Clues and Stumbling Blocks to the Understanding of Florida Soils Acknowledgments: Personnel who contributed to the Florida Soil Survey Program. Data generated through their effort prompted research & ideas reported in this talk. Collaboration of UF Soil and Water Science colleagues and students. Florida soil scientists who shared soil photographs.

Topics Addressed Stumbling Blocks –Terms that mislead –Logic of USDA soil taxonomy –Misunderstanding about Entisols –Horizon designation that mismatch genetic context Clues –Sand grain coating composition and stability –Trends across E-Bt boundaries –Trends across E-Bh boundaries

Stumbling Blocks

Terms that mislead: Bh horizons as “hardpans”

MyakkaVery friable Many fine & medium roots LeonFirm to friable Common fine & medium roots ImmokaleeFriable to loose Common fine & medium roots Wabassofriable Common fine & medium roots Bh horizon consistence & roots as described on OSDs of Alaquods of large extent Data that do NOT support presumptions of Bh being a “hardpan” Terms that mislead: Bh horizons as “hardpans”

Data that do NOT support presumptions of Bh being a “hardpan” Means of selected data for Bh, Bh1, Bh2, and Bh3 horizons sampled during the Florida Soil Survey Program Saturated Hydraulic Conductivity cm/h Bulk Density g/cm -3 Organic Carbon % Clay % Non- Ortstein (vfr or fr) n= n= n= n=466 Ortstein (vfi or fi) 8.05 n= n= n= n=43 Terms that mislead: Bh horizons as “hardpans”

Lake, etc. Candler, etc.St. Lucie, etc. “Coated”“Uncoated” Has Fe & Al No Fe & Al Some P retention No P retention Grains un-stripped Grains stripped Terms that mislead: Family “Coated” – “Uncoated” distinction

Following logic of USDA soil taxonomy Fine-loamy, mixed, semiactive, mesic Typic Hapludults (+ series RIC) Chester Series 8-15 °C % clay; >15% coarser than VFS <90% quartz & Resistant minerals In sand Argillic (Bt) horizon; Base saturation m below upper Bt boundary; Relative well drained; Udic moisture regime; Clay content decrease with depth at prescribed rate Not intergradient CEC/g clay = Can we “find out” what a series is by sampling a soil body?

Following logic of USDA soil taxonomy

Animal Classification Boundaries of individuals: Are observable & independent of observer Are not arbitrary Can’t be altered (without harm to animal!) USDA Soil Classification Boundaries of individuals: Are NOT observable or independent of observer ARE arbitrary (conceptually established by consensus) CAN BE and ARE periodically altered (by consensus) Following logic of USDA soil taxonomy

Logic of USDA soil taxonomy: Entisols 185 cm 205 cm 210 cm 195 cm 190 cm 201 cm 185 cm Ult Ent What if depth of classification was 250 cm? 185 cm 205 cm 210 cm 195 cm 190 cm 201 cm 185 cm Ult OK, … as long as we don’t presume “Entisol” = recent or un-weathered Consider common FL distinction – Entisols (Bt > 2m) and Ultisols (Bt ≤ 2m) Old geomorphic surface

Bt ≤200 cm Ultisol “Pedon” >150 cm Entisol “Pedon” Ultisol “Pedon” ≤150 cm Change to 150 cm We could cleave boundaries of an Ultisol pedon, converting part to an Entisol e.g., … & still have an Ultisol We could cleave boundaries of an ostrich … … but we’d no longer have the ostrich … … so let’s not do it Logic of USDA soil taxonomy: Entisols

So what IS an Entisol? Key to Soil Orders Blah blah blah Gelisols Blah blah blah Histosols Blah blah blah Spodosols Blah blah blah Andisols Blah blah blah Oxisols Blah blah blah Vertisols Blah blah blah Aridisols Blah blah blah Ultisols Blah blah blah Mollisols Blah blah blah Alfisols Blah blah blah Inceptisols Other soils Entisols Take Home All very recent and un-weathered soils are Entisols ( … maybe) But … Not all Entisols are recent and un- weathered (especially in Florida)

Ortega Blanton A EC A Bt Horizon designation mismatching genetic context

Ortega Blanton A A CE Bt “Inert sand” precluded pedogenesis Intense pedogenesis produced “inert sand “ “Inert sand” It can’t be both! Horizon designation mismatching genetic context

Duette St. Lucie A A CE Bh Horizon designation mismatching genetic context: Case of “Giant Podzols” Horizon designation should precede & remain independent of soil classification

Clues

Florida Soil Survey Data Tell a Story E-Bt mineral distributions

? In effect … No matter how deep the boundary, clay mineralogy changes there

Ap E Bt Btg Example, one of many

Bw E Coated vs. Clean Sand Grains High HIV in clay Conclusion: HIV is large proportion of small amount of clay in grain coatings No HIV In clay

Coated vs. Clean Sand Grains (cont.) Coated Clean Coated Lakeland MyakkaSt. Lucie … in Panhandle & N. Central Florida … no matter how deep or thick Coated = high HIV in clay Clean = high quartz, maybe smectite in clay

Coatings Patchy, not uniform About 2-8 % of sandy soil mass Contain similar proportions of silt & clay Silt – mostly quartz Clay – quartz, phyllosilicates, gibbsite, & oxides of Al & Fe NOT “iron oxide coatings”, although … Al- & Fe oxides largely control P sorption Al- & Fe oxides serve as “cement” Characteristics of Sand Grain Coatings

HIV-rich silts have platy grains containing K Potassium as a Clue …

HIV But despite K, mica evades detection by x-ray diffraction X-ray diffraction pattern of HIV concentrated in Medium silt gibbsite quartz (mica peak would be here)

A Glimpse of Ghostly Mica … Finally! Evidence of occluded mica zones in HIV grains 1.0-nm lattice fringe image of mica in HIV grain

Mica – Metal Oxide – Grain Coating Connections: Mica as a Ghostly Clue … Theory to explain HIV-kaolinite distribution Non-quartz mineral abundance grossly exaggerated for illustration purposes. (Mica is considered a weatherable mineral, too.)

To Bt Mica as a Ghostly Clue … Theory to explain HIV-kaolinite distribution (cont.) Clay dispersed & mobilized New clay generated by weathering Mica weathers in-situ Al- & Fe oxides form and bind other components Mica products (HIV) & some kaolinite become incorporated into coatings HIV less subject to eluviation than kaolinite, explaining depth trend

E-Bh and fluctuating water table Sand grain coatings are again clues …

Conclusions Words ill chosen lead to misunderstanding (e.g., “hardpan”) & hamper communication (e.g., “uncoated”) Not following logic of USDA soil taxonomy can lead to misunderstanding (e.g., case of Florida Entisols) Horizon designation precedes & remains independent of soil classification Soil survey data are a powerful resource in understanding soil genesis Sand grain coatings & their distribution are major clues to genesis of Florida soils

Consider Ultisol vs Alfisol soil orders: <35% vs ≥35% Base Saturation (BS) A E Bt C 33% BS A E Bt C 38% BS A E Bt C 30% BS A E Bt C 36% BS A E Bt C 34% BS A E Bt C 39% BS A E Bt C 31% BS A E Bt C A E Bt C A E Bt C A E Bt C A E Bt C A E Bt C A E Bt C Ult Alf What if BS distinction had been set at 30%? Alf Following logic of USDA Soil Taxonomy

A E Bt C 33% BS A E Bt C 38% BS A E Bt C 30% BS A E Bt C 36% BS A E Bt C 34% BS A E Bt C 39% BS A E Bt C 31% BS Ult What if BS distinction had been set at 40%? Ult Soil classes Have arbitrary boundaries Can’t be populated by sorting discrete individuals Properties of Series are heavily constrained by hierarchical boundaries Yup, all Ultisols Following logic of USDA Soil Taxonomy

Implications of this distinction: It’s meaningful to measure & compare properties of classes or individuals defined by discrete immutable natural boundaries. EX, blood pressures of elephants vs. ostriches It’s NOT meaningful to measure and compare properties of classes or individuals with arbitrarily-defined boundaries One can’t “find out” what an Entisol, Ultisol, Alfisol, Chester series, etc., etc. is by sampling them because …. You can’t “see” them Their properties are largely constrained by their defined class boundaries Following logic of USDA Soil Taxonomy