25) Chaves, W. A.; Valle, D.; Monroe, M. C.; Wilkie, D. S.; Sieving, K. E.; Sadowsky, B. 2017. Changing wild meat consumption: an experiment in the central Amazon, Brazil. Conservation Letters. doi: 10.1111/conl.12391
24) Valle, D.; Cvetojevic, S.; Robertson, E.; Reichert, B. E.; Hochmair, H. H.; Fletcher Jr., R. J. 2017. Individual movement strategies revealed through novel clustering of emergent movement patterns. Scientific Reports 7, 44052.
23) Baiser, B.; Valle, D.; Zelazny, Z.; Burleigh, G. 2017. Non-random patterns of invasion and extinction reduce phylogenetic diversity in island bird assemblages. Ecography 40:001-014.
22) Seva, A. P.; Mao, L.; Ovallos, F. G.; Tucker-Lima, J. M.; Valle, D. 2017. Risk analysis and prediction of visceral leishmaniasis dispersion in Sao Paulo State, Brazil. PLOS Neglected Tropical Diseases 11(2): e0005353
21) Tucker-Lima, J.; Vittor, A.; Rifai, S.; Valle, D. 2017. Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence. Philosophical Transaction of the Royal Society B: Biological Sciences 372:20160125
20) Valle, D.; Millar, J.; Amratia, P. 2016. Spatial heterogeneity can undermine the effectiveness of country-wide test and treat policy for malaria: a case study from Burkina Faso. Malaria Journal, 15:513.
19) Tucker-Lima, J.; Valle, D.; Moretto, E.; Pulice, S.; Zuca, N.; Roquetti, D.; Beduschi, L.; Praia, A.; Okamoto, C.; Carvalhaes, V.; Branco, E.; Barbezani, B.; Labandera, E.; Timpe, K.; Kaplan, D. 2016. A social-ecological database to advance research on infrastructure development impacts in the Brazilian Amazon. Scientific Data. 3:160071 doi: 10.1038/sdata.2016.71
18) Valle, D.; Tucker Lima, J. M.; Millar, J.; Amratia, P.; Haque, U. 2015. Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches. Malaria Journal, 14:434.
17) Valle, D.; Tucker Lima, J. M. 2014. Large-scale drivers of malaria and priority areas for prevention and control in the Brazilian Amazon region using a novel multi-pathogen geospatial model. Malaria Journal, 13:443.
16) Valle, D.; Baiser, B.; Woodall, C.; Chazdon, R. 2014. Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method. Ecology Letters, 17:1591-1601
15) Valle, D. 2014. Response to the critique by Hahn et al. entitled “Conservation and Malaria in the Brazilian Amazon”. Am. J. Trop. Med. Hyg., 90(4), pp. 595-596
14) Valle, D.; Clark, J. 2013. Improving the Modeling of Disease Data from the Government Surveillance System: a Case Study on Malaria in the Brazilian Amazon. PLOS Computational Biology 9(11): e1003312.
13) Valle, D.; Zaitchik, B.; Feingold, B.; Spangler, K.; Pan, W. 2013. Abundance of Water Bodies is Critical to Guide Mosquito Larva Control Interventions and Predict Risk of Mosquito-Borne Diseases. Parasites & Vectors, 6:179.
12) Valle, D.; Clark, J. 2013. Conservation Efforts May Increase Malaria Burden in the Brazilian Amazon. PLoS ONE 8(3): e57519.
11) Zhao, K.; Valle, D.; Popescu, S.; Zhang, X.; Mallick, B. 2013. Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sensing of Environment, 132, 102-119
10) Valle, D.; Berdanier, A. 2012. Computer programming skills for environmental sciences. Bulletin of the Ecological Society of America, 93.
9) Valle, D.; Clark, J.; Zhao, K. 2011. Enhanced understanding of infectious diseases by fusing multiple datasets: a case study on malaria in the Western Brazilian Amazon region. PLOS One, 6(11): e27462
8) Clark, J.; Bell, D.; Hersh, M.; Kwit, M.; Moran, E.; Salk, C.; Stine, A.; Valle, D.; Zhu, K. 2011. Individual-scale variation, species-scale differences: Inference needed to understand diversity. Ecology Letters, 14: 1273-1287
7) Valle, D. 2011. Incorrect representation of uncertainty on the modeling of growth leads to biased estimates of future biomass. Ecological Applications, 21(4), pp. 1031-1036
6) Clark, J. S.; Bell, D. M.; Chu, C.; Courbaud, B.; Dietze, M. C.; Hersh, M.; HilleRisLambers, J.; Ibanez, I.; LaDeau, S.; McMahon, S.; Metcalf, J. E.; Mohan, J. E.; Moran, E.; Pangle, L.; Pearson, S. F.; Salk, C. F.; Shen, Z.; Valle, D.; Wyckoff, P. 2010. High dimensional coexistence based on individual variation: a synthesis of evidence. Ecological Monographs, 80(4), pp. 569-608.
5) Valle, D; Staudhammer, C. L.; Cropper Jr., W. P.; van Gardingen, P. 2009. The importance of multimodel projections to assess uncertainty in projections from simulation models. Ecological Applications 19(7), pp. 1680–1692
4) Valle, D.; Staudhammer, C.; Cropper Jr., W. P. 2007. Simulating nontimber forest product management in tropical mixed forests. Journal of Forestry, 105, 6, 301-306.
3) Valle, D.; Phillips, P.; Vidal, E.; Schulze, M.; Grogan, J.; Sales, M.; van Gardingen, P. 2007. Adaptation of a spatially explicit individual tree-based growth and yield model and long-term comparison between reduced-impact and conventional logging in eastern Amazonia, Brazil. Forest Ecology and Management. 243: 187-198.
2) Valle, D.; Schulze, M.; Vidal, E.; Sales, M.; Grogan, J. 2006. Identifying bias in stand-level growth and yield estimations: a case study in eastern Brazilian Amazonia. Forest Ecology and Management. 236: 127-135.
1) van Gardingen, P.; Valle, D.; Thompson, I. 2006. Evaluation of yield regulation options for primary forest in Tapajós National Forest, Brazil. Forest Ecology and Management. 231: 184-195.
24) Valle, D.; Cvetojevic, S.; Robertson, E.; Reichert, B. E.; Hochmair, H. H.; Fletcher Jr., R. J. 2017. Individual movement strategies revealed through novel clustering of emergent movement patterns. Scientific Reports 7, 44052.
23) Baiser, B.; Valle, D.; Zelazny, Z.; Burleigh, G. 2017. Non-random patterns of invasion and extinction reduce phylogenetic diversity in island bird assemblages. Ecography 40:001-014.
22) Seva, A. P.; Mao, L.; Ovallos, F. G.; Tucker-Lima, J. M.; Valle, D. 2017. Risk analysis and prediction of visceral leishmaniasis dispersion in Sao Paulo State, Brazil. PLOS Neglected Tropical Diseases 11(2): e0005353
21) Tucker-Lima, J.; Vittor, A.; Rifai, S.; Valle, D. 2017. Does deforestation promote or inhibit malaria transmission in the Amazon? A systematic literature review and critical appraisal of current evidence. Philosophical Transaction of the Royal Society B: Biological Sciences 372:20160125
20) Valle, D.; Millar, J.; Amratia, P. 2016. Spatial heterogeneity can undermine the effectiveness of country-wide test and treat policy for malaria: a case study from Burkina Faso. Malaria Journal, 15:513.
19) Tucker-Lima, J.; Valle, D.; Moretto, E.; Pulice, S.; Zuca, N.; Roquetti, D.; Beduschi, L.; Praia, A.; Okamoto, C.; Carvalhaes, V.; Branco, E.; Barbezani, B.; Labandera, E.; Timpe, K.; Kaplan, D. 2016. A social-ecological database to advance research on infrastructure development impacts in the Brazilian Amazon. Scientific Data. 3:160071 doi: 10.1038/sdata.2016.71
18) Valle, D.; Tucker Lima, J. M.; Millar, J.; Amratia, P.; Haque, U. 2015. Bias in logistic regression due to imperfect diagnostic test results and practical correction approaches. Malaria Journal, 14:434.
17) Valle, D.; Tucker Lima, J. M. 2014. Large-scale drivers of malaria and priority areas for prevention and control in the Brazilian Amazon region using a novel multi-pathogen geospatial model. Malaria Journal, 13:443.
16) Valle, D.; Baiser, B.; Woodall, C.; Chazdon, R. 2014. Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method. Ecology Letters, 17:1591-1601
15) Valle, D. 2014. Response to the critique by Hahn et al. entitled “Conservation and Malaria in the Brazilian Amazon”. Am. J. Trop. Med. Hyg., 90(4), pp. 595-596
14) Valle, D.; Clark, J. 2013. Improving the Modeling of Disease Data from the Government Surveillance System: a Case Study on Malaria in the Brazilian Amazon. PLOS Computational Biology 9(11): e1003312.
13) Valle, D.; Zaitchik, B.; Feingold, B.; Spangler, K.; Pan, W. 2013. Abundance of Water Bodies is Critical to Guide Mosquito Larva Control Interventions and Predict Risk of Mosquito-Borne Diseases. Parasites & Vectors, 6:179.
12) Valle, D.; Clark, J. 2013. Conservation Efforts May Increase Malaria Burden in the Brazilian Amazon. PLoS ONE 8(3): e57519.
11) Zhao, K.; Valle, D.; Popescu, S.; Zhang, X.; Mallick, B. 2013. Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection. Remote Sensing of Environment, 132, 102-119
10) Valle, D.; Berdanier, A. 2012. Computer programming skills for environmental sciences. Bulletin of the Ecological Society of America, 93.
9) Valle, D.; Clark, J.; Zhao, K. 2011. Enhanced understanding of infectious diseases by fusing multiple datasets: a case study on malaria in the Western Brazilian Amazon region. PLOS One, 6(11): e27462
8) Clark, J.; Bell, D.; Hersh, M.; Kwit, M.; Moran, E.; Salk, C.; Stine, A.; Valle, D.; Zhu, K. 2011. Individual-scale variation, species-scale differences: Inference needed to understand diversity. Ecology Letters, 14: 1273-1287
7) Valle, D. 2011. Incorrect representation of uncertainty on the modeling of growth leads to biased estimates of future biomass. Ecological Applications, 21(4), pp. 1031-1036
6) Clark, J. S.; Bell, D. M.; Chu, C.; Courbaud, B.; Dietze, M. C.; Hersh, M.; HilleRisLambers, J.; Ibanez, I.; LaDeau, S.; McMahon, S.; Metcalf, J. E.; Mohan, J. E.; Moran, E.; Pangle, L.; Pearson, S. F.; Salk, C. F.; Shen, Z.; Valle, D.; Wyckoff, P. 2010. High dimensional coexistence based on individual variation: a synthesis of evidence. Ecological Monographs, 80(4), pp. 569-608.
5) Valle, D; Staudhammer, C. L.; Cropper Jr., W. P.; van Gardingen, P. 2009. The importance of multimodel projections to assess uncertainty in projections from simulation models. Ecological Applications 19(7), pp. 1680–1692
4) Valle, D.; Staudhammer, C.; Cropper Jr., W. P. 2007. Simulating nontimber forest product management in tropical mixed forests. Journal of Forestry, 105, 6, 301-306.
3) Valle, D.; Phillips, P.; Vidal, E.; Schulze, M.; Grogan, J.; Sales, M.; van Gardingen, P. 2007. Adaptation of a spatially explicit individual tree-based growth and yield model and long-term comparison between reduced-impact and conventional logging in eastern Amazonia, Brazil. Forest Ecology and Management. 243: 187-198.
2) Valle, D.; Schulze, M.; Vidal, E.; Sales, M.; Grogan, J. 2006. Identifying bias in stand-level growth and yield estimations: a case study in eastern Brazilian Amazonia. Forest Ecology and Management. 236: 127-135.
1) van Gardingen, P.; Valle, D.; Thompson, I. 2006. Evaluation of yield regulation options for primary forest in Tapajós National Forest, Brazil. Forest Ecology and Management. 231: 184-195.
