diff --git a/Project.toml b/Project.toml
index 252e2e2da..5e495f92e 100644
--- a/Project.toml
+++ b/Project.toml
@@ -3,7 +3,7 @@ uuid = "c7f686f2-ff18-58e9-bc7b-31028e88f75d"
 keywords = ["markov chain monte carlo", "probablistic programming"]
 license = "MIT"
 desc = "Chain types and utility functions for MCMC simulations."
-version = "7.2.2"
+version = "7.3.0"
 
 [deps]
 AbstractMCMC = "80f14c24-f653-4e6a-9b94-39d6b0f70001"
diff --git a/src/MCMCChains.jl b/src/MCMCChains.jl
index 0592a5014..141cade9b 100644
--- a/src/MCMCChains.jl
+++ b/src/MCMCChains.jl
@@ -3,7 +3,7 @@ module MCMCChains
 using AxisArrays
 const axes = Base.axes
 import AbstractMCMC
-import AbstractMCMC: chainscat
+import AbstractMCMC: chainscat, chainsstack
 using Distributions
 using RecipesBase
 using Dates
@@ -35,7 +35,7 @@ import LinearAlgebra
 import Random
 import Statistics: std, cor, mean, var, mean!
 
-export Chains, chains, chainscat
+export Chains, chains, chainscat, chainsstack
 export setrange, resetrange
 export set_section, get_params, sections, sort_sections, setinfo
 export replacenames, namesingroup, group
diff --git a/src/chains.jl b/src/chains.jl
index ee01675bf..39eeb7186 100644
--- a/src/chains.jl
+++ b/src/chains.jl
@@ -749,6 +749,7 @@ Base.hcat(c::Chains, cs::Chains...) = _cat(Val(2), c, cs...)
 Base.hcat(c::T, cs::T...) where {T<:Chains} = _cat(Val(2), c, cs...)
 
 AbstractMCMC.chainscat(c::Chains, cs::Chains...) = _cat(Val(3), c, cs...)
+AbstractMCMC.chainsstack(c::AbstractVector{<:Chains}) = AbstractMCMC.chainscat(c...)
 
 _cat(dim::Int, cs::Chains...) = _cat(Val(dim), cs...)
 
@@ -822,13 +823,13 @@ function _cat(::Val{3}, c1::Chains, args::Chains...)
         c -> get(c.info, :start_time, nothing),
         vcat,
         args,
-        init = get(c1.info, :start_time, nothing),
+        init = [get(c1.info, :start_time, nothing)],
     )
     stops = mapreduce(
         c -> get(c.info, :stop_time, nothing),
         vcat,
         args,
-        init = get(c1.info, :stop_time, nothing),
+        init = [get(c1.info, :stop_time, nothing)],
     )
     # Concatenate sampler states too. This is hacky(!) but required upstream in Turing.jl
     # because otherwise you cannot resume multiple-chain sampling.
@@ -836,7 +837,7 @@ function _cat(::Val{3}, c1::Chains, args::Chains...)
         c -> get(c.info, :samplerstate, nothing),
         vcat,
         args,
-        init = get(c1.info, :samplerstate, nothing),
+        init = [get(c1.info, :samplerstate, nothing)],
     )
     other_props = filter(
         x -> !(x in [:start_time, :stop_time, :samplerstate]),
diff --git a/test/concatenation_tests.jl b/test/concatenation_tests.jl
index 2b2b6772f..0fe3166b7 100644
--- a/test/concatenation_tests.jl
+++ b/test/concatenation_tests.jl
@@ -174,7 +174,7 @@ end
     @test chn2b.name_map == chn2.name_map
     @test chn2b.info == chn2.info
 
-    # check merging of info field
+    # check merging of info field for multiple-chain concatenation
     chn = Chains(
         rand(10, 3, 1),
         ["a", "b", "c"],
@@ -202,4 +202,24 @@ end
     @test chn3.info.samplerstate == ["state1", "state2"]
     # other fields should just be taken from the first chain
     @test chn3.info.otherinfo == "info1"
+
+    # for single-chain concatenation too
+    chn = Chains(
+        rand(10, 3, 1),
+        ["a", "b", "c"],
+        info = (
+            start_time = 1,
+            stop_time = 2,
+            samplerstate = "state1",
+            otherinfo = "info1",
+        ),
+    )
+    for new_chn in [chainscat(chn), chainsstack([chn])]
+        @test new_chn.value == chn.value
+        @test new_chn.name_map == chn.name_map
+        @test new_chn.info.start_time == [chn.info.start_time]
+        @test new_chn.info.stop_time == [chn.info.stop_time]
+        @test new_chn.info.samplerstate == [chn.info.samplerstate]
+        @test new_chn.info.otherinfo == chn.info.otherinfo
+    end
 end