Publications by Jonathan Spiess
Veg Community
Overview I summarized plant species, structural environmental variables, and plant functional group data to the patches within each pasture for each year. Despite some seperation between speceis and functional groups, there is not a lot of explanation found in our environmental variables. Summarizing by the patch instead of each transect helped w...
1684 sym R (31458 sym/31 pcs) 7 img
Veg Structure Stats and Graphs
Overview Mostly showing graphs and yearly Tukey’s for now Consistent patch contrast across variables except for 2019 No differences between grazer treatments VOR Graphs VOR Stats VORt17a <- lmer(log(VOR_Mean+1) ~ TSF + (1|Transect/Pasture), data=subset(HRECVeg, Year=="2017"), REML = FALSE) Mult_VOR17a <- glht(VORt17a, linfct=mcp(TSF = "Tuke...
526 sym R (18083 sym/62 pcs) 28 img
Forage Graphs
KgHa ## boundary (singular) fit: see ?isSingular ## boundary (singular) fit: see ?isSingular ## boundary (singular) fit: see ?isSingular ## boundary (singular) fit: see ?isSingular ## Data: HRECSIOmit ## Models: ## KgHaNull: log(KgHa + 1) ~ 1 + (1 | Location/Month/Year) ## KgHaG: log(KgHa + 1) ~ Treatment + (1 | Location/Month/Year) ## Kg...
332 sym R (65344 sym/130 pcs) 7 img
Veg Structure Stats and Graphs
Overview Mostly showing graphs and yearly Tukey's for now Consistent patch contrast across variables except for 2019 No differences between grazer treatments VOR Graphs VOR Stats ## boundary (singular) fit: see ?isSingular ## Data: HRECVeg ## Models: ## VORnull: log(VOR_Mean + 1) ~ 1 + (1 | Transect/Pasture/Year) ## VORm: log(VOR_Mean + 1) ~...
875 sym R (71952 sym/169 pcs) 28 img
Chapter 2 Workbook
ADG vs patch contrast Weight Gains Questions/Hypothesis Are animals gaining weight each year? -I expect average daily gain to be positive for each livestock class each year Do weight gains differ between years for any livetock class? -I do not expect years to differ despite variable precipitation Results Gain, Hold, or Lose ## ## Simultan...
2984 sym R (30620 sym/70 pcs) 21 img 2 tbl
Soil Models May
Total C TCnull <- lmer(log(TotalC_percent+1) ~ 1 + (1|Location/Year), data=SoilJuly181920, REML = FALSE) TCT <- lmer(log(TotalC_percent+1) ~ TSF + (1|Location/Year), data=SoilJuly181920, REML = FALSE) TCE <- lmer(log(TotalC_percent+1) ~ ESD + (1|Location/Year), data=SoilJuly181920, REML = FALSE) TCTE <- lmer(log(TotalC_percent+1) ~ TSF + ESD +...
245 sym R (50906 sym/132 pcs)
HREC PBG Veg Community
Overview Data Transformation ## Yo. 91 species (94.7916666666667% of total) don't make the cut. HREC Relative Abundance Ends at PASM; more species than the proportion filter Structure Ordi Setup StSp.MDSe <- metaMDS(StrSpeHREC, k=3, trymax=50, distance="euclidean") ## Wisconsin double standardization ## Run 0 stress 0.04709878 ## Run 1 st...
854 sym R (39343 sym/45 pcs) 12 img
HREC PBG Veg Variance Partitioning
Model Construction Everything summarized to the transect instead of including transect I then summarized the sdcor values by Year, variable, and random effect grouping for graphing purposes. VOR VP Calc knitr::kable(VORvar) Block Model Variable Year grp var1 var2 vcov sdcor C VOR20C VOR 2020 Management:Patch (Intercept) NA 0.1481627 0.3849191 ...
825 sym R (12879 sym/51 pcs) 9 img 10 tbl
Month?
Overview I need to do a few things with month, and the last one keeps putting me on a fun loop of repeating the same thing over and over. 1: Look for differences in TSF, ESD, or Grazer Type across seasons and years Solution: Fully nested random effect (1|Location/Month/Year) 2: Look for differences in TSF, ESD, or Grazer Type over individual graz...
1497 sym R (18565 sym/34 pcs) 1 img
HREC TSF Summaries
Soils Inorganic N TSF knitr::kable(SummarySoilNtsf) TSF species mean Sd Se 1yr < NH4_ppm 9.40948 9.40860 1.10881 1yr < NO3_ppm 4.79491 2.46950 0.29103 1yr - 2yr NH4_ppm 8.97969 10.88984 1.28338 1yr - 2yr NO3_ppm 4.87418 3.84448 0.45308 2yr - 3yr NH4_ppm 12.14896 10.89741 1.57291 2yr - 3yr NO3_ppm 4.57292 3.94534 0.56946 3yr - 4yr NH4_pp...
149 sym R (231 sym/8 pcs) 8 tbl