Gains and Constraints to Forest Productivity: A Perspective from the Southeastern U.S.

Transcription

1 Gains and Constraints to Forest Productivity: A Perspective from the Southeastern U.S. Eric J. Jokela 1/, Thomas R. Fox 2/, and Timothy A. Martin 1/ 1/ School of Forest Resources & Conservation, University of Florida 2/ Dept. Forest Resources & Environmental Conservation Virginia Tech

2 Overview The success story of loblolly pine plantation silviculture Where did we start from? How far have we come? Where are we going? Research opportunities for enhancing levels of forest productivity

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4 Complex Problems Require Multi-Disciplinary Solutions Silviculture, Soils & Ecophysiology Genetics Pathology

5 Processes Controlling/Limiting Stand Productivity LAI Light Use Efficiency Nutrient and Water Demand and Supply GENOTYPE Size-Density Relationships Pests Dry Matter Allocation

6 Number of Hectares of Southern Pine Plantations in the U.S. USFS FIA Data

7 Contribution of Silvicultural Practices to Productivity Improvements and Rotation Lengths in Managed Southern Pine Stands Volume at Harvest (m3 / ha) Rotation age (years) Establishment Decade Natural Stand Planting Site Prep Fertilization Weed Control Tree Improve Biotech/Clonal Rotation Age 0 Redrawn from: Fox, T.R., E.J. Jokela and H.L. Allen The development of pine plantation silviculture in the southern United States. J. Forestry 105:

8 When visioning about the future it can be useful to think about the past. P added However, changes that occurred in the past can not always predict the future, but they can be useful for defining the framework for reaching the new objectives.

9 Research Agenda in Support of Achieving Large Gains in Defining the target Productivity Models: trust but verify; incorporate biology and genetics Multi-rotation nutrient management Carryover effects; better understand the understory and forest floor as sources and sinks for nutrients Beyond N and P Using genetics to manage nutrition Genetic interactions LAI, ideotypes, and nutrient use efficiency Inter-tree competition and density management Genetic deployment in potentially novel climates

10 Defining the Target Defining and understanding potential productivity is still an elusive concept Models are central to summarizing what we can expect in particular situations G&Y models will always be chasing new technology Incorporating data from experiments and productive operational stands will remain important Improve incorporation of mechanism and genetics in modeling efforts Iteration between process and G&Y models

11 Defining the Target 13 yr-old Loblolly Pine Gulf Co, FL No Fert or Weed Control 30 m 3 /ha Fert + Weed Control 294 m 3 /ha

12 Growth of Loblolly Pine in Argentina 1 year old 2 years old 4 years old Thinned + Pruned

13 Pinus taeda in Brazil 35 Site Index Curves for Pinus taeda in the U. S. Dominant Height (m) Age (years) SI=16.8 SI=19.8 SI=22.9 SI=25.9 SI=29.0

14 Coordinating Treatments is Central to Integrated Forest Management C L I M A T E Nutrient Management Competition Control 2 2 *** LEVEL 1 *** Genetic Deployment (growth, I, D) Density Management S O I L S

15 FERTILIZATION Primarily N and P Near Establishment and at Mid-rotation

16 History of Forest Fertilization in the Southern U.S. From: Albaugh et al. 2011; Forest Productivity Cooperative

17 Soil Variability Site Specific Silvicultural Fertilization Prescriptions Based on Soils, Geology and Stand Conditions Soil Map as a GIS Layer

18 Technology for Precision Silviculture Prescriptions

19 CRIFF A B C Soil Groups D E F G

20 High Organic Matter Content Low High Nitrogen Availability Low Very Poorly Drained Clay With Shallow Bt Poorly Drained Sandy Clay Loam with 4-6 Surface Somewhat Poorly Drained Sandy Clay Loam with >20 Surface Poorly Drained Spodic with Sandy Clay Loam

21 Loblolly Pine Mid-rotation Fertilization 8-Year Growth Responses Volume Response (m 3 ha -1 ) P Rate (kg ha -1 ) Nitrogen Rate (kg ha -1 ) Fox et. al. 2007

22 Nutrient Supply Controls Leaf Area Development Mean All-Sided LAI (m 2 m -2 ) Pinus elliottii Age (years) Control Herbicide Fertilize Fert+Herb

23 LAI effects on Growth Response to Fertilizer SR = ((Treatment Growth - Stand Average Growth) / std dev) x (cv + 100) Standardized response Rojas 2004 R 2 = LAI

24 Estimate Leaf Area From the Ground Leaf Area Charts

25 Use of Landsat to Determine Leaf Area Reflectance (%) Control Fertilized Wavelength (um) Reflectance Spectrum

26 4.0 Remote Sensing Estimation of LAI Using Landsat Imagery LAI y = 0.59x - 1 R 2 = Simple Ratio Flores et al (SR=NIR/R)

27 Estimated Stand Peak LAI LAI Class > 3.5

28 LAI Determined From Lidar LAI Predicted LAI = (Veg mean ) (Veg 20th ) (LPI) (I mean ) (Cd+1) (Cd-4) 6 NSD 897 TPH control NSD 897 TPH fertilized NSD 1794 TPH control 5 NSD 1794 fertilized Henderson control Henderson vegetation control 4 SETRES control SETRES fertilized, irrigated or both RW18 control and thinned 3 RW18 fertilized unthinned RW18 fertilized and thinned RW19 fertilized 2 1:1 Line 1 0 R 2 = 0.83 RMSE = 0.45 CV-RMSE = LAI Observed Peduzzi et al. 2012

29 Using Lidar to Separate Overstory and Understory Leaf Area Deciduous Hardwood Leaf Area In Pine Stands

30 Top of Canopy Fert HTLC Understory Ground Relief

31 Potassium and Micronutrients

32 Cumulative Volume Growth in Loblolly Pine Average Across All Sites 140 Volume (m 3 /ha) Yr 6 Yr 4 Yr 0 Control NP NPK NPK+ Carlson et al. 2014

33 Site Specific Response to to Potassium and Micronutrient Fertilization With Elevation Carlson et al. 2014

34 Loblolly Pine Response to K and Micronutrient Fertilization Carlson et al. 2014

35 Location of K Deficiencies on Pleistocene Terraces in Georgia

36 What About Micronutrients? No Problem!

37 Problem! Cu deficiency on wet Bunnell, FL loblolly pine PPINES

38 Problem with a genetic component! Family-specific loblolly pine Cu deficiency on wet Spodosols Bunnell, FL

39 Micronutrient Limitations Rep 1 Trt 3 Cu Mn Mo All B Fe Zn Nil Treatment 0 = 0-N 1 = 100-N 2 = 200-N 3 = 300-N Rep 1 Trt 0 Rep 2 Trt 3 Cu Mn Mo All Cu Mn Mo All Rep 1 Trt 2 B Fe Zn Nil Cu Mn B Fe Zn Nil Rep 1 Trt 1 Cu Mn Mo All Mo All Nil Rep 2 Trt 0 Cu Mn Mo All Rep 4 Trt 1 Cu Mn Mo B Fe Zn Nil B Fe Zn B Fe Zn Nil B Fe Zn Nil All Rep 2 Trt 1 Rep 2 Trt 2 Rep 4 Trt 3 Measurment Plot 18.2 X 7.3 m Cu Mn Mo All Cu Mn Mo All Nil Cu Mn Mo All Mico treatment plot 19.8 X 7.3 m N loading plots 42.6 X 40.2 m B Fe Zn Nil Rep 3 Trt 0 Cu Mn Mo All B Fe Zn Rep 3 Trt 1 Cu Mn Mo B Fe Zn Nil Rep 4 Trt 20 Cu Mn Mo All Total tretment size 50.2 X 47.5 m B Fe Zn Nil B Fe Zn Nil All B Fe Zn Nil 0.95 ha/rep Rep 3 Trt 2 Rep 3 Trt 3 Rep 4 Trt ha/ site Cu Mn Mo All Cu Mn Mo All Cu Mn Mo All B Fe Zn Nil B Fe Zn Nil B Fe Zn Nil

40 Micronutrient deficiencies can limit production Sub-acute nutrient stresses can be induced by intensive management (soil supply/stand demand) Mn, Cu, B, Zn micronutrients of concern Slash pine response to Mn additions over 16 yrs 2.3 m 3 /ha/yr Source: Jokela et al Soil Sci. Soc. Am. J.

41 Taxonomically similar Spodosols, but with much different levels of micronutrient supply Loblolly pine site Zn Cu Slash pine site Concentration (ppm) A,AE E, Bh Bh, Bh2, E' Bt Concentration (ppm) A E, A2,Bh Bh,E Btg, Bt1 Vogel and Jokela SSSAJ 75:

42 Understanding Inter-rotational Effects of Silvicultural Treatments on Productivity 350 Loblolly Pine 350 Slash Pine Forest C pools (Mg C ha -1 ) Forest C pools (Mg C ha -1 ) Vegetation 0 Control F W FW Treatment 0 Control F W FW Treatment Soil Detritus Forest Floor Vegetation Results Vegetation carbon follows patterns in Basal Area: But Total Ecosystem Carbon Follows the pattern: F > FW > W > C Vogel et al. Can J. For. Res. 41:

43 Forest Floor/Understory Plants Nutrient Sink / Source?

44 Understanding Inter-rotational Effects of Silvicultural Treatments on Productivity Subedi et al SSAJ

45 Total aboveground loblolly pine biomass accumulation for second rotation loblolly pine stands growing at the IMPAC II study on Spodosols in north Florida. Error bars represent standard deviations.

46 Soil P supply and aboveground pine biomass in untreated carryover plots Aboveground pine biomass at age 3 year (Mg/ha) CC CF CFW CW Aboveground pine biomass Soil P supply rate Soil supply rate (micrograms/10cm2/8 week) at 15 cm depth Aboveground pine biomass R² = Soil P supply rate Subedi et al. 2014

47 Total nutrient accumulation in aboveground biomass of pine and understory at age 2 years Untreated carryover plots N content (kg/ha) CC CF CFW CW 20 3 P content (kg/ha) Mn content (kg/ha) CC CF CFW CW 0 CC CF CFW CW Understory Loblolly pine

48 Understanding and Managing the Understory Community Competitors vs. nutrient cyclers Trading herbicide for fertilizer may have sustainability implications (especially on sandy soils) Forest floor C Soil C at depth Prescribed fire

49 Tree Improvement (Regional Breeding Cooperatives Since the 1950 s) Disease Resistance Growth Form Wood Quality Fusiform Rust (Cronartium quercuum f. sp. fusiforme)

50 Genetic Analysis Requires A Well Designed Population & Intensive Phenotyping Population = CCLONES 1 Partial diallel of 43 parents 71 full-sib families genotypes per family 1212 clonal genotypes, propagated as rooted cuttings In 2002, 47,408 ramets & seedlings were planted at six sites and managed with operational and intensive treatments Tree Size Height, DBH Shoot phenology Crown Width, height of live crown, branch angle, branch diameter, Needle delta 13 C Wood Chemistry, density, MOE, stiffness Disease Tip moth Fusiform rust resistance Field & screening center Pitch canker resistance Southern pine beetle Resin canal #, resin flow

51 Analytical Approaches Used Successfully Quantitative Genetics Heritability estimates for selection & genetic gain predictions Genetic x environment interactions Genetic correlations Association Genetics Identify gene candidates for selection and genetic engineering Genomic Selection Predict traits from genetic variants for accelerated selection and breeding

52 Status Addition of 50,000 SNP markers nearly complete Genomic Selection Established that predictive models with good accuracies can be developed for most traits Developing mate selection Testing current models with crosses in progress Candidates for oleoresin yield are being transformed into loblolly pine to identify genes that regulate resinosis

53 Understanding Interactions of Genetics with Management

54 Genotype x Environment Increasing Crop Yield Genotype A Genotype B Genotype C Genotype D Increasing site resources and/or reduction in stress

55 PPINES Experimental Design (example Block) Silviculture (2) Intensive Operational Spacing (2) Narrow tpa Wide tpa Full-sib Families (7) Poor family 6 elite families Mix of elite mix mix LEGEND = Low Culture = High Culture 2 x 2 x 8 factorial, planted in a randomized complete block splot-plot design = Low Density = High Density 5 4 mix 2 mix x 2 x 8 factorial, planted in a randomized complete block split-plot design

56 Sanderson, Florida 400 m

57 Families vary in their response to management intensity Stem Volume (ft 3 /ac) Loblolly PPINES, Age 12, Waverly, GA L1 L2 L4 L5 L7 L8 L Culture H 550 Consistent response Stem Volume (ft 3 /ac) 500 Interaction

58 Competition vs. Crop ideotypes Competition Ideotype Large, spreading crown Aggressive root system Rapid growth through aggressive competition with neighbors Crop Ideotype Narrow, compact crown "Contained" root system Rapid growth through efficient utilization of resources Understanding intergenotypic competitive interactions helps predict phenotypic performance, define growth strategies, and aid in deploying the correct mix of families with complimentary characteristics. Less aggressive competition with neighbors Donald 1968, Cannell 1978, Dickman 1985

59 Potential benefits of crop ideotypes Efficient conversion of resources Greater stand uniformity due to decreased inter-tree competition Increased carrying capacity??

60 Crop ideotypes may be difficult to detect in traditional progeny trials Early selection for growth before crown closure may favor isolation ideotypes Selection after crown closure may favor competition ideotypes Poorly-competing crop ideotypes may be outcompeted in mixed-genotype progeny trials

61 Family x Deployment Interaction Crop ideotypes should maintain high productivity in pure plots, but show decreased productivity in mixture with other genotypes Crop Ideotype in Pure Family Deployment Crop Ideotype in Mixed Family Deployment

62 Year 7 Family x Deployment (pure vs. mixed) Interaction for Volume (Loblolly) Only deployment interaction had rank changes 2000 Putative Competition Ideotype Putative Crop Ideotype Volume (ft 3 /ac) M P 0 L1 L2 L4 L5 L7 L8 L8 (putative crop ideotype) had: 14% greater stemwood / crown volume than L4 (p=0.003) Smaller crown volume than L4 (p=0.0003) (Staudhammer et al Can.J.For.Res. 39: )

63 Age 5: Narrow Crowned Clone ARB-1 is Less Competitive than Wide-Crowned ARB Narrow Crown Crop Ideotype Wide Crown Competition Ideotype Crop Ideotype in Pure Taxon Deployment Stem Volume (cubic feet) p=0.04 p=0.10 Crop Ideotype in Mixed Taxa Deployment 0 Mixed Pure Mixed Pure ARB-1 ARB-1 ARB-4 ARB-4 Deployment and Clone Age 5 year average individual tree stem volume in mixed clone and pure clone plots for a narrowcrowned clone (ARB-1) and wide-crowned clone (ARB-4) in the VARIETIES I study near Starke, FL.

64 Clones Vary in Their Leaf Area Efficiency Productive, narrow-crown clone

65 Managing nutrients with genetics Deploying smallcrowned, efficient taxa may Increase efficiency of fertilizer Increase stand uniformity Influence carrying capacity Garcia, A. 2013

66 Is response to thinning under genetic control? Probably! Implications for Selecting for responders Planting density decisions and thinning in genetically diverse vs. family or clonal stands Inferences from old thinning studies may be colored by highly diverse genetic stock used in those studies

67 SSIGNS Site Specific Interactions of Genetics, Nutrition and Soils Experimental design: Randomized complete block design (RCBD) with two factors (split-plot) Nutrition regimes: 5 (Control, N+P, N+P+micronutrients*, N+P+macronutrients**, N+P+macros+micros) Genotypes: 30 (full-sib families) Blocks: 3 each consisting of 5 main-plots (one per nutrition level). Sub-plots: 2 (each with one copy of each genotype, forming interlaced blocks for projected thinning) Trials: 4 (sites per soil type; n=16) Soil types: 3-4 (e.g., CRIFF B, C, D, E, etc.) *Micronutrients: Cu, B, Fe, Mn, Mo; **Macronutrients: N, P, K, Ca, Mg, S

68 Intra-specific competition Reineke Stand Density Index (No. of trees at 10 in. (25 cm) average diameter) Long et al. 2004

69 Overstocking Limits Survival, Growth and Fertilizer Response With loblolly pine, reductions in survival and growth can occur at a basal area about 30 m 2 /ha. Jokela et al. 2004, For. Ecol Mgmt. 192:

70 Inter-tree competition and self-thinning Wide-crown competitor family Narrow-crown crop family

71 Loblolly Pine in South America Increased Carrying Capacity Argentina Brazil

72 Why Does Carrying Capacity Change in Other Parts of the World? Hawaii (and Brazil?) Argentina US South Brazil Hawaii USA

73 Loblolly Pine in NZ 99 yr old stand 73 TPA (180 TPHA) 370 ft 2 /ac (85 m 2 /ha) Dq = 30.6 in (78 cm) SDI = 438 (1082) Max SDI USA = 450 (1111) Max BA USA = 200 ft 2 /ac (46 m 2 /ha)

74 Understanding Genetic Deployment in a Changing World

75 PINEMAP: Pine Integrated Network: Education, Mitigation and Adaptation Project Google Earth The Pine Integrated Network: Education, Mitigation, and Adaptation Project (PINEMAP) is a Coordinated Agricultural Project funded by the USDA National Institute of Food and Agriculture, Award # For more information, visit A NIFA-Funded Climate Change CAP

76 NIFA Coordinated Agricultural Project ( CAP ) Program Climate Change Large (initially 5 yr, $20 million) commodity-focused projects (loblolly pine, wheat, corn) Multi/inter/transdisciplinary Include research, education, outreach Focus on climate mitigation and adaptation

77 Prescribed, Outcome Based Program Dictates Project Goals Reduce the use of (energy), nitrogen fertilizer, and (water) by 10% and increase carbon sequestration by 15% through resilient forest production systems under changing climate by 2030 Project research, education and Extension goals focused on achieving these outcomes

78 PINEMAP Approach: Integrating & Leveraging Existing Networks Project Learning Tree State Climatologists Extension Professionals: SREF, Land Grant & County Extension University Government - Corporate Forest Research Cooperatives Research Cooperative Cooperative Forest Genetics Research Program Cooperative Tree Improvement Program Forest Biology Research Cooperative Forest Modeling Research Cooperative Forest Productivity Cooperative Plantation Management Research Cooperative Southern Forest Resource Assessment Consortium Western Gulf Forest Tree Improvement Program Host University (year founded) University of Florida (1953) North Carolina State University (1955) University of Florida (1996) Virginia Polytechnic Univ. (1979) Virginia Polytechnic Univ. / NC State Univ. (1969) University of Georgia (1975) North Carolina State University (1994) Texas A&M Univ. / Texas Forest Service (1969)

79 PINEMAP Project Team 57 Principal Investigators 23 Research and Technical Staff 38 Grad Students 7 Postdocs At 11 land grants universities + USFS

80 Project Structured Around 6 Disciplinary Aims Silviculture and Field Ecology Monitoring network establishment and measurement Biophysical Modeling (3-PG Lob, WaSSI (Water Supply Stress Index predicts regional GEP relative to enviromental conditions (soil, H 2 O availability, solar radiation, air temp, LAI)) Genetics and Breeding Gene discovery and deployment guidelines Economics and Policy Life cycle assessment; multi-scale policy and regional economic analysis (simulates how land use and timber markets will respond to changes in wood supply and demand in relation to climate Education Educational and training programs for stakeholders and students Extension Extension program development and delivery

81 Silviculture and Field Ecology Establish a regionwide three-tiered monitoring network and standardized methods to quantify carbon, water, and nutrient storage and flux baselines and responses to climate and management.

82 Tier 1 Network Sharing Previously Unshared Data ~700 existing cooperative sites and data Data shared under PINEMAP guidelines Develop and test models Datasets assembled and being uploaded into a spatially explicit database

83 Tier 2 / Active Network ~125 existing cooperative experiments Additional intensive ecological and ecophysiological measurements (LAI, NPP, NEP, Soil Rs (R H + R A ) Develop and test models Sub-regional field crews perform standardized measurements

84 Tier 3 Network Pushing Loblolly Into the Future With Fertilizer and Throughfall Diversion Experiments 4 locations in existing, genetically diverse plantations on edges of range Replicated, factorial combination of 30% throughfall diversion and fertilizer Intensive biological and ecological measurements(lai, stomatal conductance, transpiration, NPP, NEP, Soil Rs (R H + R A )) Intended to simulate future stresses the species may encounter and for developing and parameterizing models under novel conditions Treatments initiated Spring 2012

85 McCurtain Co., OK

86 Cross-Range Genetics Trials from Three Cooperatives Developing Universal Response Functions using progeny trial and climate data from across region Will underlie development of deployment tool Testing genotyping methodology to aid identification of alleles associated with resilience traits

87 DSS Overview A web-based tool to synthesize PINEMAP research for forest landowners (industry, agency, Extension, etc.) Providing regional management guidance for a changing climate e.g., projected temperature and rainfall patterns on Productivity -- G&Y, ANPP; pest risks (southern pine beetle), seed source deployment Options for novice and advanced users

88 Summary Points Similarities Complimentary research agendas. Multidisciplinary approaches; Phenotyping, genomic selection e.g., Understanding resilience to climate change; Site specific silviculture prescriptions (tools); Carrying capacity (changing vs. accelerated).

89 Summary Points Differences Ideotypes relative to understanding growth strategies; Understanding genetic controls on thinning and fertilizer response; Role of soil symbionts

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