos positivos de 0.2%, indicando que os índices de diversidade podem ser uma boa ferramenta para a descrição de texturas de faces humanas.

River restoration projects are being installed worldwide to rehabilitate degraded river habitat. Many of these projects focus on stream habitat improvement (SHI), and an estimated 60%of the 37,000 projects listed in the National River Restoration Science Synthesis Program focus on SHI for salmon and trout species. These projects frequently lack a sufficient monitoring program or account for the environmental costs associated with SHI. The present study used life cycle assessment (LCA) techniques and topographic effectiveness monitoring to quantify environmental costs on the basis of geomorphic change. This methodology was a novel approach to assessing the cost-benefit relationship of SHI. To test this methodology, two phases of the Lower Scotts Creek Floodplain and Habitat Enhancement Project (LSCR) were used as a case study. The LSCR was a SHI project installed along the northern coast of Santa Cruz County, California, USA. A limited scope LCA was used to quantify the life cycle impacts of raw material production, materials transportation, and on-site construction. Once these baseline results were produced, a topographic monitoring program was used to quantify the topographic diversity index (TDI) in pre- and post-project conditions. The TDI percent change was used to scale the baseline LCA results, which quantified the environmental impacts based on geomorphic change. Phase II outperformed phase I. Phase I had greater cumulative environmental impacts and experienced a 7.7 % TDI increase from pre- to post-project conditions. Phase II had 43% less cumulative environmental impacts and experienced a 7.9% TDI increase from pre- to post-project conditions. The impacts in phase I were greater because of the amount of material excavated to create off-channel features, which were a key feature of the LSCR. A scenario analysis also was conducted within the LCA component of this study. The scenario analysis suggests that life cycle impacts could be reduced by 30%-65% by using the accelerated recruitment method in place of importing materials to build large wood complexes. The results of this study suggest that managers may improve the environmental performance of SHI projects by: (1) using the accelerated recruitment method to introduce larger key pieces to the channel, reducing the need to import materials; (2) using nursery grown plants as opposed to excavating plants for revegetation; (3) minimizing fuel combustion in heavy equipment and haul trucks by ensuring clear access to the channel and streambank, using small engine equipment to clear access corridors during site preparation, running more fuel-efficient machinery or bio-fuel powered machinery, and by attempting to minimize haul distances by sourcing materials locally; and (4) utilizing a “franken-log” design (a ballasted LWC configuration with a rootwad fastened to the downstream end of a log) in LWCs which led to favorable TDI change. This study concluded that LCA could be a valuable tool for monitoring SHI and river restoration projects and that further research of the TDI analysis is justified.

MSCAGR (Plant Production) / Department of Plant Production / Indigenous trees play important roles in livelihoods for rural communities. Sclerocarya birrea and Berchemia discolor are indigenous in Africa and are used in rural communities for food and livestock feed, as well as for medicinal and construction purposes. These trees are subject to attack by insects, which can result in lower tree productivity. However, there is no documented information about insects found on both tree species in South Africa. This study investigated the seasonal abundance and diversity of insects on S. birrea and B. discolor in Tshikundamalema Area, Limpopo Province, South Africa. Five trees were selected for each of the two tree species at two sampling sites with different vegetation cover, one site mainly the woodland bushveld while the other site was savannah grasslands. Canopy fogging was used to sample insects. Insect samples were collected at one time point for each of the seasons: summer (February), autumn (May), winter (July) and spring (November). Insects were identified to morphospecies and Simpson’s diversity index was used to compare insect diversity on both trees. Analysis of variance was used to compare the abundance of insects across seasons. The most abundant insects were collected from Coleoptera, followed by Hemiptera, Hymenoptera, Diptera, Lepidoptera and Orthoptera. A total of 3259 insects belonging to the six Orders were collected. All specimens belonging to Coleoptera, Hemiptera and Hymenoptera (3216 in total) were identified to Family level, with a total of 97 morphospecies, belonging to 19 Families. Insects from Diptera, Lepidoptera and Orthoptera were not identified further due to their low numbers. The abundance and diversity of insects were affected by seasons, sites and tree species. The number of insects was high during the spring season with 1782 insects, and summer coming second with 1104 individuals, followed by autumn (238 insects), then winter (92). B. discolor sampled for a great number of insects (1741) as compared to S. birrea (1475). The woodland bushveld (1924 insects) surpassed the savannah grassland (1292 insects) site in terms of the insect numbers sampled. / NRF